材料设计中的机器学习，高分子材料和生物材料的模拟，神经网络分子动力学，QM/MM，AIMD，大规模模拟，高分子，酶反应，界面氧化还原与电子转移，量子化学软件（QChem, CP2K, Quantum Espresso, VASP），metadynamics 模拟，粗粒度力场开发
Machine learning for material design, simulations of polymers and biomaterials, Neural Network MD, QM/MM, AIMD, large-scale simulations, polymers, enzymatic reactions, interfacial redox and electron transfer, quantum software (QChem, CP2K, Quantum Espresso or VASP), metadynamics simulations, coarse-grained forcefield development

具有批判性思维的科学多模态基础模型、少样本科学知识获取、科学领域中的规划与推理、与物理世界交互的科学研究代理人、自然语言处理、基于文献的发现、人类参与的强化学习、科学家辅助人工智能（AI4Scientist）、科学语料库中的知识抽取、可解释人工智能、自主实验室
Scientific Multimodal Foundation Models with Critical Thinking, Few-Shot Scientific Knowledge Acquisition, Planning and Reasoning in Scientific Domain, Scientific Research Agents with Physical World Interactions, Natural Language Processing, Literature-based Discovery, Human-in-the-loop Reinforcement Learning, AI for Scientists (AI4Scientist), Knowledge Extraction from Scientific Corpora, Explainable AI, Self-driving Laboratories

面向商业和医疗保健应用的人工智能、机器学习和数据挖掘
AI, machine learning, and data mining for business and healthcare applications

机电一体化：传感器与驱动；机器人：动力学、建模与控制、人机交互、欠驱动机器人；机器学习：将物理学与机器学习相结合，提高机器人平台的控制质量和可靠性，并减小物理系统与机器学习之间的差距。
Mechatronics: sensors and actuators; Robotics: dynamics, modeling and control, human-robot interaction, underactuated robots; Machine Learning: integrating physics and machine learning to improve control quality and reliability of robotic systems, and reduce the gap between physical systems and machine learning.

人工智能、数据挖掘、机器学习、大语言模型、深度强化学习、自动机器学习、可信人工智能、多模态学习，以及在推荐系统、信息检索、城市计算、健康医疗等领域的应用。
Artificial Intelligence, Data Mining, Machine Learning, Large Language Models, Deep Reinforcement Learning, AutoML, Trustworthy AI, Multimodal Learning, and applications in Recommendation Systems, Information Retrieval, Urban Computing, and Healthcare.

人工智能安全、机器学习、联邦学习安全、优化
Artificial Intelligence Security, Machine Learning, Federated Learning Security, Optimization

前沿超快光学，太赫兹光谱技术，超快激光谱探测，低维材料的超快载流子动力学，量子材料的声子动力学，有机二维材料，非线性光学，时间分辨光谱技术如瞬态吸收和时间分辨荧光
Ultrafast optics, Terahertz spectroscopy, Ultrafast laser spectroscopy, Carrier dynamics in low-dimensional quantum materials, Phonon dynamics in quantum materials, Organic 2D materials, Nonlinear optics, Time-resolved spectroscopy techniques such as transient absorption and time-resolved fluorescence

Systems for DL/LLM (e.g., OS/Arch/Security); Systems and software security

vision, multimodality, 3D, generative models, representation learning, AI for science, AI for medicine, computationall imaging

Hardware security, VLSI design, computer engineering

Generative AI, AI Safety, Embodied AI, Agent

Gen-AI (e.g., Diffusion Model), AI4Science (e.g., Quantum), Deep Learning Theory (e.g., Optimization and Generalization)

Machine Learning, Reinforcement Learning, LLMs, Efficient Learning/Training, MLSys

Knoweldge Graph, Neural Graph Database, Retrieval Augmented Generation

Computer Vision, Large Language Model, Interpretable Machine Learning, Robotics

RL, GenAI (Diffusion models, LLMs); Health; Physics

Cybersecurity, Applied Machine Learning, Mobile Healthcare, Mobile Sensing

ML System, large scale LLM, multimodal, GPU optimization

Large Language Model (LLM), Bayesian Deep Learning, LLM Reasoning, Interpretable Machine Learning (ML), ML for Healthcare

Trustworthy AI, Reinforcement Learning, LLMs

Topological data analysis, Topological machine learning, Computational topology, Theory

ML security/privacy, ML for cybersecurity

cyber security, hardware security, sidechannel attacks, quantum computing

移动感知与计算系统；物联网中以人为中心的计算；结合无线/可穿戴设备与人工智能进行精准感知；利用无线信号和人体生理活动构建先进人机接口；使用手机和智能手表进行普适移动健康计算；构建低成本、低门槛、尊重隐私的健康计算系统；涵盖数据分析、信号处理、算法和硬件创新。
Mobile sensing and computing systems; human-centered computing in IoT; accurate perception with wireless/wearable devices and AI; advanced human-computer interaction using wireless signals and biological activity; ubiquitous mobile health using smartphones and smartwatches; low-cost, low-barrier and privacy-respecting health computing systems; data analytics, signal processing, algorithms, and hardware innovations.

分布式优化和机器学习算法，包括在网络化系统、控制和信号处理中的应用
Distributed optimization and machine learning algorithms, including applications in networked systems, control, and signal processing

单分子电子学，扫描隧道显微镜断裂结，热电和电化学性质，紧束缚建模和密度泛函理论计算
single molecule electronics, scanning tunneling microscope break junction, thermoelectric and electrochemical properties, tight-binding modelling and density functional theory calculations

物联网安全与隐私，用户隐私，合规性检测，软件安全，大语言模型代理的安全
IoT security and privacy, user privacy, compliance detection, software security, LLM agent security

机器人、机器视觉和人工智能在农业中的应用
Applications of robotics, machine vision, and artificial intelligence in agriculture

电力系统规划与运行、综合能源系统建模与分析方法、能源系统优化理论、电力市场机制设计。相关领域包括电气工程、数学优化、人工智能和能源经济。
Power system planning and operation, integrated energy system modeling and analysis methods, energy system optimization theory, power market mechanism design. Related areas include electrical engineering, mathematical optimization, artificial intelligence, and energy economics.

云系统，机器学习系统，系统安全，包括有机会研究具有安全特性的硬件并与工业界合作
Cloud systems, Machine Learning systems, System security, including opportunities to work on new hardware with security features and industry collaboration

大模型、生成式AI、数字人、3D计算机视觉、动作与舞蹈生成、3D高斯散射、数字音乐生成
Large models, Generative AI, Digital Human, 3D Computer Vision, Dance and Motion Generation, 3D Gaussian Splatting, Digital Music Generation

生医影像量化分析、计算成像、智能体等研究

1. 电力系统动态建模与仿真 2. 大语言模型与流程自动化
1. Power systems dynamic modeling and simulation 2. Large language models and process automation

用于机器人系统的3D视觉感知，基于点云的3D感知，不确定性估计，强化学习，视觉与语言，机器人规划
3D visual perception for robotics, point cloud based 3D perception, uncertainty estimation, reinforcement learning, vision and language, robot planning

人工智能安全，机器学习，联邦学习安全，优化
AI Security, Machine Learning, Federated Learning Security, Optimization

3D Computer Vision, Generative Models, Human Motion Modeling, Vision-Language Models, Shape Analysis, Transfer Learning

计算机体系结构，硬件安全，机器学习系统，CXL性能、安全性和编程模型，GPU架构和内存管理，大语言模型的系统优化
Computer architecture, Hardware security, Machine learning systems, CXL performance, security, and programming model, GPU architecture and memory management, System optimization for large language models

磁共振成像序列研发，磁共振领域的人工智能应用，医学数据采集及后处理
MRI sequence development, AI applications in MRI, medical data acquisition and post-processing

可信/可靠人工智能，自然语言处理（NLP），大型语言模型（LLM），计算社会科学，用于安全/网络安全的人工智能，数据不确定性，鲁棒性评估
Trustworthy / Reliable AI, natural language processing (NLP), large language models (LLM), computational social science, AI for security / cybersecurity, data uncertainty, robustness evaluation

先进材料、增材制造、多材料增材制造、组织/器官生物打印、可穿戴/植入式生物电子设备、软体机器人、可持续能源材料与系统。
Advanced materials, additive manufacturing, multi-materials additive manufacturing, bioprinting of tissues/organs, wearable/implantable bioelectronics, soft robotics, sustainable energy materials and systems.

神经形态计算、机器人学习、具身人工智能系统、类脑人工智能、与啮齿类动物神经数据的生物验证、空间导航、视觉感知、联想学习与记忆、海马神经信号处理
Neuromorphic Computing, Robotic Learning, Embodied AI Systems, Brain-Inspired Artificial Intelligence, Biological Validation with Rodent Neural Data, Spatial Navigation, Visual Perception, Associative Learning and Memory, Hippocampal Neural Signal Processing

机器人、无人机、人工智能、机器学习。平台包括移动机器人、飞行器、机械臂。研究内容包括学习、导航、决策、规划、控制。
Robotics, Unmanned Aerial Vehicles (UAVs), Artificial Intelligence, Machine Learning. Platforms include mobile robots, aerial vehicles, robotic arms. Research topics include learning, navigation, decision-making, planning, control.

人工智能、机器学习、数据科学、生物医学研究、健康信息学、大规模数据处理、智能信息抽取、计算建模、现代机器学习方法、深度学习（PyTorch/TensorFlow）、自然语言处理、软件工程、全栈开发、Python编程、数据工程、统计建模、生物医学和临床数据研究
Artificial intelligence, machine learning, data science, biomedical research, health informatics, large-scale data processing, intelligent information extraction, computational modeling, modern machine learning methods, deep learning (PyTorch/TensorFlow), natural language processing, software engineering, full stack development, Python programming, data engineering, statistical modeling, biomedical and clinical data research

量子信息科学、凝聚态物理、超导微波量子比特、量子传感、强关联系统、新型量子材料的量子器件设计、电路量子电动力学（circuit QED）、纳米量子机械系统、低温实验、纳米加工、超导量子电路、二维材料。
Quantum information science, condensed matter physics, superconducting microwave qubits, quantum sensing, strongly correlated systems, quantum device design based on novel quantum materials, circuit quantum electrodynamics (circuit QED), nano quantum mechanical systems, low-temperature experiments, nanofabrication, superconducting quantum circuits, 2D materials.

流行病学与生物统计学，公共卫生
Epidemiology and Biostatistics, Public Health

基于先进的原子模拟、实验、人工智能技术研究水泥基材料水化反应以及水化产物的多尺度模型构建；水泥基材料低碳化制备技术研发；智能/功能化/高性能水泥基材料开发；基于第一性原理/机器学习力场/增强采样的分子动力学模拟；水化产物的组分-结构-性能关系研究。
Cement-based materials hydration reaction and multiscale modeling using atomic simulations, experiments, and AI; Low-carbon preparation techniques of cement-based materials; Development of smart/functional/high-performance cement-based materials; Molecular dynamics simulations based on first principles/machine learning force fields/enhanced sampling; Structure-property-composition relationships of hydration products.

虚拟机管理程序模糊测试，固件安全，软硬件安全，嵌入式系统安全，任务关键系统安全
Hypervisor fuzzing, firmware security, hardware/software security, embedded systems security, mission-critical systems security

计算机系统，包括计算机体系结构、操作系统、编译器、运行时系统和安全性。致力于构建高效、安全、可靠的计算机系统。
Computer systems, including computer architectures, operating systems, compilers, runtimes, and security. Focus on building efficient, secure, and reliable computer systems.

真菌基因组学，宿主-病原体相互作用，真菌对环境适应的基因组进化机制，宿主免疫受体的功能多样性，高通量技术产生的组学数据分析，生物信息学，计算生物学
Fungal genomics, host-pathogen interaction, genomic evolutionary mechanisms underlying fungal adaptation, functional diversity of host immune receptors, OMICS data analysis, bioinformatics, computational biology

高性能计算、并行编程、程序分析、软件工程、性能剖析工具、性能问题检测与优化
High-performance computing, parallel programming, program analysis, software engineering, performance profiling tools, performance issue detection and optimization

大语言模型（LLMs）、人工智能安全、嵌入式系统与侧信道安全、形式化验证、生成式AI在网络安全的应用、大模型的可解释性与安全性、嵌入式设备端侧大模型应用
Large Language Models (LLMs), AI security, embedded systems and side-channel security, formal verification, Generative AI applications in cybersecurity, explainability and security of LLMs, embedded LLM applications

人工智能安全，机器学习，联邦学习安全，优化
AI Security, Machine Learning, Federated Learning Security, Optimization

细胞应激反应通路的分子机制，结构生物学（冷冻电镜/Cryo-ET），计算生物学（从头蛋白设计），生物化学（蛋白质表征），细胞生物学（荧光成像），蛋白质工程，神经退行性疾病，代谢紊乱，癌症，治疗方法开发
Molecular mechanisms of cellular stress response pathways, structural biology (Cryo-EM/Cryo-ET), computational biology (de novo protein design), biochemistry (protein characterization), cell biology (fluorescent imaging), protein engineering, neurodegeneration, metabolic disorders, cancer, therapeutic development

Multimodal AI, Generative AI, AI for health/science

Language models, reasoning, interaction, AI safety

Reinforcement Learning, Multi-agent Learning, Dynamical Systems, Robotics, Safe AI

AI安全与保障（对抗性学习、对齐、可解释性、形式验证）、强化学习（基础理论、世界模型、人机交互）、大语言模型与具代理性AI
AI Security and Safety (adversarial learning, alignment, interpretability, formal assurance), Reinforcement Learning (foundations, world models, human-AI interaction), Large Language Models and Agentic AI

人工智能安全, 机器学习, 联邦学习安全, 优化
AI Security, Machine Learning, Federated Learning Security, Optimization

形式方法，模糊测试，基于人工智能的漏洞修复，软件可靠性，软件工程的理论基础，变异执行，零知识证明工具链，与大语言模型相关的布尔猜想形式化与测试，神经定理证明的引导与评估
Formal Methods, Fuzzing, AI-based Bug Fixing, Software Reliability, Theoretical Foundations of Software Engineering, Metamorphic Executions, Zero Knowledge Proof Toolchains, Boolean Conjectures with LLMs, Neural Theorem Proving

人工智能、计算机系统和计算机视觉的交叉研究。研究重点包括多模态生成式AI、空间智能感知推理、在移动和嵌入式系统上的部署和实现、边缘计算、可穿戴计算、物联网、虚拟现实、具身智能、视频生成、真实世界模拟、AI的安全性、可解释性和公平性，将AI和深度学习应用于远程和智慧医疗（包括肺部疾病、心血管疾病、康复医学），与匹兹堡大学医学中心（UPMC）及工业界合作。
Cross-disciplinary research in artificial intelligence, computer systems, and computer vision. Focus areas include multimodal generative AI, spatial intelligent perception and reasoning, deployment and implementation on mobile and embedded systems, edge computing, wearable computing, Internet of Things (IoT), virtual reality, embodied intelligence, video generation, real-world simulation, AI safety, interpretability and fairness, application of AI and deep learning in remote and smart healthcare, including lung diseases, cardiovascular diseases, and rehabilitation medicine. Collaboration with UPMC and industry partners.

云系统、机器学习系统、系统安全，包括有机会从事带有安全特性的硬件研究并与工业界合作
Cloud systems, Machine learning systems, System security, including opportunities to work on new hardware with security features and collaboration with industry

健康数据管理、自然语言处理（NLP）、大语言模型（LLM）、分布式计算
Health data management, Natural Language Processing (NLP), Large Language Models (LLM), Distributed computing

人机交互与以用户为中心的设计（社会计算、危机信息学、以人为本的IT、交互设计、算法偏见、在线安全、辅助技术、教育技术）、网络安全与复杂系统（网络战、网络科学、密码学）、人工智能与智能系统（深度学习、医疗AI、脑机接口）、公共科技与数据分析（智慧城市、游戏、数据分析）
HCI & User-Centered Design (Social Computing, Crisis Informatics, Human-Centered IT, Interaction Design, Algorithmic Bias, Online Safety, Assistive Tech, Education Tech), Cybersecurity & Network Science (Cyber Warfare, Network Science, Cryptography), AI, Machine Learning & Intelligent Systems (Deep Learning, Healthcare AI, BCI), Civic Tech & Data Analytics (Smart Cities, Games, Data Analytics)

强化学习与控制理论的交叉融合，数据驱动的学习方法在机器人控制系统中的应用，强化学习在动态系统中策略的稳定性与鲁棒性保障，通过引入控制理论与机器人物理信息提升学习算法的可靠性与控制性能
Intersection of reinforcement learning and control theory, data-driven learning methods for robotic control systems, stability and robustness of reinforcement learning in dynamical systems, integrating control theory and robot physical information to enhance reliability and performance of learning algorithms

人工智能（AI）与科学计算交叉领域的研究，重点开发先进的计算方法和数据驱动技术，以解决复杂的物理和工程问题。
Artificial Intelligence (AI) and Scientific Computing, with a focus on developing advanced computational methods and data-driven technologies to solve complex physical and engineering problems.

