جستجوی استاد راهنمای دانشگاهی

Wenzhong Liمشاهده پروفایل

استاد

• AI-Empowered Distributed Systems
• MultiModal Large Models
• Embodied Intelligence
• +۹ مورد دیگر

Wenzhong Li is a Professor at the School of Computer Science, Nanjing University, where he leads research at the State Key Laboratory for Novel Software and Technology. His academic career spans over 15 years with significant contributions to AI-empowered distributed systems, big data mining, and networking applications. He teaches Computer Networks and guides graduate students in Distributed Computing Research. Professor Li's research focuses on cutting-edge areas including AI-Empowered Distributed Systems and Applications (MultiModal Large Models, Embodied Intelligence, Edge Computing), Big Data Mining (Time Series Analysis, Graph Computing, Social Networks Analysis), and AI-Based Distributed Resource Scheduling. His work bridges theoretical foundations with practical implementations in real-world systems. His recent publications demonstrate a strong trend toward integrating deep learning with graph theory and time series analysis, with applications in human activity recognition, network optimization, and multimodal systems. The research spans multiple disciplines including artificial intelligence, computer vision, networking, and data mining, with a particular emphasis on practical implementations for real-world problems. Best Paper Runner Up at KSEM 2023 for 'Learning-based Dichotomy Graph Sketch for Summarizing Graph Streams with High Accuracy' Best Paper Award at APNet 2018 for 'Toward Effective and Fair RDMA Resource Sharing' Professor Li has advised numerous PhD and Master's students who have gone on to prominent positions at institutions like Nanjing University, Huawei, Alibaba, Microsoft, and various international universities. His research is supported by substantial grants from the National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province, National Power Grid, and other major funding bodies, totaling multiple multi-year projects with significant budgets. He leads the AINet Group and is affiliated with the Sino-German Institute of Social Computing and MobileCloud research initiatives. His DISLAB provides the organizational framework for his research team, which includes dozens of graduate students and collaborators working on cutting-edge problems in AI, networking, and distributed systems.

• High-Performance Composite Structures
• Sustainable Marine Engineering
• Structural Load and Corrosive Environment Coupling
• +۳ مورد دیگر

Dr. Hou Chao is an Associate Professor and PhD Supervisor at the Department of Ocean Science and Engineering , Southern University of Science and Technology (SUSTech) since 2019. Previously, he held academic positions at the University of Sydney (2015-2019) and served as a lecturer there (2018-2019). He received his BEng (2009) and PhD (2014) in Structural Engineering from Tsinghua University , where he was recognized as an outstanding graduate and awarded the National Scholarship of China (2013). Research Interests focus on High-performance composite structures Sustainable marine engineering systems Load and marine environment coupling effects Modular construction technology Corrosion resistance in offshore structures Publication Trends reveal expertise in concrete-filled steel tubular (CFST) structures under extreme conditions. His work spans mechanical behavior analysis, fatigue assessment, and innovative connection design for modular buildings, with methodological focus on experimental testing, finite element modeling, and machine learning applications. Key sub-fields include localized corrosion effects, post-fire performance, and reliability-based design frameworks. Scientific Recognition : 2022 Ministry of Education Natural Science First Prize (3/5) China Patent Excellence Awards (2/2, 5/10) Inclusion in Stanford-Elsevier Top 2% Scientists (2023, 2024) Dean’s Outstanding Teaching Award, University of Sydney (2018) Editorial roles: Structures , Advances in Structural Engineering He has secured over 10 international research grants, including National Natural Science Foundation of China projects and Shenzhen Science & Technology Innovation Commission awards. His work is codified in 7 Chinese national standards, applied in critical infrastructure like the Wenchuan Kequ Bridge.

Shangfei Wangمشاهده پروفایل

استاد

• Pattern Recognition
• Affective Computing
• Probabilistic Graphical Models
• +۳ مورد دیگر

Shangfei Wang is a full Professor at the School of Computer Science and Technology, University of Science and Technology of China (USTC). His research focuses on pattern recognition, affective computing, and probabilistic graphical models, with significant contributions to facial expression analysis, emotion recognition, and multimodal human-robot interaction. He leads the Key Laboratory of Computing and Communication Software of Anhui Province and has received multiple international competition awards including placements in the OMG Empathy Prediction Challenge and Detecting Depression with AI Sub-Challenge. PhD in Computer Science, USTC (2002) MSc in Electronic Science and Technology, USTC (1999) BSc in Electronic Engineering, Anhui University (1996) His work combines domain knowledge with advanced machine learning techniques, including adversarial learning, dual learning, and multimodal deep regression Bayesian networks. Research themes include: Emotion-aware medical consultation systems Thermal image-based facial recognition Privileged information learning for emotion detection Spontaneous vs. posed expression differentiation EEG and physiological signal integration AI applications in mental health support Key projects include multiple National Nature Science Foundation of China grants and international collaborations with French institutions. He serves as Associate Editor for IEEE Trans. on Affective Computing and ACM Trans. on Multimedia Computing, and organized several international conference tracks.