人工智能，机器学习，基础模型，不确定性量化，反问题
Artificial intelligence, machine learning, foundation models, uncertainty quantification, inverse problems

极端条件下的等离子体-材料相互作用，半导体加工，等离子体物理，仪器设备，材料加工
Plasma-material interactions in extreme conditions, semiconductor processing, plasma physics, instrumentation, materials processing

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unknown

1) 大语言模型（LLMs）、多智能体系统、多模态学习；2) 可信赖人工智能，包括安全性、隐私保护、可解释性；3) 人工智能在生物医学与医疗健康领域的应用
1) Large Language Models (LLMs), Multi-Agent Systems, Multi-Modal Learning; 2) Trustworthy AI including security, privacy, interpretability; 3) AI applications in bio/healthcare

1）基于先进可视化技术和人工智能机器视觉图形处理技术的流体层/湍流流动与传热行为的实验和理论研究；2）微尺度固体表面形态及流体界面拓扑结构和相分布对质量能量传输的影响；3）先进多尺度多物理场耦合数值工具的开发及其在清洁能源系统设计与优化中的应用。研究应用包括新一代核能系统、微尺度器件、储能系统、太阳能系统和航空发动机等。
1) Experimental and theoretical study of fluid layers/turbulent flow and heat transfer behavior using advanced visualization (PIV/LIF/PTV, DIC, X-/γ-ray tomography, HSV) and AI-based computer vision techniques; 2) Influence of micro-scale surface morphology and fluid interface topology and phase distribution on mass and energy transfer; 3) Development and application of advanced multi-scale multi-physics coupled numerical tools for clean energy system design and optimization. Applications include next-generation nuclear systems, micro-scale devices, energy storage systems, solar energy systems, and aviation engines.

1. 基础模型（视觉-语言模型，扩散生成）；2. 鲁棒优化（分布外泛化）；3. 可解释机器学习（机制解释）；4. 面向健康的可信AI（多模态；推理；对齐）；5. 安全的学习系统（科学数据；自主系统）
1. Foundation Models (Vision-Language Models, Diffusion Generation); 2. Robust Optimization (Out-of-Distribution Generalization); 3. Explainable Machine Learning (Mechanistic Interpretation); 4. Trustworthy AI for Health (Multimodal; Reasoning; Alignment); 5. Safe Learning-Enabled System (Scientific Data; Autonomous System)

可穿戴技术，移动健康，人机交互
Wearable Technology, Mobile Health, Human-Robotic Interaction

人工智能和物联网，包括深度学习、AI算法与架构设计、理论AI、图像与信号处理、类脑AI、脉冲神经网络、计算机视觉、大数据系统、数据科学、大模型、边缘计算、高效计算、嵌入式系统、物联网设备与平台、可穿戴计算与传感器、智能健康和精准医疗等方向。
AI and IoT, including topics such as Deep Learning, Algorithmic and Architecture Design on AI, Theoretical AI, Image and Signal Processing, Brain-inspired AI, Spiking Neural Network, Computer Vision, Big Data System, Data Science, Large Models, Edge Computing, Efficient Computing, Embedded System, IoT Devices and Platform, Wearable Computer and Sensors, Smart Health and Precision Medicine.

网页、安全系统、软件、安全网络和隐私；网络安全与系统/软件黑客实践经验；程序分析与验证；大规模软件/系统构建与原型开发；网络系统/协议设计与实现
Web, Systems, Software, Network Security and Privacy; Cybersecurity and Hands-on System/Software Hacking experience; Program Analysis and Verification; Large-scale Software/System Building/Proto-typing; Networking Systems/Protocols Design and Implementation

云系统，机器学习系统，系统安全，包括在具有安全功能的新硬件上工作的机会以及与产业界的合作
Cloud systems, Machine Learning systems, System security, including opportunities for working on new hardware with security features and industry collaboration

计算机视觉，深度学习
Computer vision, deep learning

科学科学、挖掘科学文献以加速科学发现、生物医学/健康领域的人工智能
science of science, mining scientific literature to accelerate scientific discovery, AI for biomedicine/health

AI的安全与可解释性（例如自动驾驶、机器人和无人机中的鲁棒性和可解释性）；多模态感知（使用摄像头、激光雷达和其他传感器）；具身智能；可信AI；信息物理系统；物联网
AI safety and interpretability in autonomous systems (e.g., autonomous vehicles, robots, and drones); multi-modal perception with camera, LiDAR, and other sensors; Embodied AI agents; Trustworthy AI; Cyber Physical Systems; Internet of Things

管理信息系统（MIS），包括理论与实证研究、MIS顶级期刊（如MIS Quarterly和Information Systems Research）论文发表、UTD-24期刊研究、信息系统研究方法
Management Information Systems (MIS), including theoretical and empirical research, publication in top MIS journals such as MIS Quarterly and Information Systems Research, UTD-24 journal research, IS research, information systems research methodology

智能生产系统：基于状态的控制、实时瓶颈检测、吞吐量优化和离散制造中的资源分配；工业数据分析：变点检测、预测建模和性能诊断；能源系统与效率：工业能源系统（暖通空调、冷水机组、RTU、工艺设备）的评估和减少能耗的优化技术；信息物理制造系统：传感、数据平台和控制算法的一体化，用于实时系统优化；应用控制与优化：制造、能源和机器人系统的建模与动态控制。
Smart Production Systems: State-based control, real-time bottleneck detection, throughput optimization, and resource allocation in discrete-part manufacturing; Industrial Data Analytics: Change-point detection, predictive modeling, and performance diagnostics; Energy Systems & Efficiency: Assessments of industrial energy systems (HVAC, chillers, RTUs, process equipment) and optimization techniques for reducing energy consumption; Cyber-Physical Manufacturing Systems: Integration of sensing, data platforms, and control algorithms for real-time system optimization; Applied Control & Optimization: Modeling and dynamic control of manufacturing, energy, and robotic systems.

Formal Verification, Program Synthesis/Analysis, Neuro-Symbolic AI, SE

计算神经科学，机器学习，深度学习，多模态脑成像（MRI、EEG），认知/行为数据分析，神经生物标志物，脑疾病的精准医疗
Computational neuroscience, machine learning, deep learning, multimodal brain imaging (MRI, EEG), cognitive/behavioral data analysis, neural biomarkers, precision medicine in brain disorders

人工智能、机器学习、数据挖掘、负责任和可信赖的人工智能、大语言模型和基础模型的可信性
Artificial intelligence (AI), machine learning (ML), data mining, Responsible and Trustworthy AI, trustworthiness of large language models (LLMs) and foundation models

人工智能（AI）在制造，能源，数据中心上的应用；仿真软件（COMSOL, ANSYS, Simulink）的使用；编程（Python, MATLAB）
Applications of Artificial Intelligence (AI) in manufacturing, energy, and data centers; simulation software usage (COMSOL, ANSYS, Simulink); programming (Python, MATLAB)

深度学习、数据分析、人工智能和智能系统；医疗和生物医学研究（癌症影像、脑影像、个性化医疗）；用于生命科学和药物发现的生成式人工智能；多变量时间序列与序列数据建模；可解释和概率深度学习；AI驱动的智能农业系统；AI工程与智能代理系统（包括大语言模型和自主代理）。
Deep Learning, Data Analytics, AI and Intelligent Systems, Healthcare and Biomedical Research (cancer imaging, brain imaging, personalized healthcare), Generative AI for Life Sciences and Drug Discovery, Multivariate Time Series and Sequential Data Modeling, Interpretable & Probabilistic Deep Learning, AI-Driven Smart Agriculture Systems, AI Engineering and Intelligent Agent Systems including LLMs and autonomous agents.

通用人工智能、生成式人工智能、大语言模型、可解释人工智能、人机交互、人机协作、人工智能在机器人中的应用
AGI, Generative AI, Large Language Models (LLM), Explainable AI, Human-Computer Interaction (HCI), Human-Robot Interaction (HRI), AI in Robotics

Conversational AI, NLP, Multimodal LLMs (inference and generation), AI Discovery

Scientific Machine Learning, Health Informatics, Bioinformatics, Reinforcement Learning Applied

具身人工智能系统以增强人类身体与认知能力；机器人硬件；机器人学习；人机交互；脑机接口；认知科学；人工智能与自动化的社会影响；人工智能在艺术与设计中的应用。具体研究包括：BEHAVIOR 家务任务仿真系统；从多样化人类数据中学习；智能脑机接口系统；结合大型基础模型提升机器人泛化能力；机器人在绘画、舞蹈、烹饪、运动等方面的表现；结合世界模型与运动规划算法。
Embodied AI systems to augment human physical and cognitive abilities; robotics hardware; robot learning; human-robot interaction; brain-computer interfaces; cognitive science; societal impacts of AI and automation; applications of AI in art and design. Specific research focuses include: BEHAVIOR simulation system for household tasks; learning from diverse human data; intelligent brain-computer interfaces; integration of large foundation models to enhance robotics generalization; robot performance in art, dance, cooking, sports; motion planning with world models.

AI for science: 大语言模型+graph（用于科学领域，如医疗、药物发现等），可信任人工智能：基于知识图谱的大语言模型可解释性，知识图谱推理和逻辑查询问答，图神经网络与强化学习在大语言模型中的应用
AI for science (LLMs + graph for science, e.g., healthcare, drug discovery), Trustworthy AI (LLMs + graph for explainability and transparency), Knowledge graph reasoning and logical query answering, Applications of Graph Neural Networks and reinforcement learning in LLMs

Trustworth AI, AI computation and memory efficiency, AI theoretical guarantees

数据驱动优化，动态决策，供应链管理，智慧城市，机器学习，随机过程（如马尔可夫决策过程），近似动态规划，运筹学
Data-driven optimization, dynamic decision-making, supply chain management, smart cities, machine learning, stochastic processes (e.g., Markov decision processes), approximate dynamic programming, operations research

模电芯片设计，使用Cadence和Calibre设计具有创新性的小电路，例如LDO、DC-DC转换器。包括流片、测试和论文发表。
Analog integrated circuit design, including innovative small circuits such as LDOs and DC-DC converters using tools like Cadence and Calibre. Includes tape-out, testing, and paper publication.

行为神经科学，社会环境与大脑功能，啮齿动物模型，行为学测试，化学遗传学，光遗传学，光纤光度记录，组织学，神经环路，内分泌机制，神经精神障碍
Behavioral neuroscience, social environment and brain function, rodent models, behavioral testing, chemogenetics, optogenetics, fiber photometry, histology, neural circuits, endocrine mechanisms, neuropsychiatric disorders

基于人工智能的企业ESG分析以支持可持续转型中的绿色融资决策
AI-Enhanced Corporate ESG Analytics for Smarter Green Financing Decisions in the Sustainable Transition

垂直飞行，旋翼机，航空航天工程，大气与空间环境技术
Vertical flight, rotorcraft, aerospace engineering, atmospheric and space environment technologies

1，Networked Edge AI（面向网络化与边缘环境的智能计算研究）；2，AI for Applications（构建真实AI系统，推动 AI 在不同领域的应用与创新）
1. Networked Edge AI: Intelligent computing in networked and edge environments. 2. AI for Applications: Collaborative real-world AI systems for applications in various fields.

生成式人工智能、医学图像分析、智能门诊、生成式医疗AI、近视临床研究、生成模型的临床转化应用
Generative AI, medical image analysis, intelligent outpatient clinics, generative medical AI, myopia clinical studies, clinical translation of generative models

流体力学，包括生物混合、湍流、主动能量通量控制
Fluid Mechanics, including Biogenic Mixing, Turbulence, Active Energy Flux Control

弱监督学习、知识增强深度学习、时空统计建模、因果推断与卫生信息工程，致力于开发先进的数据驱动分析方法，用于复杂系统建模、监测与诊断，广泛应用于医疗保健、制造业与服务系统。
Weakly supervised learning, knowledge-enhanced deep learning, spatiotemporal statistical modeling, causal inference, health informatics and healthcare systems engineering, data-driven analytics for complex system modeling, monitoring and diagnosis, with applications in healthcare, manufacturing, and service systems.

Security, Privacy, Network, Internet Measurement

High-performance Computing, Data reduction and compression, AI+System

Data systems and algorithms (req: C++, CUDA, etc.), deep learning (req: PyTorch, etc.), check: https://bit.ly/danielYan

Computer Vision, 2D and 3D Generation

AI+Database, Vector database, LLM for data system, Retrieval-augmented generation (RAG), Information retrieval

Multi-party/Multi-modal Dialogue, NLP, AI for Education/Healthcare, Deep Structured Prediction

AI for Science including healthcare and geophysics

NLP/ML/AI

Data Mining, Graph Machine Learning, Computational Epidemiology, Smart Health

ML, Graph Neural Networks

Trustworthy NLP, Multilingual NLP, Multimodal LLMs, Knolwedge Extraction

NLP (LLMs, scientific/biomedical text mining), data mining, AI for science

ML System, High Performance Computing, Compiler Optimization

AI for science, AI-integrated data infrastrcuture for science

IoT, Network Security, Mobile Computing, Wireless Communication, AI

Data Mining, Machine Learning, Natural Language Processing, Social Computing

Robotics, Embodied AI, Human-Robot Interaction, Multi-Robot Systems, Autonomous Driving, Multi-Agent Learning, Trustworthy AI

金属分离及回收，溶剂萃取，金属络合，萃取剂合成，电化学分离
Metal separation and recovery, solvent extraction, metal complexation, extractant synthesis, electrochemical separation

机械控制，智能制造，机器视觉，机器学习，自动化，柔性电子制造，医学决策支持系统，仪器与控制，深度学习
Mechanical control, intelligent manufacturing, machine vision, machine learning, automation, flexible electronics manufacturing, medical decision-support systems, instrument and control, deep learning

电力系统的数学建模与数值仿真、优化方法、机器学习方法、电力系统、Python/MATLAB 编程、使用 MATPOWER 等工具。
Mathematical modeling, numerical simulations for electric power systems, optimization methods, machine learning methods, power systems, Python/MATLAB programming, use of tools like MATPOWER.

并行与分布式计算、计算机体系结构、高性能计算、面向数据密集型应用的可扩展可编程软件系统，具体应用领域包括文本与流处理、点云分析、图分析，重点优化GPU上的非规则应用
Parallel and distributed computing, computer architecture, high-performance computing, scalable and programmable software systems for data-intensive applications, application areas include text and stream processing, point cloud analytics, graph analytics, optimizing irregular applications for GPUs

可信机器学习、安全相关的机器学习
Trustworthy Machine Learning, Machine Learning for Security

具身智能，自动驾驶，机器人；AI原生网络，AI-RAN，确定性通信；无线网络；数字孪生；边缘计算
Embodied AI, Autonomous Driving and Robots; AI-Native Networks, AI-RAN, Deterministic Communication; Wireless Networks; Digital Twin; Edge Computing

机电一体化、控制、强化学习、生成式人工智能、计算机视觉、用于手术和可穿戴机器人的计算机仿真
Mechatronics, control, reinforcement learning, generative AI, computer vision, computer simulation for surgical and wearable robotics

医学图像分析中的人工智能，超声成像，低成本显微成像系统如傅里叶拼接显微镜
AI in Medical Image Analysis, Ultrasound Imaging, low-cost microscopic imaging systems such as Fourier ptychography microscopy

分析化学；电化学；拉曼光谱；表面增强拉曼光谱（SERS）；纳米材料制备与表征；金属纳米颗粒合成；生物传感器；超声；微流控；癌症研究；微生物；植物培养；动物实验；组织实验
Analytical chemistry; electrochemistry; Raman spectroscopy; surface-enhanced Raman spectroscopy (SERS); nanomaterials synthesis and characterization; metal nanoparticle synthesis; biosensors; ultrasound; microfluidics; cancer research; microbiology; plant cultivation; animal experiments; tissue experiments.