• Control Theory
• Game Theory
• Signal Processing
• +۴ مورد دیگر

Kemi Ding is an Associate Professor at the School of Automation and Intelligent Manufacturing, Southern University of Science and Technology (SUSTech), leading the LEMONS lab (Learning and Mathematical Optimization in Networked Systems). Her career spans postdoctoral research at Arizona State University and Nanyang Technological University, followed by roles at SUSTech since 2021. Education Ph.D., Electronic and Computer Engineering, HKUST (2018) B.E., Electronic and Information Engineering, HUST (2014) Visiting Student, Harvard SEAS (2016-2017) Her research bridges control theory, game theory, signal processing, and machine learning , focusing on cyber-physical system security/privacy , networked estimation , and graph-based learning methods . She has published in top journals like Automatica and IEEE Transactions series, emphasizing secure and robust networked systems. Key publication trends include: Game-theoretic approaches to sensor security and deception strategies Optimization of estimation under bandwidth and attack constraints Graph signal processing for networked system modeling Privacy conflict resolution in social networks Resilient control theory under adversarial conditions

Fuchun SUNمشاهده پروفایل

استاد

• Intelligent Control
• Robotics
• Networked Control Systems
• +۷ مورد دیگر

Fuchun SUN is a Full-time Professor at Tsinghua University's Department of Computer Science and Technology, where he has been affiliated since 1998. He holds a Bachelor's (1986) and Master's (1989) in Automation from the Institute of Naval Aeronautical Engineering, and a Ph.D. in Computer Science & Technology from Tsinghua University (1997). Prof. SUN serves as Deputy Director of the State Key Laboratory of Intelligent Technology and Systems and holds editorial positions in IEEE Transactions on Neural Networks and Soft Computing. Research Focus: His work spans Intelligent Control, Robotics, Networked Control Systems, and Artificial Cognitive Systems. He pioneers neuro-fuzzy modeling, adaptive control of nonlinear systems, and Markov jump system filtering, with applications in spacecraft, mobile robots, and flexible manipulators. Research projects include National 863 High-Tech Programs and National Basic Research (973) Programs on hyperspace vehicle control and multi-satellite networking. Publications Trend: His 15 most recent articles (2002–2010) demonstrate consistent focus on neuro-fuzzy adaptive control, robotics, Markov jump systems, and H-infinity filtering. Over 80% involve experimental validation of theoretical frameworks for robotic manipulators and nonlinear systems. Awards: National Natural Science Funds for Distinguished Young Scholars (2006) New Century Talents Award, Ministry of Education (2004) National Science and Technology Progress Award, Second Class (2002) 18th Choon-Gang Academic Award, Korea (2003) Science and Technology Progress Award, Beijing (Second Class, 2004) National Distinguished Doctoral Dissertation (2000) Academic Leadership: Supervised 15 Ph.D. and 20 Master's students. Secured 10+ national grants including NSFC Distinguished Young Scholars funding. Developed experimental platforms: two flexible-link robot test-beds and a space teleoperation system for on-orbit servicing.

Jun Zhuمشاهده پروفایل

استاد

• Probabilistic Machine Learning
• Adversarial Robustness
• Bayesian Methods
• +۶ مورد دیگر

Jun Zhu is a Professor in the Computer Science Department at Tsinghua University and serves as Co-Director of the Tsinghua Artificial Intelligence Lab (TSAIL) and Director of the Tsinghua-Bosch Joint Center for Machine Learning. His research focuses on probabilistic machine learning, adversarial robustness, Bayesian methods, deep learning, and reinforcement learning. His recent work includes open-sourcing the Vidu video generator (2024), DPM-Solver for diffusion models (2024), and Tianshou deep RL library, with publications in top venues like ICLR and IEEE CoG. He has received prestigious awards including IEEE Fellow, AAAI Fellow, and MIT TR35 China recognition. Notable Awards: IEEE Fellow AAAI Fellow MIT TR35 China Pioneer (2017) NSFC Excellent Young Scholar (2013) Leadership: Co-Director, TSAIL Group Director, Tsinghua-Bosch Joint Center for ML Associate Editor-in-Chief, IEEE TPAMI

• Neuroscience
• Machine Learning
• Control Theory
• +۴ مورد دیگر

Dr. LIU Quanying is an Associate Professor in the Department of Biomedical Engineering at the Southern University of Science and Technology (SUSTech), where she has been a faculty member since September 2019. She serves as the Principal Investigator of the Neural Computing and Control Laboratory (NCC lab) and is a doctoral supervisor. Prior to joining SUSTech, she earned her PhD in Biomedical Engineering from ETH Zurich and conducted postdoctoral research at Caltech. Education: PhD in Biomedical Engineering, ETH Zurich (2013-2017) Master in Computer Science, Lanzhou University (2010-2013) Bachelor in Electrical Engineering, Lanzhou University (2006-2010) Research Interests: Dr. Liu’s research integrates neuroscience, machine learning, and control theory. Her work focuses on multi-modal neural signal processing (EEG, sEEG, fMRI, DTI), explainable AI for neuroscience, and optimization techniques for neuromodulation (tES, TMS). She has developed high-density EEG source localization algorithms and data-driven brain network modeling frameworks, aiming to enhance precision in neural stimulation and control. Scientific Awards: The New Brain 30 (2023) AAIC Travel Award (2019) Estes Stars Award (2018) 深圳市孔雀人才计划C类 Laboratory and Team: As the PI of the NCC lab, Dr. Liu leads a team focused on machine learning algorithms, neurocomputational modeling, and neurofeedback control. The lab actively recruits graduate students, postdocs, and visiting researchers, emphasizing interdisciplinary collaboration in neuroscience and AI.

Derong Liuمشاهده پروفایل

استاد

• Adaptive Dynamic Programming
• Reinforcement Learning
• Intelligent Control
• +۵ مورد دیگر

Derong Liu is a Chair Professor at Southern University of Science and Technology (SUSTech) in Shenzhen, China, holding dual appointments as Full Professor of Electrical and Computer Engineering and Computer Science at the University of Illinois at Chicago. He is a distinguished scholar with multiple prestigious recognitions including Member of Academia Europaea, Fellow of IEEE, Fellow of International Neural Network Society, and Fellow of International Association for Pattern Recognition. His academic journey spans multiple institutions across China and the United States, with significant contributions to control theory and artificial intelligence. Ph.D. in Electrical Engineering from University of Notre Dame (1994) M.Sc. in Automatic Control Theory from Chinese Academy of Sciences (1987) B.Sc. in Mechanical Engineering from East China Institute of Technology (1982) Liu's research focuses on Adaptive Dynamic Programming and Reinforcement Learning, Intelligent Control and Information Processing, Modeling and Control of Complex Industrial Processes, Neural Networks and Computational Intelligence, and Smart Grid technologies. His work bridges theoretical foundations with practical applications in industrial control systems, particularly in automotive engine control and energy management. He has pioneered significant methodologies in neural network design and adaptive control systems that have become foundational in the field. His publication record demonstrates a consistent trajectory of high-impact research, with recent articles focusing on event-triggered control systems, neural architecture search, fault tolerant control, and multi-agent game theory applications. The research spans both theoretical advances in control algorithms and practical implementations in complex industrial systems, showing a clear evolution from foundational neural network research to sophisticated adaptive control frameworks. Member, Academia Europaea (2021) IEEE Computational Intelligence Society Neural Network Pioneer Award (2022) Dennis Gabor Award from International Neural Network Society (2018) Highly Cited Researcher by Clarivate (2017-present) Editor-in-Chief of Artificial Intelligence Review (2014-present) Liu has mentored numerous students and researchers throughout his career, serving as Editor-in-Chief for major journals and leading significant research initiatives. His work has been supported by multiple grants from the National Science Foundation of the United States and the National Natural Science Foundation of China. His research group continues to push boundaries in adaptive control systems and neural network applications. Currently, Liu leads a research group at SUSTech focusing on intelligent control systems, with active projects in adaptive dynamic programming, reinforcement learning applications, and smart grid technologies. His laboratory serves as a hub for interdisciplinary research connecting theoretical control frameworks with practical industrial implementations.