物联网、信息物理系统、机器学习、安全与隐私、面向移动、嵌入式和网络系统的可信AI技术
Internet of Things (IoT), cyber-physical systems, machine learning, security and privacy, trustworthy AI techniques for mobile, embedded, and networked systems

AI/ML驱动的下一代无线/移动网络系统和应用（例如毫米波通信、可重构智能表面、车联网、协同感知等）；下一代无线/移动网络的安全与隐私（例如开放式无线接入网，集成感知与通信）；可信的人工智能系统：用于信息物理系统（联网/自动驾驶汽车、无人机等）的安全稳健感知与决策；隐私保护的分布式数据分析、稳健和隐私保护的机器学习/联邦学习
AI/ML-driven next-generation wireless/mobile network systems and applications (e.g., millimeter-wave communication, reconfigurable intelligent surfaces, vehicle networks, cooperative perception, etc.); Security and privacy of next-generation wireless/mobile networks (e.g., ORAN, integrated sensing and communication); Trustworthy AI systems: secure and robust perception and decision-making for cyber-physical systems (connected/autonomous vehicles, drones, etc.); Privacy-preserving distributed data analysis, robust and privacy-preserving machine learning/federated learning

高性能计算（可扩展通信算法设计和并行I/O技术优化）、数据可视化（性能分析和可视化）、系统智能（AI for HPC 和 HPC for AI）
High-Performance Computing (scalable communication algorithms design and parallel I/O techniques optimization), Data Visualization (performance profiling and visualization), AI for system (AI for HPC and HPC for AI)

机器学习中的算法理论与分析，非线性优化，随机优化，高维采样，计算最优传输，GPU加速计算，大语言模型推理与Lean形式化
Algorithmic foundations of machine learning, nonlinear optimization, stochastic programming, high-dimensional sampling, computational optimal transport, GPU-accelerated computation, LLM reasoning and Lean formalization

人工智能增强的企业ESG分析、绿色融资决策、可持续转型
AI-Enhanced Corporate ESG Analytics, Green Financing Decisions, Sustainable Transition

动态系统的数据驱动建模、网约车服务（如自动驾驶出租车）、自动驾驶出行系统设计与管理、智能物流、交通安全。方法包括应用经济学、博弈论、机器学习、优化和网络建模。
Data-driven modeling for dynamic systems, ride-hailing services (e.g., robotaxi), autonomous mobility system design and management, smart logistics, traffic safety. Methodologies include applied economics, game theory, machine learning, optimization, and network modeling.

unknown

AI for structural and construction engineering (digital twins, structural health monitoring, construction monitoring/automation, robotics)

计算机视觉、机器学习、深度学习、智能基础设施系统、人工智能核心算法与系统实现、深度学习系统与工具的研发
Computer Vision, Machine Learning, Deep Learning, Intelligent Infrastructure Systems, Core AI Algorithms and System Implementation, Development of Deep Learning Systems and Tools

数据库理论、查询优化、动态查询处理、数据隐私与安全、数据分析平台、大数据处理、隐私计算、机器学习、分布式系统、流处理系统、自然语言处理、大模型+数据库、安全多方计算、可信执行环境
Database theory, query optimization, dynamic query processing, data privacy and security, data analytics platforms, big data processing, privacy-preserving computation, machine learning, distributed systems, stream processing systems, natural language processing, large language models + databases, secure multi-party computation, trusted execution environments

机器学习、人工智能、数据挖掘及其在医学与健康领域的应用
Machine learning, Artificial Intelligence, Data Mining and their applications in medicine and healthcare

Prof.
Prof.

PET-MRI 成像，利用量子纠缠的 PET 成像，实时运动校正（骨骼运动），呼吸与心脏运动校正，基于人工智能的 CT 去噪
PET-MRI imaging, PET using quantum entanglement, real time motion correction (skeletal movement), respiratory and cardiac motion correction, CT denoising using AI

计算机与人工智能安全，包括无人机安全、人工智能安全、物联网安全、通用网络安全。研究成果发表在顶级安全会议（CCS、USENIX Security、NDSS）。
Computer and AI Security, including drone security, AI security, IoT security, and general cybersecurity. Research published in top security conferences (CCS, USENIX Security, NDSS).

计算机视觉，机器学习，深度模型压缩，自动驾驶视觉
Computer vision, machine learning, deep model compression, visual perception for autonomous driving

计算生物力学，动物与人体组织和细胞建模，数字孪生开发，计算模型的实验验证，数据驱动的生物力学数据分析，骨骼肌肉神经系统建模
Computational biomechanics, modeling of animal and human tissues and cells, digital twin development, experimental validation of computational models, data-driven biomechanical data analysis, musculoskeletal and nervous system modeling

刺激响应型胶体体系；油水分离膜；纳米技术；高分子科学；膜分离技术
Stimuli-responsive colloidal systems; Oil/water separation membranes; Nanotechnology; Polymer science; Membrane separation technology

超高强钢的强韧性新机理
New mechanisms for strength and toughness in ultra-high strength steels

无线/mmWave传感与成像，下一代无线网络，基于无线的三维感知，多模态融合，通信与感知联合，面向无线系统的人工智能/机器学习，物联网上的TinyML，以及无线在机器人应用中的应用。
Wireless/mmWave sensing and imaging, NextG wireless networking, wireless-to-3D perception, multimodal fusion, joint communication and sensing, AI/ML for wireless systems, TinyML on IoTs, and wireless for robotics applications.

计算生物学、用于空间和单细胞转录组数据的机器学习与人工智能方法
Computational biology, machine learning, AI methods for spatial and single-cell transcriptomic data

My current research interests are mainly in optimization, with twin interests in theoretical foundations and computational practice. My research up to now has involved enhancing the scalability of optimization algorithms for solving large-scale linear and convex optimization -- both generically as well as on specific applications. My overarching aspiration is to extend the capability of modern optimization methods to effectively solve problems arising in operations research, data science, and machine learning/AI.

人工智能，大语言模型，新型大模型架构和训练策略，高效大模型训练、推理、微调和部署，深度学习网络的科学理解
Artificial Intelligence, Large Language Models, Large Model Architectures and Training Strategies, Efficient Training, Inference, Fine-tuning and Deployment of Large Models, Scientific Understanding of Deep Learning Networks

空间智能：神经渲染、3D 重建与生成；计算机视觉：多模态学习、视觉-语言模型（VLM）；具身智能：机器人系统、视觉-语言-动作（VLA）
Spatial Intelligence: Neural Rendering, 3D Reconstruction and Generation; Computer Vision: Multimodal Learning, Vision-Language Models (VLM); Embodied AI: Robotic Systems, Vision-Language-Action (VLA)

深度学习，人工智能理论及算法，智能控制系统，机器人，多模态大模型（如CLIP、BLIP、LLaVA），大语言模型（如LLaMA、Qwen），Transformer，VAE，BERT，无监督预训练，SFT，RLHF，控制理论，高性能计算，大数据
Deep learning, Artificial intelligence theory and algorithms, Intelligent control systems, Robotics, Multimodal large models (e.g., CLIP, BLIP, LLaVA), Large language models (e.g., LLaMA, Qwen), Transformer, VAE, BERT, Unsupervised pretraining, SFT, RLHF, Control theory, High-performance computing, Big data

药物相关蛋白组学、蛋白药定量分析、spatial proteomics、定量蛋白组学、肥胖、糖尿病、心血管疾病、阿尔兹海默症和血液肿瘤的生物标志物发现，血浆蛋白质组和单细胞蛋白质组学技术开发，与大型药企合作开展蛋白药研发
Drug-related proteomics, quantitative analysis of protein drugs, spatial proteomics, quantitative proteomics, biomarker discovery for diseases such as obesity, diabetes, cardiovascular diseases, Alzheimer's disease, and hematological malignancies; development of plasma proteomics and single-cell proteomics; collaboration with pharmaceutical companies on protein drug development

贝叶斯统计、机器学习、多组学整合，跨学科合作（数学、统计、数据科学与应用）
Bayesian statistics, machine learning, multi-omics integration, interdisciplinary collaboration in mathematics, statistics, data science, and applied domains

人工智能安全, 机器学习, 联邦学习安全, 优化
AI Security, Machine Learning, Federated Learning Security, Optimization

即时检验电子设备的研发及其在生物标志物量化检测中的应用；纳米孔芯片和设备研发以及单分子测序技术研发及其在蛋白组学中的应用；神经退行性疾病中的蛋白沉积和药物对其的影响；环境和污染物监测以及小分子检测传感器的研发。
Development of point-of-care test devices and their application in biomarker quantification; nanopore chip and device development, single-molecule sequencing technology and its application in proteomics; protein aggregation in neurodegenerative diseases and drug effects; environmental and pollutant monitoring and small molecule detection sensor development.

计算机安全，包括移动安全、系统安全、软件测试、区块链安全和人工智能安全
Computer Security, including mobile security, system security, software testing, blockchain security, and AI security

人工智能安全、软件安全、硬件安全、密码学、密码分析学、应用密码学、机器学习在安全领域的应用、可信执行环境（TEEs）、二进制分析、深度学习模型保护
Artificial Intelligence Security, Software Security, Hardware Security, Cryptography, Cryptanalysis, Applied Cryptography, Machine Learning in Security, Trusted Execution Environments (TEEs), Binary Analysis, Deep Learning Model Protection

基础模型, 医疗健康, 大规模机器学习, 高效可靠的机器学习算法, 机器学习安全性, 生物信息学
Foundation Models, Healthcare, Large-scale Machine Learning, Efficient and Robust ML Algorithms, Machine Learning Security, Bioinformatics

通过实验与建模相结合，研究流体力学、固体力学、软物质、生命系统和应用数学的前沿交叉领域。具体项目包括薄膜流动（如自相似性、不稳定性）、软材料断裂（如平面应力/应变转变、相似解）和真菌菌落发展（如感知与响应环境刺激）。
Interdisciplinary research combining experiments and modeling in fluid mechanics, solid mechanics, soft matter, living systems, and applied mathematics. Specific topics include thin film flows (e.g., self-similarity, instability), fracture of soft materials (e.g., plane stress/strain transition, similarity solutions), and fungal colony development (e.g., sensing and response to environmental stimuli).

生物电子，电路电子与计算机，电化学生物传感器，多模态/可穿戴/可植入生物传感系统，信号处理，人机交互，机器人控制与学习，强化学习，智能医疗，边缘AI集成的可穿戴和植入式传感器，临床健康监测
Bioelectronics, circuit electronics and computing, electrochemical biosensors, multimodal wearable/implantable biosensing systems, signal processing, human-computer interaction, robotics control and learning, reinforcement learning, intelligent healthcare, edge AI integration in wearable and implantable sensors, clinical health monitoring

AI for Material Science and Public Health; Algorithmic Fairness; Graph Learning; Trustworthy ML

Security, Systems, Application of ML

功能高分子合成，电池材料，先进表征技术，聚合物电解质，陶瓷类电解质，固态锂电池，新型电化学体系的开发
Synthesis of functional polymers, battery materials, advanced characterization techniques, polymer electrolytes, ceramic electrolytes, solid-state lithium batteries, development of novel electrochemical systems

使用电子显微镜技术研究行星物质（如火星陨石）的变质作用和蚀变；在类地行星材料上进行冲击波动态压缩实验；与Caltech、JPL和新墨西哥理工合作进行同位素地球化学和地质年代学分析。
Metamorphism and alterations in planetary materials using electron microscopy techniques (e.g. Martian meteorites), shock-wave dynamic compression experiments on planetary analogs, isotope geochemistry and geochronology analyses in collaboration with Caltech, JPL and New Mexico Tech.

基因组生物信息学，基因组学数据分析，转座子、外源病毒基因组插入、泛基因组等相关研究及在人类疾病研究中的应用；具备HPC和组学FASTQ数据分析经验优先，具备生信软件开发经验或转座子/外源序列插入研究经验者尤为鼓励。
Genomic bioinformatics, genomics data analysis, software development related to transposable elements in the human genome, exogenous viral genome insertions, pangenomics, and their applications in human disease research. Experience in HPC and FASTQ-based omics data analysis is preferred. Experience in bioinformatics software development or research on transposable elements/exogenous sequence insertion is highly encouraged.

生物信息、数据可视化、机器学习、基因序列处理，应用于微生物、组学数据、医学研究
Bioinformatics, data visualization, machine learning, gene sequence processing, applied in microbiology, omics data, and medical research

增强型语言模型中的工具/流程/任务的自动化，增强型语言模型中的决策/推理的可靠性，可扩展/高效/安全的增强型语言模型系统，生成式AI中的数据优化/增强/选择，生成式AI中的算法-硬件协同设计。
Tool/Chain/Task Automation in Augmented Language Models (ALM), Decision/Reasoning Reliability in ALM, Scalable/Efficient/Safe ALM Systems, Data Optimization/Augmentation/Selection for Generative AI, Algorithm-Hardware Co-design for Generative AI.

计算机网络与操作系统，重点关注高性能计算的网络软硬件基础设施构建，包括面向AI加速器的系统设计。
Computer Networks and Operating Systems, with a focus on building network hardware and software infrastructure for high-performance computing, including systems design for AI accelerators.

计算生物学，生物信息学，基因组测序数据分析，基因组重复序列（转座元件、串联重复、大型卫星重复序列），癌症，神经退行性疾病，人工智能在基因组学中的应用，免疫学
Computational biology, bioinformatics, genome sequencing data analysis, genomic repeats (transposable elements, tandem repeats, satellite repeats), cancer, neurodegenerative disorders, artificial intelligence applications in genomics, immunology

人工智能安全、机器学习、联邦学习安全、优化
AI Security, Machine Learning, Federated Learning Security, Optimization

Prof.
Prof.

优化与机器学习，包括分布式/在线优化，联邦学习（通信效率、对攻击者的鲁棒性、无问题参数的方法等），双层优化，以及在无线网络中的应用。
Optimization and machine learning, including distributed/online optimization, federated learning (communication efficiency, robustness against attackers, problem-parameter-free methods), bilevel optimization, and applications in wireless networks.

高效生成式人工智能，人工智能/机器学习算法，节能硬件设计，智能机器人计算，安全/可靠/鲁棒的人工智能，人工智能驱动的应用，量子计算
Efficient generative AI, AI/ML algorithms, energy-efficient hardware design, intelligent robotic computing, secure/reliable/robust AI, AI-powered domain applications, quantum computing

聚焦安全的互联网测量、网络流量混淆与指纹识别、隐私增强技术（PETs）、下一代网络协议中的隐私、不同地区安全与隐私服务的差异
Security-focused Internet measurement, Network traffic obfuscation and fingerprinting, Privacy-Enhancing Technologies (PETs), Privacy in next-generation network protocols, Regional differences in security and privacy offerings

医疗人工智能、多模态数据分析（EHR、影像、组学、信号、临床文本等）、因果AI（因果推断、因果发现、反事实推理）、用于提升患者健康结果和医疗系统效率的可部署可信赖AI模型
AI for Healthcare, multimodal data analysis (EHR, imaging, omics, signal, clinical text), causal AI (Causal Inference / Causal Discovery / Counterfactual Reasoning), deployable and trustworthy AI models for improving patient outcomes and healthcare systems

人工智能安全, 机器学习, 联邦学习安全, 优化
AI Security, Machine Learning, Federated Learning Security, Optimization

数据归因、数据蒸馏/压缩、可信机器学习（鲁棒性、不确定性量化、可解释性、公平性）、模型评估、AI+X应用（生物医学工程、金融、社交媒体、推荐系统，使用大模型、图神经网络等）
Data attribution, data distillation/condensation, trustworthy machine learning (robustness, uncertainty quantification, interpretability, fairness), model evaluation, AI + X applications (biomedical engineering, finance, social media, recommendation systems, using LLMs, GNNs, etc.)

高性能计算及其在科学计算、大数据、人工智能等领域的应用，包括大规模数据的有效压缩，科学数据的管理分析与可视化，人工智能算法的加速与并行，注重理论（数学/算法）与并行实现的结合以提升计算或存储效率。
High performance computing and its applications in scientific computing, big data, artificial intelligence, including efficient compression of large-scale data, scientific data management, analysis and visualization, acceleration and parallelization of AI algorithms, with a focus on combining theory (mathematics/algorithms) and parallel implementation to improve computational or storage efficiency.

人工智能，强化学习，多智能体系统
Artificial Intelligence, Reinforcement Learning, Multi-Agent Systems

计算机系统，包括边缘和云计算系统、系统虚拟化、操作系统、内存与存储系统以及系统架构。
Computer systems, including edge and cloud computing systems, systems virtualization, operating systems, memory and storage systems, and systems architecture.

AI基础设施（包括kv-cache，强化学习后训练，故障恢复，RAG推理协同设计），LLM用于系统（基于LLM的数据库自动调优、存储系统自动优化），数据库系统（RocksDB、LevelDB、HBase、向量数据库、图数据库、数据库索引设计），存储系统（备份系统、重复数据删除系统、缓存系统、新型存储介质如NVM、ZNS SSD、SMR、DNA、Glass），用于AI/ML服务的系统。
AI infrastructure (including kv-cache, RL post-training, failure recovery, RAG-inference co-design), LLM for systems (LLM-based database auto tuning, storage system auto optimization), database systems (RocksDB, LevelDB, HBase, VectorDB, graph databases, database indexing design), storage systems (backup systems, data deduplication systems, caching systems, NVM, ZNS SSD, SMR, DNA, Glass), systems for AI/ML services.

大型音频语言模型（与 Google DeepMind 合作，专注于减少幻觉现象）、多模态表示学习、扩散模型、强化学习、优化方法、机器学习理论
Large Audio Language Models (focus on hallucination reduction, in collaboration with Google DeepMind), Multimodal Representation Learning, Diffusion Models, Reinforcement Learning, Optimization, Theoretical Aspects of Learning

医学影像处理/分析，机器学习，神经科学，癌症，人工智能，数据科学，计算机视觉，大语言模型，脑电图/脑磁图
Medical image processing/analysis, machine learning, neuroscience, cancer, artificial intelligence, data science, computer vision, large language models, EEG/MEG

数据库系统，数据集成和发现，数据湖，结构化数据表示学习，基于大模型的多智能体系统，数据挖掘，自然语言处理，机器学习
Database systems, data integration and discovery, data lakes, structured data representation learning, large-model-based multi-agent systems, data mining, natural language processing, machine learning

可信任机器学习（模型鲁棒性、数据隐私、模型可解释性）、AI+电力系统、AI+生物健康、基于张量的动态系统分析与控制、面向工程/生物的人工智能
Trustworthy Machine Learning (robustness, data privacy, interpretability), AI + Power Systems, AI + Biomedical Health, Tensor-based Dynamic System Analysis and Control, AI for engineering and biology applications

自然语言处理（NLP）、人工智能（AI）、社会计算、大语言/视觉语言模型的可解释性、社会责任、以人为中心的多样性
Natural Language Processing (NLP), Artificial Intelligence (AI), Social computing, Interpretability of LLMs/VLMs, Social responsibility, Human-centered diversity

CRISPR分子诊断技术、微流控诊断芯片、生物传感技术、人工智能驱动的临床诊断、CRISPR生化分析、DNA和RNA分析、合成生物学、电化学和纳米传感技术、CRISPR生物传感器、纳米材料、生物仪器、电子工程、微流控芯片技术、3D打印、智能互联医疗
CRISPR-based molecular diagnostics, microfluidic diagnostic chips, biosensors, artificial intelligence (AI)-driven clinical diagnostics, biochemical analysis using CRISPR, DNA/RNA analysis, synthetic biology, electrochemical and nano-sensing technologies, CRISPR-based biosensors, nanomaterials, bio-instruments, electronics, microfluidic chip technology, 3D printing, smart health devices

Human-Computer Interaction (HCI), Social Computing, Responsible AI, Work and Labor, Health and Wellbeing, Design Research

Networking, Information Theory, Generative Models

计算脑科学（如利用信息理论、图模型和网络科学技术建模功能性脑网络），人工智能与数据分析（仿生AI、预测脑治疗反应的AI、统计学习等），功能性脑动态（使用统计/机器学习技术分析多模态神经影像测量的脑时空动态模式）
Computational Brain Science (e.g., utilizing information theory, graphical models and network science techniques to model functional brain networks), Artificial Intelligence and Data Analytics (bio-inspired AI, AI to predict brain therapy response, statistical learning), Functional Brain Dynamics (statistical/machine learning techniques to analyze the spatiotemporal dynamic patterns of brain measured by multimodal neuroimaging data)

下一代无线通信、传感、网络与安全；利用机器学习提升无线网络在能效、实时响应、可扩展性、灵活性与安全性方面的关键性能；6G网络与自动驾驶场景下的多模态传感器融合、波束成型、信道预测、目标识别、资源分配与网络安全；创新物联网应用（包括跨协议、跨介质、超低功耗通信、联网及其安全等）。
Next-Generation Wireless Communication, Sensing, Network, and Security; use of machine learning to improve wireless network performance in terms of energy efficiency, real-time response, scalability, flexibility, and security; 6G networks and autonomous driving scenarios including multimodal sensor fusion, beamforming, channel prediction, target recognition, resource allocation, and network security; novel IoT applications including cross-protocol, cross-medium, ultra-low power communication, networking and security.

人工智能，大语言模型
AI, large language models

人工智能安全, 机器学习, 联邦学习安全, 优化
AI Security, Machine Learning, Federated Learning Security, Optimization

电化学、分析化学、生物化学、材料化学、材料科学与工程、生物医学工程、微流控、生物传感、生物电子、柔性电子。具体研究方向包括：（1）基于织物微流控的生物传感器件的制备以及应用；（2）可降解功能纤维/织物的制备以及应用。
Electrochemistry, Analytical Chemistry, Biochemistry, Materials Chemistry, Materials Science and Engineering, Biomedical Engineering, Microfluidics, Biosensing, Bioelectronics, Flexible Electronics. Specific research topics include: (1) Fabrication and application of fabric-based microfluidic biosensors, (2) Fabrication and application of biodegradable functional fibers/fabrics.

界面现象与表面润湿；热传递与热力学；微流体、纳米流体与光流体；光流体生物传感与近表面传感；微机电系统（MEMS）与芯片实验室
Interfacial phenomena and surface wettability; heat transfer and thermodynamics; microfluidics, nanofluids, and optofluidics; optofluidic biosensing and near-surface sensing; MEMS and lab-on-a-chip systems

可解释性AI, 算法公平性, 人机交互, 社交媒体的社会影响
Explainable AI, Algorithmic Fairness, Human-Computer Interaction, Social Impact of Social Media

用前沿的生物成像分析技术（包括细胞超分辨率荧光成像、单分子探测、高通量基因组成像）研究神经生物学，RNA生物学，免疫学里的疾病（神经退行疾病和癌症等）相关的课题。实验室研究课题高度学科交叉，涉及化学，物理，生物学，工程学等多种学科。
Cutting-edge bioimaging and analysis techniques (including cellular super-resolution fluorescence imaging, single-molecule detection, high-throughput genotyping imaging) to study disease-related topics in neurobiology, RNA biology, and immunology (such as neurodegenerative diseases and cancer). Highly interdisciplinary research involving chemistry, physics, biology, and engineering.

云系统、机器学习系统和系统安全，包括有机会从事具有安全功能的新硬件工作并与工业界合作。
Cloud systems, Machine Learning (ML) systems, and System security, including opportunities to work on new hardware with security features and collaboration with industry.

Scientific Machine Learning, AI for Engineering Applications

主要研究方向为CPS系统（工业应用和自动驾驶车辆），具体包括无线网络（5G/6G）和有线网络（TSN）的系统性能优化。实验室配备有5G测试床（USRP）和TSN测试床（TTTech）。
Cyber-Physical Systems (CPS) including industrial applications and autonomous vehicles, with a focus on system performance optimization for wireless networks (5G/6G) and wired networks (TSN). The lab is equipped with a 5G testbed (USRP) and a TSN testbed (TTTech).

大型语言模型在医疗健康中的应用，医学图像处理（使用深度学习进行分类或分割），医学图像重建/插值，人工智能，机器学习，生物信息学知识发现，用于组学数据可扩展分析的高性能计算算法
Applications of Large Language Models (LLM) in healthcare, medical imaging (classification or segmentation using deep learning), medical image reconstruction/interpolation, artificial intelligence, machine learning, bioinformatics knowledge discovery, high-performance computing algorithms for scalable omics data analysis

数据挖掘，机器学习，非凸优化，图神经网络，深度生成模型，时空数据挖掘，可解释人工智能，分布式深度学习，生物启发式人工智能，应用于事件预测、医疗、蛋白质结构预测、脑结构建模、集成电路设计等。具体研究方法包括可解释AI、人机交互、结构引导的表示学习和深度生成模型、可控与因果数据生成、图神经网络、大模型图挖掘、加速大型语言模型、多模态基础模型、时空数据挖掘。应用方向包括医学成像与神经成像、癌症传播、神经形态学、分子设计与性质预测、地理信息系统、太阳图像和太阳物理等。
Data mining, machine learning, non-convex optimization, graph neural networks, deep generative models, spatiotemporal data mining, explainable AI, distributed deep learning, biologically inspired AI, applications in event prediction, healthcare, protein structure prediction, brain modeling, integrated circuit design. Methodologies include Explainable AI, Human-AI Interaction, Structure-guided Representation Learning, Controllable and Causal Data Generation, Graph Neural Networks, Large Language Models for Graph Mining, Accelerating Large Language Models, Multi-modal Foundational Models, Spatiotemporal Data Mining. Applications include Medical Imaging, Neuroimaging, Cancer Communication, Neuromorphology, Molecular Design and Property Prediction, GIS, Solar Imaging and Solar Physics.

自然语言处理和大语言模型，包括错误信息检测（事实核查、观点挖掘、社交媒体分析、AI生成内容的检测）、信息检索（多模态信息提取、推荐系统）、AI for Science（医学文本、医学图像、蛋白质、分子、同行评审中的应用）。
Natural Language Processing and Large Language Models, including misinformation detection (fact checking, opinion mining, social media analysis, AI-generated content detection), information retrieval (multi-modal information extraction, recommender systems), and AI for Science (applications in medical text, medical imaging, protein, molecule, peer review).

人工智能安全, 机器学习, 联邦学习安全, 优化
AI Security, Machine Learning, Federated Learning Security, Optimization

高性能网络、边缘计算、网络与系统安全（对抗攻击防御、可信计算）、机器学习（联邦学习、推荐系统等）
High-performance networking, edge computing, network and system security (including adversarial attack defense and trusted computing), machine learning (federated learning, recommender systems, etc.)

AI驱动的实验性计算机系统，机器学习系统，操作系统，分布式系统，大数据平台（如Spark, Storm, Flink），无服务器计算软件（如容器，kubernetes）
AI-driven experimental computer systems, ML Systems, operating systems, distributed systems, big data platforms (Spark, Storm, Flink), serverless computing software (e.g., container, kubernetes)

多尺度多物理场模拟，并行计算，基于物理方程的机器学习；应用包括血栓形成与栓塞、流固耦合、微流体设计与优化
Multiscale multiphysics simulation, parallel computing, physics-informed machine learning (PIML); applications include thrombosis and embolism, fluid-structure interaction, microfluidic design and optimization

嵌入式系统与边缘计算，算法-系统协同设计使嵌入式AI可在小型系统运行，服务于自动驾驶、农业等边缘应用；边缘端机器学习与多模态大模型；面向农业等新兴应用的嵌入式设计；类脑计算与传感器内计算
Embedded systems and edge computing, algorithm-system co-design for embedded AI in small systems, edge applications (e.g., autonomous driving, agriculture), edge machine learning and multimodal foundation models, embedded design for emerging applications such as agriculture, neuromorphic computing and in-sensor computing

1. 开发机器学习算法（如受物理约束的机器学习或神经算子学习），以提高复杂工程网络的可靠性和韧性；2. 空中交通网络的优化与控制；3. 水分配和雨水系统的数字孪生，包括数据同化、机器学习增强模拟，以及不确定性下的实时优化与控制。
1. Develop machine learning algorithms (e.g., physics-constrained ML or Neural Operator Learning) to enhance the reliability and resilience of complex engineering networks; 2. Optimization and control of air transportation networks; 3. Digital twin for water distribution and stormwater systems, including data assimilation, ML-enhanced simulation, and real-time optimization and control under uncertainty.

工程力学、岩土力学、多孔介质力学、断裂力学、固-液界面物理化学过程、分岔分析、颗粒介质力学、相场理论
Engineering Mechanics, Geomechanics, Porous Media Mechanics, Fracture Mechanics, Solid-liquid interfacial physico-chemical processes, Bifurcation analysis, Granular media mechanics, Phase-field theory

网络与系统安全，研究方向包括但不限于：（1）SDN驱动的智慧农业，结合无人机、田间传感器和边缘计算；（2）网络切片与安全/隐私保护，构建可验证的隔离与SLA保障机制；（3）SDN与可编程数据平面的安全性，开发协议无关安全工具箱，结合误用测试、模糊测试与动态不变量检测。
Network and system security, including but not limited to: (1) SDN-driven smart agriculture with UAVs and edge computing, (2) Network slicing and privacy/security through verifiable isolation and SLA enforcement, (3) Security of SDN and programmable data planes with protocol-agnostic toolkits, misuse-based testing, fuzzing, and dynamic invariant checking.

高性能计算，计算加速器（GPU），并行分布式计算，大数据的管理和分析，高能效深度学习
High Performance Computing (HPC), computing accelerators (GPU), parallel and distributed computing, big data management and analysis, energy-efficient deep learning

网络协议实现的安全性测试，包括协议模型的模型学习、形式化验证、符号执行、自动漏洞分析和用于协议栈（如DTLS、TCP、SSH）的测试工具开发。
Security Testing of Network Protocol Implementations, including model learning of protocol models, formal verification, symbolic execution, automated vulnerability analysis and testing tools for protocol stacks like DTLS, TCP, SSH.

分布式计算及网络、边缘计算、人工智能、移动互联网、智慧物联网、无线多媒体通信
Distributed computing and networking, edge computing, artificial intelligence, mobile internet, smart Internet of Things, wireless multimedia communications

数据库理论、查询优化、动态查询处理、数据隐私与安全、数据分析平台、大数据处理、隐私计算、机器学习、分布式系统、流处理系统、安全多方计算、可信执行环境、自然语言处理/大模型与数据库结合
Database theory, query optimization, dynamic query processing, data privacy and security, data analysis platform, big data processing, privacy-preserving computation, machine learning, distributed systems, stream processing, secure multi-party computation, trusted execution environments, natural language processing (NLP)/large language models with databases

面向系统的机器学习：利用机器学习技术（包括LLM代理）构建自感知、自优化的计算机系统。面向机器学习的系统：重新定义LLM的内存和存储架构，重点关注训练后优化和具备智能行为的LLM系统设计。
Machine Learning for Systems: using ML techniques (including LLM agents) to build self-aware and self-optimizing computer systems. Systems for Machine Learning: redefining memory and storage stack for LLMs, focusing on post-training optimizations and agentic LLM system design.

可信机器学习、高效机器学习、安全与隐私、边缘计算
Trustworthy Machine Learning, Efficient Machine Learning, Security & Privacy, Edge Computing

量子信息、量子密钥分发、量子通信、量子计算与机器学习、量子纠错、抗量子密码
Quantum information, quantum key distribution, quantum communication, quantum computing and machine learning, quantum error correction, post-quantum cryptography

CPS安全：身份认证/配对、智能环境、物联网安全。AI安全：对抗攻击与防御、水印与内容归属、数据隐私与安全。
CPS security: Authentication/pairing, smart environments, IoT security. AI Security: Adversarial attacks and defenses, watermarking and content attribution, data privacy and security.

1. 制备和处理金属材料用于可持续能源相关应用；2. 材料在微纳米尺度、极端条件和多物理场耦合下的力学性能测试和表征；3. 增材制造具有复杂微观结构的金属和陶瓷材料；4. 可持续冶金新工艺设计和研究；5. 多物理场耦合条件下金属微观结构演变和材料流变的模拟与预测。
1. Processing and treatment of metallic materials for sustainable energy applications; 2. Mechanical behavior characterization of materials at micro/nano scale, under extreme conditions and multi-physics coupling; 3. Additive manufacturing of metals and ceramics with complex microstructures; 4. Design and study of new sustainable metallurgy processes; 5. Simulation and prediction of microstructure evolution and material rheology under multi-physics coupling.

非厄米光学与宇称-时间(PT)对称光学，光学与电路系统中的奇异点及其应用，光学热化与非线性光学，光波导和光学微谐振腔
Non-Hermitian optics and parity-time (PT) symmetric optics, exceptional points in optical and circuit systems and their applications, optical thermalization and nonlinear optics, optical waveguides and microresonators

大语言模型（LLM）思维机制、多模态视觉模型、机器人、模型的鲁棒与可解释性
Large language models (LLM) thinking mechanisms, multimodal vision models, robotics, model robustness and interpretability

基因组生物信息学，基因组学数据分析，软件开发，转座子，外源病毒基因组插入，泛基因组研究及其在人类疾病研究中的应用，高性能计算（HPC），FASTQ 数据分析，生信软件开发
Genomic bioinformatics, genomics data analysis, software development, transposable elements, exogenous viral genome insertion, pan-genome studies, application to human diseases, HPC, FASTQ data analysis, bioinformatics software development

人工智能控制理论、具身智能控制、强化学习控制、智能控制系统、机器人、机器学习、深度学习模型（CLIP、BLIP、LLaVA、VAE、Transformer、BERT、LLaMA、Qwen）、高性能计算、大数据
Artificial intelligence control theory, embodied intelligence control, reinforcement learning control, intelligent control systems, robotics, machine learning, deep learning models (CLIP, BLIP, LLaVA, VAE, Transformer, BERT, LLaMA, Qwen), high performance computing, big data.

大数据、数据挖掘、机器学习
Big Data, Data Mining, Machine Learning

开发用于癌症与女性健康精准医疗的基因AI与大语言模型（LLM）；利用单细胞/空间组学及病理数据开发个体化药物预测的AI方法；基于空间组学数据开发患者结局预测（如治疗反应、生存率等）的AI工具与方法；构建融合电子病历（EHR）、病理报告和基因数据的多模态、多智能体、可适应模型。
Development of Gene AI and large language models (LLM) for precision health in cancer and women's health; AI methods for personalized drug prediction using single cell/spatial omics and pathology data; AI tools for patient outcome prediction using spatial omics data; Development of multimodal, multi-agent adaptable models integrating EHR, pathology notes, and genetic data.

机器学习系统（大语言模型）、分布式与并行计算机系统、云计算、边缘计算
Systems for Machine Learning (LLMs), Distributed and Parallel Computer Systems, Cloud Computing, Edge Computing

机器人具身智能，人机协作，机器人施工，多机器人协作的强化学习，面向建筑领域的人机协作
Robotic embodied intelligence, human-robot collaboration, robotic construction, reinforcement learning for multi-robot cooperation in construction, human-machine collaboration in architecture

电力系统规划、智能电网安全、机器学习、能源管理、电动车在电网中的应用、控制优化、电力系统规划与运行、建筑/家庭能源管理、智能电网的大数据分析与机器学习、大语言模型在电网中的应用、具有 Hypersim、RT-LAB、Exada 及 OPAL-RT使用经验者优先
Power system planning, smart grid security, machine learning, energy management, application of electric vehicles in the grid, control optimization, building/home energy management, big data analytics and machine learning for smart grid, use of large language models (LLMs) in power systems, experience with software such as Hypersim, RT-LAB, Exada and OPAL-RT

Prof.
Prof.

计算机网络，无线通信
Computer networks, wireless communication

人工智能赋能智慧健康、物联网人工智能、隐私计算、人机交互系统
AI for Smart Health, Artificial intelligence of things (AIoT), Privacy Computing, Human-Computer Interaction System

主动学习，大模型、语言模型的不确定性建模，科学计算中的人工智能，数据高效与不确定性感知的机器学习，基础模型/大语言模型的标签高效学习与验证方法，物理信息模型，多标签图像分类，密度泛函建模
Active Learning, Uncertainty Quantification for large/foundation/language models, AI for Science, data-efficient and uncertainty-aware machine learning, label-efficient learning, validation methods for foundation models/LLMs, physics-informed models, multi-label image classification, density functional modeling

从人类反馈中进行强化学习（RLHF）、开发无需预定义奖励函数的复杂强化学习算法、高效RLHF框架、大型语言模型（LLMs）的微调与对齐、人类反馈在机器人领域的应用、将LLMs用于自然语言反馈的生成与解释。
Reinforcement learning from human feedback (RLHF), algorithm development to solve complex RL tasks without predefined reward functions, efficient RLHF frameworks, fine-tuning and alignment of large language models (LLMs), human feedback in robotics, integrating LLMs for generating and interpreting natural language feedback.

计算机视觉，机器学习，智能医疗，图像与视频压缩，物理引导的机器学习与视觉
Computer vision, machine learning, AI for healthcare, image and video compression, physics-informed machine learning and vision

计算机体系结构，安全与隐私，人工智能/机器学习系统，安全与可信的处理器硬件与架构，可信与隐私保护的人工智能系统（包括大模型），高效的人工智能硬件与系统，芯片微架构安全（CPU/GPU 侧信道攻击与防御），处理器硬件安全漏洞的自动化检测，内存保护，可信执行环境
Computer Architecture, Security and Privacy, AI/ML Systems, Secure and Trusted Processor Hardware and Architectures, Trustworthy and Privacy-preserving AI Systems including Large Models, Efficient AI Hardware and Systems, Microarchitecture Security (CPU/GPU Side Channel Attacks and Defenses), Automated Vulnerability Analysis of Processor Hardware, Secure Memory, Trusted Execution Environments

可信数据基础架构、机密计算、数据驱动AI、安全高效使用私有和受控数据、从系统与架构角度重构计算信任边界、分解式数据中心与异构高性能计算（GPU/DPU/NPU）的机密计算系统、可扩展的安全机密计算机制、基于形式化验证的数据治理、合规与数据溯源框架、结合密码学与隐私保护的AI可信数据管线、面向AI训练与推理的安全数据流与数据库系统。
Trustworthy Data Infrastructure, Confidential Computing, Data-Centric AI, secure and efficient use of private and regulated data for AI training and inference, system and architecture level trusted computing boundary reconstruction, confidential computing systems for disaggregated data centers and heterogeneous computing (GPU/DPU/NPU), scalable and secure confidential computing mechanisms, formal verification-based data governance, compliance and provenance frameworks, cryptography and privacy-preserving trusted data pipelines for AI, secure data flow and database systems for AI.

深度学习理论：对ICLR 2025的oral论文的进一步延伸，应用于特征学习范式，研究neural ODE、大深度ResNet、大深度Transformer；图机器学习：研究GNN的oversmoothing问题，重新思考GNN与WL测试的关系，从理论上保证表达能力，建立GNN的通用近似定理体系，分析message passing与特征学习的关系，从而改进或提出新的GNN架构和训练范式。
Deep learning theory: extension of ICLR 2025 oral paper, application to feature learning regime, study of neural ODE, large-depth ResNet, large-depth Transformer; Graph machine learning: oversmoothing in GNNs, theoretical relationship between GNN and WL test, theoretical guarantees of GNN expressive power, universal approximation theorem for GNNs, theoretical analysis of message passing and feature learning, new GNN architectures and training paradigms.

人工智能、物联网、安全等交叉前沿领域
Artificial Intelligence, Internet of Things (IoT), Security, and their interdisciplinary frontiers

LLM, Agent memory system, AI for science, multi-modal, efficiency

Data Mining (Graph), Parallel Computing, GPGPU

Privacy-preserving ML, Federated Learning, Game theory and Incentives (Data Economics)

Responsible and Reliable AI, Causal ML, LLMs, AI for Computational Biology

wireless and mobile computing

AI for social impact, differentiable optimization, online learning, multi-agent systems, public health

Mobile Computing, Internet of things, Wearable Computing, Multi-modal and LLM for Mobile, Wearable and IoT, Mobile Health, Mobile and IoT Security and Privacy, Wireless Systems, Embedded Systems

Mobile Computing, Mobile Health, Wireless Sensing, Wearable Sensing, Multi-model Sensing

Wireless Network, Quantum Network, Blockchain, Distributed/Federated Learning, Learn to Optimize, Security & Privacy, Edge Computing

Natural Language Processing, Multi-modal Large Language Models

Mobile Health, Artificial Intelligence, and Speech/Audio Processing

unknown

Reinforcement Learning, Bandits, Information Retrieval, Agents

Computer Vision, Machine Learning, Multi-modal Analysis, Healthcare, NLP/LLM

Mathmatical modeling, Optimization, Control, Machine learning application in Smart Grid

Wireless communications, IoT Intelligence, Remote Sensing, Learning Theory

计算加速器物理，加速器物理中的机器学习应用，等离子体加速器概念，加速器设计，对撞机研究，与杰斐逊实验室合作。
Computational accelerator physics, machine learning applications in accelerator physics, plasma-based accelerator concepts, accelerator design, collider studies, collaboration with Jefferson Lab.

网络安全、移动计算与感知、物联网、无线感知、安全通信
Cybersecurity, Mobile Computing & Sensing, Internet of Things (IoT), Wireless Sensing, Network Security, Secure Communications

基因组生物信息学，包括基因组学数据分析及相关软件开发，尤其是人类基因组中的转座子、外源病毒基因组插入和泛基因组等研究及其在人类疾病研究中的应用。欢迎具备HPC及组学FASTQ数据分析经验者，具备生信软件开发经验或转座子/外源序列插入研究经验者尤为鼓励。
Genomic bioinformatics, including analysis of genomic data and software development, research on transposable elements in the human genome, exogenous viral genome insertions, pan-genomics and their applications in human disease research. Candidates with experience in HPC and omics (FASTQ) data analysis, bioinformatics software development, or transposable element/exogenous sequence insertion research are especially encouraged.

影响大脑发育、适应和复原力的生物和环境因素；心理健康的神经生物机制；认知与行为科学中的大数据和高级分析方法；神经科学、认知科学、数据科学
Biological and environmental factors shaping brain development, adaptation, and resilience; neurobiological mechanisms underlying mental health; big data and advanced analytic methods in cognitive and behavioral sciences; neuroscience, cognitive science, data science

深度学习，机器学习，医学图像处理，放射组学，磁共振物理和序列，医学数据采集、自动化处理、大数据分析
Deep learning, machine learning, medical image processing, radiomics, magnetic resonance physics and sequences, medical data acquisition, automation processing, big data analysis

1. 为开源设计工具开发云计算解决方案（40%） 2. 构建支撑工程设计社区的生态系统（30%） 3. 基于机器人的先进制造系统研究（30%）
1. Develop cloud computing solutions for open-source design tools (40%) 2. Build ecosystems to support the engineering design community (30%) 3. Research on advanced manufacturing systems based on robotics (30%)

新兴AI硬件（光学/光子学、后CMOS电子器件）、光子计算与互联系统、电子-光子异构AI系统设计、高效AI/ML算法与系统（LLM/VLM/扩散模型，量化、稀疏性、蒸馏、核优化、分布式部署）、AI应用的软硬件协同设计（边缘部署、稳健性、功耗、可扩展性等）、电子/光子设计自动化（EPDA、综合/布局布线、制造导向设计等）、AI用于物理建模和科学计算（AI辅助PDE求解、光学结构逆向设计）
Emerging AI Hardware (optics/photonics, post-CMOS electronics), photonic computing and interconnects, electronic-photonic heterogeneous AI system design, efficient AI/ML algorithms and systems (LLM/VLM/Diffusion, quantization, sparsity, distillation, kernel optimization, distributed deployment), hardware/software co-design for AI applications (including edge deployment, robustness, power, scalability, etc.), electronic/photonics design automation (EPDA, synthesis/placement/routing, design-for-manufacturing), AI/ML for physics and scientific computing (AI-assisted PDE solving, optical inverse design).

无线通信、无人机通信、卫星通信、分布式学习、网络安全、数字融合
Wireless communications, UAV communications, satellite communications, distributed learning, network security, digital convergence

人工智能驱动的药物发现，小分子/蛋白质的全新设计及优化，针对RNA靶点的药物设计，生物分子基础模型，分子识别，计算生物学，AI4Science
AI-driven drug discovery, de novo design and optimization of small molecules/proteins, RNA-targeted drug design, biomolecular foundation models, molecular recognition, computational biology, AI4Science

数据库理论、查询优化、动态查询处理、数据隐私与安全、分布式系统、流处理、隐私计算、机器学习、自然语言处理+数据库、可信执行环境、安全多方计算
Database theory, query optimization, dynamic query processing, data privacy and security, distributed systems, stream processing, privacy computing, machine learning, natural language processing + databases, trusted execution environment, secure multi-party computation

人工智能与免疫学，CAR-T/NK细胞突触分析，使用Python、深度学习、视觉语言大模型（LVLM）的预测建模，三维图像数据分析与可视化，免疫学数据分析界面，转化免疫治疗，免疫检查点抑制剂，双特异性T细胞连接器（BITE），癌症疫苗，细胞因子，溶瘤病毒，单克隆抗体，可信与可解释AI，隐私保护与可解释机器学习，用于生物医学成像的大语言模型与视觉语言模型，合成数据生成，多模态AI框架。
AI + Immunology, CAR-T/NK Cell Synapse Analysis, predictive modeling using Python, deep learning, large vision-language models (LVLMs), quantitative 3D image data analysis, user-friendly immunological data interfaces, translational immunotherapy, immune checkpoint blockades, BITE, cancer vaccines, cytokines, oncolytic viruses, monoclonal antibodies, trustworthy and explainable AI, privacy-preserving and interpretable machine learning, LLMs/LVLMs for biomedical imaging, synthetic data generation, multimodal AI frameworks.

冰盖水文过程、冰盖崩解动力学、海冰力学、近岸工程。研究方法包括水槽物理实验、数值模拟计算、遥感观测分析，融合多孔介质流动理论、颗粒力学与地球科学的交叉研究。
Ice Sheet Hydrology, Calving Dynamics, Sea Ice Mechanics, Coastal Engineering. Methods include hydraulic physical experiments, numerical simulation, remote sensing analysis. The research integrates porous media flow theory, granular mechanics and Earth science.

机器学习，视觉语言模型，计算机视觉在生物医学图像处理中的算法开发与应用，包括但不限于生成式人工智能的可信度研究、AI4Science、超分辨重建、图像分割、目标检测等算法在心血管成像、可穿戴传感器图像、微波图像、细胞及分子的共轭显微镜图像上的应用。
Machine Learning, Vision-Language Models, Computer Vision applied to biomedical image processing, including but not limited to trustworthy Generative AI, AI4Science, super-resolution reconstruction, image segmentation, object detection, with applications in cardiovascular imaging, wearable sensor images, microwave imaging, and cellular and molecular conjugate microscopy images.

CNAI 实验室的研究课题包括医学图像，机器学习与人工智能，计算机视觉，神经科学，数据挖掘等多学科领域的方向，例如： 1）图神经网络（graph neural network）和 transformer 应用于分析脑网络和疾病诊断 2）基于生成式AI模型/深度学习的MRI 图像重建（image reconstruction） 3）人工智能应用于医学数据分析 （AI for healthcare） 4）多模态学习的数据挖掘及其在脑神经科学的应用

Prof.
Prof.

云系统，机器学习系统，系统安全，包括有机会从事具有安全特性的硬件和与工业界合作的项目
Cloud systems, machine learning (ML) systems, system security, including opportunities to work on hardware with security features and industry collaboration

Machine Learning for Health and Biomedical Data

Quantum Computing, Quantum Sensing, Quantum HPC

High-performance computing (HPC), scientific computing, data compression, parallel computing, GPU, AI for science, HPC x AI, HPC x IoT

AI for Biomedicine, foundation models, and explainable/trustworthy AI (XAI)

1. 仿生软体机器人：仿生设计、软体结构建模与控制、先进材料与嵌入式智能。应用：微创手术工具、灾害响应系统、建筑维护。2. 可穿戴机器人：外骨骼、人机交互、生物力学、控制理论。应用：康复、行动增强、认知拓展。3. 建筑与制造机器人：灵巧操作、精准施工、系统集成。技能：机器人3D打印、模块化装配、自主施工。4. 视觉-语言-行动模型：多模态学习、感知-推理-控制一体化、VLA大模型。应用：家庭、酒店、医疗等人机共融场景。5. 虚拟/增强现实与劳动力培训：VR/AR仿真、AI驱动互动培训系统。应用：应急响应、法医调查、外科培训。
1. Soft Biomimetic Robotics: bio-inspired design, soft structure modeling and control, advanced materials, embedded intelligence. Applications: minimally invasive surgical tools, disaster response systems, construction maintenance. 2. Wearable Robotics: exoskeletons, human-machine interaction, biomechanics, control theory. Applications: rehabilitation, mobility enhancement, cognitive augmentation. 3. Construction & Manufacturing Robotics: dexterous manipulation, precision construction, system integration. Skills: robotic 3D printing, modular assembly, autonomous construction. 4. Vision-Language-Action Models: multimodal learning, perception-reasoning-control integration, large VLA models. Applications: human-robot cohabitation in homes, hotels, healthcare. 5. VR/AR + Workforce Training: VR/AR simulation, AI-driven interactive training systems. Applications: emergency response, forensic investigation, surgical training.

网络安全，生物识别技术
Cybersecurity, network security, Biometrics

AI驱动的设计、设计优化、动力学、断裂力学、冲击力学、软材料设计、控制-设计协同优化、科学领域的人工智能、拓扑优化、有限元分析、高斯过程、科学机器学习、计算力学
AI-driven design, design optimization, dynamics, fracture mechanics, impact mechanics, soft material design, control-design co-optimization, AI for science, topology optimization, finite element analysis, Gaussian process, scientific machine learning, computational mechanics

多智能体系统与控制（基于模型、数据驱动、学习方法，应用于移动机器人、自主车辆、无人机等），微电网的分布式控制（面向网络物理约束的高级分布式控制），电池储能系统的分布式管理（应对时变负载和不确定性的分布式控制与优化算法）
Multi-Agent Systems and Control (model-based, data-driven, learning-based approaches, mobile robots, autonomous vehicles, UAVs), Distributed Control of Microgrids (advanced distributed control for cyber-physical constraints), Distributed Management of Battery Energy Storage Systems (distributed control and optimization for networked battery systems under time-varying loads and uncertainties)

信息物理系统安全、人工智能系统安全、具身智能安全、低功耗移动计算、网络安全、移动计算、人工智能、人机交互
Cyber-Physical Systems (CPS) Security, Machine Learning Systems (MLSys) Security, Embodied AI Security, Low-power Mobile Computing, Network Security, Mobile Computing, Artificial Intelligence, Human-Computer Interaction

机器学习系统中的高性能计算问题，机器学习模型/大语言模型的训练和推理性能优化，计算机系统中的并行算法优化，图数据处理系统性能优化
High-performance computing in machine learning systems, training and inference performance optimization for machine learning models/large language models, parallel algorithm optimization in computer systems, performance optimization of graph data processing systems

AI for Good, Robotics for good, Edge VLM, LLM

Prof.
Prof.

认知科学与可信人工智能，人工智能的认知科学（从认知心理学和神经科学的角度理解人工智能系统的内部运作和脆弱性），服务认知健康的人工智能（用于增进对认知障碍的理解和治疗，并模拟认知症状），人工智能安全（开发用于负责任且可解释的人工智能安全的基础计算方法，包括风险量化和控制）
Cognitive Science and Trustworthy Artificial Intelligence, AI from the perspective of cognitive psychology and neuroscience, AI for cognitive health (understanding and treating cognitive disorders, simulating cognitive symptoms), AI safety (development of foundational computational methods for responsible and explainable AI safety including risk quantification and control).

用于自主系统的人工智能与机器学习；物理-人工智能：物理建模与学习方法的结合；空中机器人技术，包括无人机控制、自主性与集群；计算最优控制与随机优化；不确定性下的安全可扩展自主系统；网络系统的分布式控制与计算
Artificial Intelligence (AI) and Machine Learning (ML) for Autonomous Systems; Physical-AI: bridging physics-based modeling and learning-based methods; Aerial Robotics, including UAV control, autonomy, and swarming; Computational Optimal Control & Stochastic Optimization; Safe and Scalable Autonomy under Uncertainty; Distributed Control and Computing for Networked Systems

高性能计算（HPC）、安全（程序分析、漏洞检测、恶意软件和网络攻击）、图神经网络AI、大语言模型（算法和优化）、用于加速图算法和AI的并行、分布式和GPU系统
High-performance computing (HPC), Security (program analysis, vulnerability detection, malware and cyber attacks), Graph AI, Large Language Models (algorithms and optimization), Parallel, Distributed and GPU systems for accelerating graph algorithms and AI

AI Security, Cyber-Physical System security, Autonomous Driving Security, LLM security

数据可视化、人机协同、人工智能与人类智能融合、人-生成式AI协作、科学中的HAI（公共卫生、社会科学、数字人文等）、AI辅助决策（如科研政策制定等高影响力场景）
Data Visualization, Human-AI Collaboration, Human-Computer Interaction, Human-GenAI Collaboration, HAI for Science (AI for public health, social science, digital humanities etc.), HAI for Decision-Making (AI-assisted decision making in high-impact domains such as science policy)

科学机器学习（AI for Science）、物理引导的机器学习、医学与计算成像、基础模型、计算成像与反问题
Scientific Machine Learning (AI for Science), Physics-Guided Machine Learning, Medical and Computational Imaging, Foundation Models, Computational Imaging and Inverse Problems

复杂性状的遗传基础；极端环境下的基因组进化；新基因的起源与功能创新；分子进化；数量遗传学；基因组学；生物信息学；基因-环境互作与隐性变异在代谢疾病中的机制；整合组学方法（包括基因组、转录组与代谢组）；利用果蝇和CRISPR等技术的功能基因组学研究。
Genetic basis of complex traits; genome evolution under extreme environments; origin and functional innovation of new genes; molecular evolution; quantitative genetics; genomics; bioinformatics; gene-environment interaction; hidden variation in metabolic diseases; integrative omics approaches including genomics, transcriptomics, and metabolomics; functional genomics in Drosophila using CRISPR and other genetic tools.

内华达大学里诺分校（University of Nevada, Reno）工程学院工业工程 Dr. Bijun Wang 课题组面向 2026 年春季（优先）/ 夏季 / 秋季 招收 1–2 名全额资助 Ph.D. 学生。研究方向（保持灵活，可随学生兴趣共同拓展）包括： 1. Human Factors / Human–Computer Interaction（HCI）：复杂系统中的人因与交互设计 2. AI-enabled Decision Support & Digital Health：临床/服务系统中的 AI 决策支持与用户 acceptance/trust 3. Systems Engineering & Operations Improvement：服务与医疗系统的流程优化与安全提升 4. Applied Statistics & Data Analytics：实验设计、调查研究与数据驱动建模（含 Smart and Connected Health、可穿戴/远程监测等应用） 导师简介 Dr. Bijun Wang，于2025年秋天加入UNR 任工业工程助理教授；Ph.D. in Engineering Management（Stevens Institute of Technology），Rutgers University 双硕士。研究聚焦 Human Factors / HCI、Digital Health、AI-Driven Healthcare Systems / Smart & Connected Health，关注技术 trust & adoption、医护 workforce well-being 及数据驱动的系统优化；与跨学科临床/工程团队长期合作，成果发表于 IISE Transactions on Healthcare Systems Engineering、International Journal of Medical Informatics, Applied Ergonomics 等期刊。

HCI, Educational Technology, Healthcare, Applied AI

节能计算机系统、可持续AI、GPU数据中心资源管理、移动计算、移动和物联网设备的机器学习、实时嵌入式系统、嵌入式GPU调度、自动驾驶应用
Power-aware computer systems, energy-efficient computing, sustainable AI, GPU data center resource management, mobile computing, machine learning for mobile and IoT devices, real-time embedded systems, embedded GPU scheduling, autonomous driving applications

近场通信、光通信与无线通信融合、通信与感知融合、信号处理、宽带接入网络、大语言模型通信等，应用于数据中心、6G、物联网等
Near field communication, optical and wireless communication integration, integrated communication and sensing, signal processing, broadband access networks, communication for large language models. Applications include data centers, 6G, IoT.

Trustworthy AI, Certified Robustness, LLM, VLM, Privacy, Human Factors in Cybersecurity

LLMs (multimodal foundation models, reasoning, planning, in-contex learning, agents), generative AI for science

移动计算，AR/VR，AI4Network，神经渲染(无线电/声学)，无线系统，物联网安全
Mobile Computing, AR/VR, AI4Network, Neural Rendering (Radio/Acoustics), Wireless Systems, IoT Security

人工智能/机器学习，物理引导数据科学，统计深度学习，时空建模
AI/ML, Physics-guided Data Science, Statistical Deep Learning, Spatio-temporal Modeling

水资源规划与管理：基于代理的建模、多目标优化、水系统建模、决策分析、人水互动。智慧水系统的韧性：暴雨径流、水库、智能控制、网络与物联网安全。用水与数据科学：风险传播、粮食与水安全、网络分析。
Water resources planning and management: agent-based modeling, multi-objective optimization, water systems modeling, decision analysis, human-water interactions. Resilience of smart water systems: stormwater runoff, reservoirs, intelligent control, networks and IoT security. Water use and data science: risk communication, food and water security, network analysis.

可穿戴电子、生物电子、微纳传感器及其集成工艺与技术、生物医学领域的应用、电路设计与信号分析、材料科学与工程、电子工程、机械工程、化学工程、生物医学工程等相关学科及其交叉领域
Wearable electronics, bioelectronics, micro/nano sensors and their integration processes and technologies, biomedical applications, circuit design, signal analysis, interdisciplinary research involving materials science and engineering, electrical engineering, mechanical engineering, chemical engineering, and biomedical engineering.

数据库理论、查询优化、动态查询处理、数据隐私与安全、安全多方计算、可信执行环境、大模型与数据库、分布式系统、流处理系统、隐私计算、大数据处理与机器学习融合
Database theory, query optimization, dynamic query processing, data privacy and security, secure multi-party computation, trusted execution environments, large language models and databases, distributed systems, stream processing systems, privacy computing, integration of big data processing and machine learning

仿真，基于传感器的建模与复杂系统优化，用于过程检测、结果预测和决策支持，应用于医疗保健、制造业、公共政策以及工程教育；复杂系统的多物理场仿真；不确定模型下的预测建模；先进传感系统的优化；复杂系统的虚拟现实仿真；虚拟现实环境下的眼动追踪数据分析；自然语言处理与自动化内容分析
Simulation, sensor-based modeling, and optimization of complex systems for process monitoring, outcome prediction, and decision support, with applications in healthcare, manufacturing, public policy, and engineering education; Multiphysics simulation of complex systems; Predictive modeling under model uncertainty; Optimization of advanced sensing systems; Virtual reality (VR) simulation of complex systems; Eye-tracking data analytics in the VR environment; Natural language processing and automated content analysis

Natural Language Processing, LLMs, Multilingual NLP

Theory of Large Language Models

深度强化学习、视觉-语言-动作模型、灵巧操作与机器人手、多机器人协作与规划、人机交互与远程操控、机器人感知与多模态传感融合、仿真到现实迁移
Deep Reinforcement Learning (DRL), Vision-Language-Action (VLA) models, Dexterous Manipulation, Multi-Robot Coordination and Planning, Human-Robot Interaction & Teleoperation, Robotic Perception & Multi-Modal Sensor Integration, Simulation-to-Real Transfer (MuJoCo, Isaac Lab etc.)

材料、物理、化学、电子、磁学、机械、生物医学工程
Materials, Physics, Chemistry, Electronics, Magnetics, Mechanical Engineering, Biomedical Engineering

下一代AI加速器的生态系统搭建（graph compiler，runtime，通信中间件等）、many-GPU LLM预训练的通信优化（基于NCCL）、在GPU、Cerebras、TPU等各种架构上高性能部署LLM推理、联邦学习中的通信优化和隐私保护增强。
Next-generation AI accelerators ecosystem (graph compiler, runtime, communication middleware, etc.), communication optimization for many-GPU LLM pretraining (on NCCL), high performance deployment of LLM inference on various architectures (GPU, Cerebras, TPU, etc.), communication optimization and privacy enhancement in federated learning.

水文学、气象学、水资源、极端气候事件、人工智能与大模型、水文建模（如Sac-SMA、VIC、SWAT、WRF-Hydro、Noah-MP）、深度学习（LSTM、CNN、状态空间模型、扩散模型）、大气建模（WRF、MPAS、CESM、E3SM）、统计分析、机器学习（Scikit-learn、图像处理、PyTorch）、高性能计算、GUI开发、地理空间数据分析与可视化、后端AI模型可视化。
Hydrology, meteorology, water resources, extreme climate events, AI and large models, hydrologic modeling (e.g., Sac-SMA, VIC, SWAT, WRF-Hydro, Noah-MP), deep learning (LSTM, CNN, State Space Model, Diffusion Model), atmospheric modeling (WRF, MPAS, CESM, E3SM), statistical analysis, machine learning (Scikit-learn, image processing, PyTorch), high performance computing, GUI development, geospatial data analysis and visualization, backend AI model visualization.

机器学习、人工智能、物联网、强化学习、联邦学习、对比学习、边缘计算、基于位置的服务、遥感图像分析、信息物理系统、自然灾害损害检测、智能农业、推荐系统、无线传感器网络
Machine Learning, Artificial Intelligence, Internet of Things, Reinforcement Learning, Federated Learning, Contrastive Learning, Edge Computing, Location-based Services, Remote Sensing Imagery Analysis, Cyber-Physical Systems, Natural Disaster Damage Detection, Intelligent Agriculture, Recommender Systems, Wireless Sensor Networks

极端条件下等离子体与材料相互作用（用于半导体应用），等离子体物理，仪器设备，半导体加工
Plasma-material interplay in extreme conditions for semiconductor applications, plasma physics, instrumentation, semiconductor processing

非地面网络, 蜂窝车联网, 无线通信（5G, 6G）, 网络与系统安全
Non-terrestrial Networks (NTN), Cellular Vehicle-to-Everything (C-V2X), Wireless Communication (5G, 6G), Network & System Security

生成式人工智能模型（包括扩散模型和大语言模型）、制造系统的数字孪生工具、人机交互与协作、智能制造、人机团队协作、自主系统
Generative AI models (including diffusion models and LLMs), digital twin tools for manufacturing systems, human-machine interaction and collaboration, smart manufacturing, human-machine teaming, autonomous systems

计算机安全与隐私、人机交互、安全可靠的众包系统、可用的安全与隐私、社会工程与诈骗、鲁棒性机器学习系统。
Computer security and privacy, human-computer interaction, secure and trustworthy crowdsourcing systems, usable security and privacy, social engineering and scam, robust machine learning systems.

AGI，基础模型，生成式人工智能，大语言模型，可解释人工智能，人机交互（HCI），人机协作（HRI），机器人中的人工智能，人工智能在碳捕集、利用与封存（CCUS）中的应用，以及其他相关方向
AGI, Foundation Model, Generative AI, LLM, Explainable AI, HCI, HRI, AI in Robotics, AI in Carbon Capture, Utilization and Storage (CCUS), and other related topics

科学机器学习；面向科学问题的人工智能（特别是偏微分方程）；物理系统的生成式人工智能/科学基础模型
Scientific machine learning; AI for science (especially PDE); Generative AI/Scientific Foundation Models for physical systems

机器人学习与控制，基于复杂时序逻辑规范的学习与感知控制，非线性、高维、难以建模动力学机器人系统的安全部署，基于博弈论与预测的人机系统设计与验证，机器人学，控制，形式方法，机器学习，特别强调可解释和可信赖的人机协作智能
robot learning and control, learning and perception-based control from complex temporal logic specifications, safe deployment of robots with nonlinear, high-dimensional, and difficult-to-model dynamics, human-robot systems via game theory and prediction, robotics, control, formal methods, and machine learning with focus on explainable and trustworthy intelligence of robots

数据库理论、查询优化、动态查询处理、数据隐私与安全、大数据处理、隐私计算、分布式系统、流处理系统、机器学习与查询处理、安全多方计算、可信执行环境、自然语言处理与大模型+数据库
Database theory, query optimization, dynamic query processing, data privacy and security, big data processing, privacy-preserving computing, distributed systems, stream processing systems, machine learning and query processing, secure multi-party computation, trusted execution environments, natural language processing and large models + databases

空间单细胞基因组学、蛋白质组学技术平台开发；下一代mRNA技术平台研发；基于大数据生物DNA基因表达的可预测机器学习模型建立
Spatial single-cell genomics and proteomics technology development; Next-generation mRNA technology platform development; Predictive machine learning models based on large-scale biological DNA gene expression data

Trustworhy AI: Intepretable ML, Model Multiplicity/Uncertainty, Reasoning in LLM, AI Evaluation

Learning-augmented algorithms, uncertainty quantification, ML for optimization, energy systems

人工智能、计算机视觉、空间/具身智能、遥感、自适应计算机视觉/基础模型、三维与机器人计算机视觉、高效与安全的机器学习和边缘人工智能
AI, Computer Vision, Spatial/Embodied Intelligence, Remote Sensing, Adaptive Computer Vision/Foundation Model, Computer Vision in 3D and Robotics, Efficient and Secured Machine Learning and Edge AI

数据挖掘与机器学习、大数据、深度学习、人工智能、机器人、数据安全和决策支持，及其在商业、医疗诊断、软件工程等领域的应用。
Data mining and machine learning, big data, deep learning, artificial intelligence, robotics, data security, decision support, and applications in business, medical diagnosis, software engineering.

自适应控制，迭代学习控制，非线性系统与控制，基于视觉的控制，地面车辆/四旋翼，多智能体/互联/网络化/网络物理系统
Adaptive control, Iterative learning control, Nonlinear systems and control, Vision-based control, Ground vehicles/Quadrotors, Multiagent/interconnected/networked/cyber-physical systems

机器学习、生物医学影像分析、AI4Science、神经科学应用、阿尔兹海默症诊断与追踪
Machine Learning, Biomedical Image Analysis, AI for Science (AI4Science), Neuroscience applications, Alzheimer's disease diagnosis and tracking

光学检测仪器开发（光谱学、干涉仪），光学加工（轻量化结构设计和镜面/晶圆表面研磨仿真），3D打印轻量化镜面结构设计与测试，薄镜和晶圆表面研磨仿真，结合光谱学的计算机视觉用于增材制造过程控制，环境监测用小型干涉仪。
Optical metrology instrumentation development (spectroscopy, interferometry), optical fabrication (lightweight topology design and mirror/wafer surface lapping process simulation), 3D printed lightweight mirror structure design and testing, thin mirror and wafer surface lapping simulation, computer vision with spectroscopy for additive manufacturing process control, compact interferometer for environment monitoring.

数据库理论，查询优化，动态查询处理，数据隐私与安全，安全多方计算，可信执行环境，大数据处理，隐私计算，机器学习与查询处理的集成。
Database theory, query optimization, dynamic query processing, data privacy and security, secure multi-party computation, trusted execution environments, integration of large-scale data processing, privacy-preserving computing, machine learning, and query processing.

生物传感器设备与系统的开发，生物-材料界面的研究和应用，涵盖物理、化学、机械工程、生物工程和电子工程等领域的交叉研究。
Development of biosensor devices and systems, research and application of bio-material interfaces, with interdisciplinary work in physics, chemistry, mechanical engineering, bioengineering, and electronic engineering.

微加工与集成光子学；量子及非线性光学实验；光力器件与系统（可拓展）；量子通信、量子网络、量子精密测量、量子机器学习等交叉方向
Microfabrication and integrated photonics; Experimental quantum and nonlinear optics; Optomechanical devices and systems (scalable); Quantum communication, quantum networks, quantum precision measurement, quantum machine learning and other interdisciplinary directions

农业机器人（无人机和地面机器人）、利用人工智能、计算机视觉和机器人技术进行作物生长监测与建模，包括病害检测、杂草识别、产量预测、作物建模，多模态数据处理（点云，多/高光谱、热图像、荧光图像等）、计算机视觉、深度学习。
Agricultural robotics (UAV and UGV), crop growth monitoring and modeling using AI, computer vision and robotics, including disease detection, weed detection, yield prediction, crop modeling, multimodal data processing (point cloud, multispectral/hyperspectral, thermal, fluorescence imaging), computer vision, deep learning.

LLMs, Reinforcement Learning, Reasoning, Model Steering, Interpretability, Theoretical Foundations of AI, AI Safety

Reinforcement Learning, Multi-agent Systems, Game Theory, Generative AI, AI Safety

计算机图形学, 三维生成, 神经形状表示, 神经渲染, 虚拟现实, 人机交互, 计算机视觉, 多媒体, 医学图像, 增强现实
Computer Graphics, 3D Generation, Neural Shape Representation, Neural Rendering, Virtual Reality, Human-Computer Interaction, Computer Vision, Multimedia, Medical Imaging, Augmented Reality

AGI, 基础模型, 生成式人工智能, 大语言模型, 可解释人工智能, 人机交互, 人机协作, 机器人中的人工智能, 碳捕集利用与封存中的人工智能及其他相关方向
AGI, Foundation Model, Generative AI, LLM, Explainable AI, HCI, HRI, AI in Robotics, AI in Carbon Capture, Utilization and Storage (CCUS), and other related areas

生物医学设备、声学、细胞力学、微/纳米技术（微流体或微系统）、芯片诊断和分析、用于免疫治疗和基因编辑的精准细胞内和亚细胞药物输送、细胞物理学、微加工
Biomedical device, acoustics, cell mechanics, micro/nano technology (microfluidics or microsystem), on-chip diagnosis and analysis, precise intracellular and subcellular drug delivery for immunotherapy and gene editing, cell physics, microfabrication

AI for Biomedicine, including aging and age-related diseases, foundation models, and explainable/trustworthy AI (XAI)

自主系统、控制理论、博弈论、优化、机器学习
Autonomous systems, control theory, game theory, optimization, machine learning

深度学习, 机器学习, 医学图像处理, 放射组学, 磁共振物理和序列, 医学数据采集、自动化处理、大数据分析
Deep learning, machine learning, medical image processing, radiomics, magnetic resonance physics and sequences, medical data acquisition, automated processing, big data analysis

在物理、工程、生物学和化学领域开发新技术和应用。具有物理或工程背景的候选人将从事新技术的开发，而具有化学或生物背景的候选人将从事这些技术的应用开发。
Development of new technologies and applications in Physics, Engineering, Biology, and Chemistry. Candidates with background in physics or engineering are expected to develop new technologies, while those with background in chemistry or biology are expected to develop applications for these technologies.

通用人工智能（AGI）、基础模型、生成式人工智能、大语言模型（LLM）、可解释人工智能、人机交互（HCI）、人机协作（HRI）、机器人中的人工智能、二氧化碳捕集利用与封存（CCUS）中的人工智能，以及其他相关方向
AGI, Foundation Model, Generative AI, LLM, Explainable AI, Human-Computer Interaction (HCI), Human-Robot Interaction (HRI), AI in Robotics, AI in Carbon Capture, Utilization and Storage (CCUS), and other related areas

自动驾驶大模型：开发多模态大模型（LLMs/VLMs/VLAs），赋能自动驾驶的感知、预测、规划与控制；人机协同：利用机器学习和个性化数据，打造以人为中心的AI交互系统；自动驾驶验证：结合边缘/云计算和V2X通信，推动真实道路场景下的自动驾驶系统验证；数字孪生：构建高保真数字孪生，实现 sim2real/real2sim 转换与不确定性预测
Autonomous driving foundation models: developing multi-modal large models (LLMs/VLMs/VLAs) for enabling perception, prediction, planning, and control in autonomous driving; Human-machine collaboration: building human-centric AI interaction systems using machine learning and personalized data; Autonomous driving verification: leveraging edge/cloud computing and V2X communication to test autonomous driving systems in real-world scenarios; Digital twin: building high-fidelity digital twins for sim2real/real2sim transformation and uncertainty prediction

可信人工智能、不确定性量化、形式化验证、人工智能在健康领域的应用、大语言模型/视觉语言模型推理
Trustworthy AI, Uncertainty Quantification, Formal Verification, AI in Health, LLM/VLM reasoning

人工智能 + X, 设备端医疗人工智能, 通过算法与硬件协同设计实现高效和自动化的机器学习/人工智能系统
AI + X, On-device Medical AI, Efficient and Automated ML/AI Systems through Algorithm-Hardware Co-Design

计算动物语言学，动物语言处理，人工智能，生物学，语言学，犬类发声，自然语言处理，机器学习
Computational Animal Linguistics, Animal Language Processing, AI, Biology, Linguistics, Canine Vocalization, Natural Language Processing, Machine Learning

集成电路，嵌入式系统，边缘人工智能
IC (Integrated Circuits), Embedded Systems, Edge AI

云系统，机器学习系统，系统安全，包括有机会在具备安全功能的新硬件上工作并与工业界合作
Cloud systems, Machine Learning systems, System security, including opportunities to work with new hardware with security features and collaborate with industry

通用人工智能、基础模型、生成式人工智能、大语言模型、可解释人工智能、人机交互、人机协作、人工智能在机器人和碳捕集利用与封存（CCUS）中的应用及其他相关方向
AGI, Foundation Model, Generative AI, LLM, Explainable AI, HCI, HRI, AI in Robotics, AI in Carbon Capture, Utilization and Storage (CCUS), and other related directions

数据库理论、查询优化、动态查询处理、数据隐私与安全、大数据处理、隐私计算、机器学习、分布式系统、流处理系统、安全多方计算、可信执行环境、自然语言处理与大模型+数据库
Database theory, query optimization, dynamic query processing, data privacy and security, big data processing, privacy-preserving computing, machine learning, distributed systems, stream processing, secure multi-party computation, trusted execution environments, natural language processing and large language models + databases

Computer Vision, Multimodal Learning, Generative Models, Robustness, Open-World Learning, Active Perception

Hardware security, AI security, side-channel analysis, LLM, GNN

具身人工智能，感知-行动闭环学习（仿真与真实环境），数字孪生，世界模型，面向科学发现的交互式与自主智能体，视频理解，多模态推理，机器人启发的学习方法
Embodied AI, perception-action loop learning (simulation and real environments), digital twin, world model, interactive and autonomous agents for scientific discovery, video understanding, multimodal reasoning, robot-inspired learning methods

可信任人工智能（稳健性、隐私、可解释性、公平性、自适应），生成式人工智能，多模态人工智能（视觉、音频、文本、传感器），边缘人工智能，智能健康系统，人机交互（HCI），使用SDR、RFID、毫米波、Wi-Fi、FPGA、PCB硬件的下一代无线与感知系统，面向设备指纹识别、无线感知、低轨卫星、智能音箱、自动驾驶/无人机/机器人、AR/VR/MR的人工智能驱动的物联网安全，物联网感知与通信中的量子机器学习，基于回散射的物联网系统（RFID、LoRa、WiFi、雷达）中的定位、感知和通信技术。
Trustworthy AI (robustness, privacy, explainability, fairness, and adaptation), generative AI, multimodal AI (vision, audio, text, sensors), edge AI, smart health systems, human-computer interaction (HCI), next-generation wireless and sensing systems using SDR, RFID, mmWave, Wi-Fi, FPGA, PCB hardware, AI-driven IoT security (device fingerprinting, wireless sensing, LEO satellite, smart speakers, autonomous systems, AR/VR/MR), quantum machine learning for IoT sensing and communication, backscatter-driven IoT systems (RFID, LoRa, WiFi, Radar) for localization, sensing, and communications.

可扩展和高效的人工智能系统，可信赖与隐私保护的机器学习，计算机视觉（CV）与大语言模型（LLMs），算法与优化
Scalable and efficient AI system, Trustworthy and privacy-preserving machine learning, Computer Vision (CV) and Large Language Models (LLMs), Algorithm and optimization

大模型，机器人，人工智能，科学智能
Large Language Models (LLM), Robotics, Artificial Intelligence (AI), AI for Science (AI4Science)

机器学习聚类算法；大语言模型与检索增强生成（LLM-RAG）；算法；图挖掘；数据挖掘
Machine Learning Clustering Algorithms; Large Language Models and Retrieval-Augmented Generation (LLM-RAG); Algorithms; Graph Mining; Data Mining

机器学习, 人工智能, 人机交互, 以人为中心的人工智能, 临床数据分析
Machine learning, Artificial intelligence, Human-computer interaction, Human-centered AI, Clinical data analysis

小尺度磁性软体机器人，电磁学，固体力学，机器人学，机器学习，工程设计，计算建模（如 COMSOL、ANSYS、ABAQUS），编程（Python、MATLAB、C++）
Small-scale magnetic soft robots, electromagnetics, solid mechanics, robotics, machine learning, engineering design, computational modeling (e.g., COMSOL, ANSYS, ABAQUS), programming (Python, MATLAB, C++)

Efficient LLM/VLM algorithms, Efficient AI, AI accelerator design, Agentic AI

Virtual Reality, HCI, Games Research, AI/LLMs

信息与网络安全，隐私计算，ML/AI/LLM 安全与隐私，后量子安全与隐私，5G/6G 无线网络安全与感知，分布式安全，区块链，物联网和智能系统安全与隐私
Information and network security, privacy computing, ML/AI/LLM security and privacy, post-quantum security and privacy, 5G/6G wireless network security and sensing, distributed security, blockchain, IoT and intelligent systems security and privacy

电力系统优化运行稳定、可再生能源和储能并网、智能配电网、微电网，优化方法，机器学习应用
Power system operation and optimization, renewable energy and energy storage integration, smart distribution networks, microgrids, optimization methods, machine learning applications

通用人工智能，基础模型，生成式人工智能，大型语言模型，可解释人工智能，人机交互，人机协作，机器人中的人工智能，碳捕集、利用与封存中的人工智能
AGI, Foundation Model, Generative AI, LLM, Explainable AI, HCI, HRI, AI in Robotics, AI in Carbon Capture, Utilization and Storage (CCUS)

密码学与应用密码学，重点包括零知识证明（ZKP）、多方安全计算（MPC）、后量子密码学。研究内容包括高效实用协议设计、支持RAM程序的实现，以及其他密码学方向和交叉领域的探索。
Cryptography and applied cryptography, with focus on Zero-Knowledge Proofs (ZKP), Secure Multi-Party Computation (MPC), and post-quantum cryptography. Research includes efficient and practical protocol design, implementations that support RAM programs, and exploration of other cryptographic directions and interdisciplinary areas.

系统安全，存储系统，操作系统，计算机体系结构，恶意软件防护，软件安全，操作系统内核安全，硬件安全，逆向工程，模糊测试，漏洞分析
System security, storage systems, operating systems, computer architecture, malware defense, software security, OS kernel security, hardware security, reverse engineering, fuzzing, vulnerability analysis

计算机网络，无线通信
Computer networks, wireless communication

Computer Vision (VLMs, image and video generation, motion generation)

Multimodal Generative AI, Vision-Language Models, Embodied Intelligence, Intelligent Transportation

多智能体，联邦学习，多模态大模型，神经网络可解释性，医疗人工智能
Multi-agent systems, Federated learning, Multimodal large models, Neural network interpretability, AI for healthcare

AGI，基础模型，生成式人工智能，大语言模型，可解释人工智能，人机交互，人机协作，机器人中的人工智能，碳捕集、利用与封存（CCUS）中的人工智能，以及其他相关方向
AGI, Foundation Model, Generative AI, LLM, Explainable AI, HCI, HRI, AI in Robotics, AI in Carbon Capture, Utilization and Storage (CCUS), and other related fields

Hardware acceleration, FPGA, GPU, LLM for chip design

人工智能安全，人工智能，电力系统中的应用，智能无线通信与网络，安全，机器学习，优化
AI security, AI, applications in power systems, intelligent wireless communication and networking, security, machine learning, optimization

AI for population health, AI for medicine, multimodal, LLM, medical informatics

机器学习：基于大模型（LVMs/LLMs/LMMs）的时间序列分析、Agentic AI、生成模型、概率模型、异常检测、OOD分析、图神经网络等。AI应用（AI for Science、AI for Social Good）：神经科学、智能医疗、地球科学、信息物理系统、智能运维等。
Machine Learning: Time series analysis with large models (LVMs/LLMs/LMMs), Agentic AI, generative models, probabilistic models, anomaly detection, OOD analysis, graph neural networks. AI applications (AI for Science, AI for Social Good): neuroscience, smart healthcare, earth science, cyber-physical systems, intelligent maintenance.

单晶生长，材料物理；多铁材料，固态电池；超导材料，纳米材料；中子和X射线散射技术
Single crystal growth, materials physics; Multiferroic materials, solid-state batteries; Superconducting materials, nanomaterials; Neutron and X-ray scattering techniques

计算机视觉，参数高效学习，网络可解释性，AI+X，使用大语言模型进行数学相关证明，表征学习
Computer Vision, Parameter-efficient Learning, Network Explainability, AI+X, use of LLMs for mathematical proofs, representation learning

高性能计算（HPC）与GPU系统容错、大模型/AI系统可靠性（如大语言模型故障检测与容错机制）、量子计算与容错架构
High Performance Computing (HPC) and GPU system fault tolerance, Large Model/AI system reliability (e.g. LLM fault detection and tolerance), Quantum computing and fault-tolerant architecture

His research interests are in software engineering, programming languages, formal methods. He is currently working on neuro-symbolic trustworthy automated reasoning and software reliability.

Generative models for images; Fake image detection; Difference between real and AI generated content

LLM for Chip Deisgn, FPGA/ASIC Design, GPU Kernel Design

Trustworthy online algorithms, reliable generative AI, decision-focused learning

HCI, Educational Technology, AI for Education

后量子安全与密码学、硬件加速、全同态加密、故障检测、遥测系统数字化
Post-quantum oriented security and cryptography, hardware acceleration, fully homomorphic encryption, fault detection, digitalization for telemetry systems

HCI & Visualization: model explanation, uncertainty communication, decision-making, data and AI literacy, trust

Efficient AI, ML system, ML for EDA

Hardware acceleration for emerging applications, ASIC, FPGA

Neurosymbolic AI, Probabilistic ML, Trustworthy AI, AI for Science

unknown

Robotics, Robot Learning, Embodied AI, 3D Vision, Graphics, (Multimodal) Language Models

理论计算机、理论机器学习、算法设计、机器学习中的次线性算法（如流式、分布式、次线性时间、MPC 模型下的学习算法）、不确定性与噪声下的学习、应对强输入扰动的鲁棒机器学习算法（如动态聚类对抗自适应攻击者）、差分隐私算法
Theoretical Computer Science, Theoretical Machine Learning, Algorithm Design, Sublinear algorithms in machine learning, Learning algorithms in streaming, distributed, sublinear time and MPC models, Learning under uncertainty and noise, Robust ML algorithms against adversarial inputs, Differentially private algorithms

多核/多芯片热建模、热仿真、热管理、云计算及其能效优化、高能效AI加速器与通信计算一体化架构
Thermal modeling and simulation of multi-core/multi-chip systems, thermal management, energy-efficient cloud computing, high-efficiency AI accelerators, integrated architecture for communication and computation at the edge and cloud computing

身体活动测量，可穿戴设备，认知，心血管功能，步态表现，行为与运动干预，老龄化，慢性疾病
Physical activity measurement, Wearable devices, Cognition, Cardiovascular function, Walking performance, Behavioral and exercise intervention, Aging, Chronic conditions

冷冻电镜和冷冻电断层扫描下的生物大分子结构建模，蛋白质和核酸结构预测，大规模功能注释，涉及算法和软件开发的生物信息学问题，深度学习，AlphaFold 修改。
Cryo-EM & cryo-ET biomolecular structure modeling, structure prediction for proteins and nucleic acids, function annotation at scale, bioinformatics problems involving algorithm and software development, deep learning, AlphaFold modifications.

面向工程的机器学习方法，应用于先进制造、材料科学和其他复杂物理系统。还包括强化学习、机器学习和编程。
Engineering-driven machine learning methods with applications to advanced manufacturing, material science, and other complex physical systems. Also includes reinforcement learning, machine learning, and programming.

信号处理、机器学习、数据科学、凸和非凸优化、博弈论、张量分析，利用稀疏性、低秩性和平滑性等低维结构开发基于优化的方法。
Signal Processing, Machine Learning, Data Science, convex and non-convex optimization, game theory, tensor analysis, optimization-based techniques using low-dimensional structures such as sparsity, low-rankness, and smoothness.

深度学习, 机器学习, 医学图像处理, 放射组学, 磁共振物理和序列, 医学数据采集、自动化处理、大数据分析
Deep learning, machine learning, medical image processing, radiomics, magnetic resonance physics and sequences, medical data acquisition, automation, big data analysis

副黏病毒的进入和组装、病毒与宿主相互作用、单分子成像、超分辨率成像、晶格结构化照明显微镜、病毒动态的实时成像
Paramyxovirus entry and assembly, virus-host interactions, single-molecule imaging, super-resolution imaging, lattice SIM microscopy, real-time imaging of virus dynamics

深度学习, 机器学习, 医学图像处理, 放射组学, 磁共振物理和序列, 医学数据采集、自动化处理、大数据分析。
Deep learning, machine learning, medical image processing, radiomics, magnetic resonance physics and sequences, medical data acquisition, automation processing, big data analysis.

LLM, RL, Efficiency, Agents

Robotics, 3D computer vision, AI

成人与小孩的语音与音频处理，机器学习与深度学习方法（包括自监督学习、序列建模等），AI在儿童早期发展与临床应用中的跨学科探索。
Speech and audio processing for adults and children, machine learning and deep learning methods (including self-supervised learning, sequence modeling, etc.), interdisciplinary applications of AI in early childhood development and clinical settings.

自动驾驶，系统安全，健康医疗，人工智能
Autonomous Driving, Cyber-Physical System Security, Smart Healthcare, Machine Learning, and Artificial Intelligence

卫星网络、边缘计算、网络安全、区块链、网络、应用密码学、博弈论、优化、近似算法、资源分配、鲁棒设计
Satellite Networks, Edge Computing, Cybersecurity, Blockchain, Networking, Applied Cryptography, Game Theory, Optimization, Approximation Algorithms, Resource Allocation, Robust Design

智能电网技术、量子计算、能源系统脱碳、电力系统运行与规划、数据驱动优化、人工智能与机器学习、量子优化
Smart grid technology, quantum computing, energy system decarbonization, power system operations and planning, data-driven optimization, AI and machine learning, quantum optimization

现代计算生态系统中的安全与隐私，软件供应链安全与隐私，移动和物联网系统安全，网络犯罪，逆向工程，静态与动态程序分析，形式化验证，程序切片，污点/流分析，模糊测试，形式方法。
Security and privacy in modern computing ecosystems, software supply chain security and privacy, mobile and IoT systems security, cybercrime, reverse engineering, static and dynamic program analysis, formal verification, program slicing, taint/flow analysis, fuzzing, formal methods.

人工智能驱动的可穿戴电子产品和个性化医疗植入物设计；用于癌症研究的AI辅助柔性医疗贴片；用于心血管疾病的个性化植入物；用于康复和物理治疗的AI辅助智能纺织品和触觉套装；非传统电子系统用于精准医疗
AI-driven design of wearable electronics and personalized medical implants; AI-assisted flexible medical patches for cancer research; personalized implants for cardiovascular diseases; AI-assisted smart textiles and haptic suits for rehabilitation and physical therapy; non-traditional electronic systems for precision medicine

智能化软件（AIware），包括但不限于：面向软件工程的人工智能、可信人工智能、以人为中心的人工智能、面向人工智能的软件工程（也称为AI工程或生产中的机器学习）、面向工程/科学/教育的人工智能、大语言模型与代码的代理流程
AI-powered Software (AIware), including but not limited to: AI for Software Engineering, Trustworthy AI, Human-Centered AI, Software Engineering for AI (AI Engineering or Machine Learning in Production), AI for Engineering/Science/Education, Large Language Models and Agentic Flow for Code

1）用于生化数据链路预测的知识图谱嵌入（KGE）或图神经网络（GNN）；2）三维图像重建与分割；3）机器学习中的黎曼几何与优化方法
1) Knowledge Graph Embedding (KGE) or Graph Neural Networks (GNN) for link prediction on biochemical data, 2) 3D image reconstruction and segmentation, 3) Riemannian geometry and optimization for machine learning

机器学习、生物医学影像分析、科学智能（AI4Science），特别是应用于阿尔兹海默症等神经疾病的诊断与追踪
Machine learning, biomedical image analysis, AI for Science, especially applications in diagnostics and tracking of neurological diseases like Alzheimer's

基于计算的药物再利用，基于深度学习的预测模型，生物医学信息学，机器学习，深度学习，语义网/知识图谱，自然语言处理（NLP），生物统计学，基于AI的药物设计，基于AI与电子病历的治疗效果预测模型
Computational Drug Repurposing, Deep Learning-based Predictive Models, Biomedical Informatics, Machine Learning, Deep Learning, Semantic Web/Knowledge Graphs, Natural Language Processing (NLP), Biostatistics, AI for Drug Design, AI-based Treatment Outcome Prediction using Electronic Health Records (EHRs)

Neurosymbolic AI, Probabilistic Methods, Explainable AI and Combinatorial Optimization

Vision Language Models

Mulitmodal AI, Embodied AI, VLMs/LLMs (reasoning, segmentation, etc.), 3D (generation, reconstruction, reasoning). Not recruiting in AI4H

Database Systems for AI/ML (including LLM inferences) and Privacy

Autonomous Driving, Robotics, AI/ML for Control

Computer architecture, System, LLM

AI for Software Engineering, LLM Reasoning about Source Code, AI For Software Security

NeuroAI, Interpretable AI, Neural Imaging, Computer Vision, Dynamical Systems

Humanoids, Legged robots, Foundation Model, AI/ML based manipulation

机器学习，生物医学影像分析，AI4Science，神经疾病（如阿尔兹海默症）诊断追踪，神经科学、放射学、统计、计算机的跨学科研究
Machine Learning, Biomedical Image Analysis, AI for Science, Diagnosis and tracking of neurodegenerative diseases such as Alzheimer's, Interdisciplinary research with neuroscience, radiology, statistics, and computer science

1）用于生化数据链路预测的知识图谱嵌入（KGE）或图神经网络（GNN）；2）三维图像重建与分割；3）机器学习中的黎曼几何与优化
1) Knowledge Graph Embedding (KGE) or Graph Neural Networks (GNN) for link prediction on biochemical data; 2) 3D image reconstruction and segmentation; 3) Riemannian geometry and optimization for machine learning

网络安全，计算机科学，交通系统，标书撰写，编程，数据分析，学术写作，演讲技能
Cybersecurity, Computer Science, Transportation Systems, Proposal Writing, Programming, Data Analysis, Academic Writing, Presentation Skills

面向软件安全的人工智能，二进制分析，使用图神经网络和自然语言处理的恶意软件分析，漏洞挖掘，软件供应链安全，大语言模型在安全领域的应用，逆向工程，代码分析
AI for Software Security, Binary Analysis, Malware Analysis using GNN and NLP, Vulnerability Discovery, Software Supply Chain Security, LLM for Security, Reverse Engineering, Code Analysis

复杂系统的统计建模、监测、预测与控制；用于先进制造系统、驾驶员模拟与监测系统、医疗时空及成像系统、水利与水文建模系统的数据分析工具；算法开发、硬件设计、理论分析、仿真与模拟。
Statistical modeling, monitoring, prognostics and control of complex systems; data analytics tools for advanced manufacturing systems, driver simulation and monitoring systems, healthcare spatio-temporal and imaging systems, water and hydrology modeling systems; algorithm development, hardware design, theoretic analysis, simulation and emulation.

Data Mining, Graph Machine Learning

AI for health, Biomedical AI

AI4PDE, Agents for Science, Scientific Machine Learning, Computational Physics, Data-Driven Dynamical Systems

Statistical learning, data privacy, computational statistics, Monte Carlo methods

Systems for Machine Learning (e.g., OS/DB/Arch/Security)

Time series, AI for science, LLMs

semiconductor devices, ultrawide bandgap semiconductors, NIR/MIR optics

Computer Systems, systems for machine learning

Trustworthy AI, learning theory, information theory

Reinforcement Learning, Game Theory, Generative AI, Agents, Robotics

AI for Material Science, Reasoning, Multimodality | AI Ethics, Unlearning

可信赖人工智能，联邦与多智能体学习，深度学习理论（泛化界限，对抗样本，大语言模型），因果推理（因果发现，联邦因果发现，因果表示学习）
Trustworthy AI, Federated & Multi-Agent Learning, Theory of Deep Learning (generalization bounds, adversarial examples, large language models), Causality (causal discovery, federated causal discovery, causal representation learning)

仿生软材料，数据驱动高分子材料，计算材料，分子动力学，数据挖掘，机器学习，实验生物材料，高分子合成，细胞与蛋白研究，结构-性能-功能关系
Bio-inspired soft materials, data-driven polymers, computational materials, molecular dynamics, data mining, machine learning, experimental biomaterials, polymer synthesis, cell and protein studies, structure–property–function relationships

深度学习, 机器学习, 医学图像处理, 放射组学, 磁共振物理和序列, 医学数据采集、自动化处理、大数据分析
Deep learning, machine learning, medical image processing, radiomics, MRI physics and sequences, medical data acquisition, automated processing, big data analysis

软件安全、AI安全、软件与AI交叉方向
Software security, AI security, intersection of software and AI security

面向无线通信的机器学习，信号处理，图像处理，深度学习，优化
Machine learning for wireless communications, signal processing, image processing, deep learning, optimization

6G 非地面网络（NTN）、低轨卫星通信、低空无线网络、面向 B5G/6G 的先进通信技术、AI/ML 驱动的 NTN 优化、空天地一体化网络的协议与系统设计
6G Non-Terrestrial Networks (NTN), Low Earth Orbit Satellite Communication, Low-altitude Wireless Networks, Advanced Communication Technologies for B5G/6G, AI/ML-driven NTN Optimization, Protocol and System Design for Integrated Air-Space-Ground Networks

计算机安全，计算机体系结构，硬件安全，可信系统，机器学习安全，物理信息系统安全
Computer security, computer architecture, hardware security, trusted systems, machine learning security, cyber-physical system security

半导体应用中的极端条件下等离子体与材料相互作用；等离子体物理、仪器、工艺
Plasma-material interplay in extreme conditions for semiconductor applications; plasma physics, instrumentation, processes

融合机理模型与机器学习用于农业作物监测与预测；数字与智能农业；近端与遥感；作物传感器；机器人与自动化系统；物联网；人工智能；辐射传输模型；作物生长模型；无人机、卫星、光学传感、2D/3D图像处理
Integrating process-based models and machine learning for agricultural crop monitoring and prediction; digital and smart agriculture; proximal and remote sensing; crop sensors; robotics and automation systems; Internet-of-Things; Artificial Intelligence; radiative transfer models; crop growth models; UAV, satellite, optical sensing, 2D/3D image processing

Bandits, EconML, LLM Reasoning, Algorithmic Fairness

Machine Learning for Systems, High Performance Computing, Computer Architecture

HCI, Human-AI Interaction, XR

ML/AI for healthcare

Reinforcement Learning, Mobile Health, Machine Learning Theory

AI for media, Generative modeling, Multimedia security

Medical Image Analysis, Large Foundation Model, AI/ML

医学图像分析、计算机视觉、深度学习、大型基础模型
Medical Image Analysis, Computer Vision, Deep Learning, and Large Foundation Models

生物信息学与计算生物学，应用统计与机器学习，大语言模型和基因组基础模型，宏基因组与转录组学，AI4Health
Bioinformatics and computational biology, applied statistics and machine learning, large language models and genomic foundation models, metagenomics and transcriptomics, AI for health

高效与稳健的图神经网络（GNNs），时序/动态图学习系统，机器学习系统与加速器，对抗稳健性与AI安全性，面向图AI应用（如GraphRAG，LLM-图混合模型）的可扩展基础设施
Efficient & Robust Graph Neural Networks (GNNs), Temporal / Dynamic Graph Learning Systems, Machine Learning Systems and Accelerators, Adversarial Robustness & AI Security, Scalable Infrastructure for Graph-based AI Applications (e.g., GraphRAG, LLM-Graph hybrids)

1) 用于生化数据链路预测的知识图谱嵌入（KGE）或图神经网络（GNN）；2) 三维图像重建与分割；3) 用于机器学习的黎曼几何与优化
1) Knowledge Graph Embedding (KGE) or Graph Neural Networks (GNN) for link prediction on biochemical data; 2) 3D image reconstruction and segmentation; 3) Riemannian geometry and optimization for machine learning

AI安全，聊天机器人系统安全，聊天机器人系统的系统级防御设计和最坏情况行为分析，故障模式分析，计算语用学，安全聊天机器人系统，大型语言模型的稳健性与安全性。
AI for Security, chatbot system security, system-level defense design for chatbot systems, worst-case behavior analysis for chatbot systems, failure modes analysis, computational pragmatics, secure chatbot systems, large language model robustness and security.

智能电网，用于能源应用的生成式人工智能和大语言模型，数据合成
Smart Grid, Generative AI and Large Language Models (LLM) for energy application, Data Synthesis

生成式人工智能在健康领域的应用，机器学习，人工智能
Generative AI with health applications, Machine Learning, Artificial Intelligence

合成生物学，蛋白质工程，RNA工程，生物领域的机器学习，基因与细胞治疗，体内记录，谱系追踪，自身免疫性疾病，癌症，衰老，分子生物学，细胞编程
Synthetic biology, protein engineering, RNA engineering, machine learning for biology, gene and cell therapy, in vivo recording, lineage tracing, autoimmune diseases, cancer, aging, molecular biology, cellular programming

人工智能、强化学习、大语言模型、LLM推理、LLM微调
Artificial Intelligence, Reinforcement Learning, Large Language Models (LLMs), LLM Reasoning, LLM Fine-tuning