جستجوی استاد راهنمای دانشگاهی

Wei Zhang is a tenured Professor at the Southern University of Science and Technology (SUSTech) , Shenzhen, China, and a Senior Member of IEEE. He serves as Associate Editor for IEEE Transactions on Control System Technology and leads the CLEAR Lab (Control & Learning for Robotics and Autonomy) within the School of Automation and Intelligent Manufacturing (AiM). His career spans institutions including the University of California, Berkeley (postdoc), and The Ohio State University (Assistant/Associate Professor). Education: PhD in Electrical Engineering from Purdue University (2009), MS in Electrical and Computer Engineering from University of Kentucky (2005), BS in Automation from University of Science and Technology of China (2003) Research Interests focus on integrating control theory, optimization, and machine learning to develop intelligent systems. Key areas include: Legged Robots: Dynamic locomotion control, bio-inspired gait design, and push recovery mechanisms Autonomous Systems: Real-time motion planning, obstacle avoidance, and safe navigation in adversarial environments Smart Grids: Distributed control for energy systems and transactive energy optimization Machine Learning: Reinforcement learning for robotics, Q-learning convergence analysis, and hybrid control-learning frameworks Publication Trends highlight interdisciplinary work at the intersection of robotics and control systems. His recent 2024 papers address: Whole-body control for wheeled-quadrupedal robots Geometric object pose refinement in computer vision Task-space Riccati feedback for underactuated systems Teacher-student reinforcement learning architectures Scientific Awards include: 2016 : NSF CAREER Award 2015 : Lumley Research Award (Ohio State University) 2013 : AFOSR Summer Faculty Fellowship 2018 : National Distinguished Expert (Young, China) 2019 : International Underwater Robot Competition 2nd Prize (team advisor) Academic Leadership involves editorial roles at IEEE Transactions on Control System Technology and IEEE Transactions on Power Systems. His lab provides state-of-the-art robotics platforms including quadruped robots, Kuka manipulators, and UAVs for algorithm validation. Research collaborators span The Ohio State University , UC Berkeley , CMU , and The University of Hong Kong .

• Control Theory
• Optimization Theory
• Machine Learning
• +۵ 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.

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

Zhan Ma is a Professor and PhD Advisor at the School of Electronic Science and Engineering, Nanjing University. He leads research in Neural Video Communication, Smart Cameras, and Computational Vision Models. His work focuses on end-to-end learning for compression, networking, and hardware-software co-design. Dr. Ma holds a PhD from New York University's Tandon School of Engineering (2010), and prior to his current role, he served as Senior Staff Researcher at Huawei (2013-2015) and Senior Researcher at Samsung (2011-2013). Research highlights include pioneering work in point cloud compression (adopted into IEEE standards) and dual-camera systems for high-resolution video acquisition. His algorithms are deployed in WeChat/WeChat Video for rate-quality optimization and in ISO standards for video complexity indicators. Recent work emphasizes machine learning-driven approaches for image/video compression and adaptive streaming frameworks. Honors include the 2023 IEEE CAS Society Outstanding Young Author Award and multiple best paper awards at IEEE WACV, BMSB, and other venues. He leads the Vision Lab at Nanjing University and collaborates with industry partners on practical implementations of his research.

• Neural Video Communication
• Smart Cameras
• Computational Vision Models
• +۳ مورد دیگر

Professor Liu Hongyan is a full-time Professor in the Department of Management Science and Engineering at Tsinghua University's School of Economics and Management, where he has served since 1994, achieving the rank of Professor in 2011 after previously holding positions as Associate Professor (2003-2011) and Teacher. His research bridges theoretical data science with practical applications across e-commerce, healthcare, and social media platforms. Education: PhD in Management, School of Economics and Management, Tsinghua University (2001) His research focuses on big data management , machine learning , and business intelligence with specialized expertise in personalized recommendation systems , medical/financial data analysis , and computer vision applications . Recent work integrates large language models and causal inference to solve complex problems in short video platforms, live streaming, and healthcare analytics, emphasizing real-world impact through industry collaborations. Analysis of his 15 most recent publications (2023-2025) reveals a strong trajectory toward multimodal AI systems combining recommendation engines with computer vision, particularly in 3D animation for advertising and healthcare. Key trends include LLM-enhanced display advertising, emotion-aware facial animation, and medical image annotation using adversarial learning, while maintaining core contributions to behavioral data mining in social networks. Scientific recognition includes: National Archives Administration's Outstanding Scientific and Technological Achievement Award Multiple Best Paper Awards at international conferences Outstanding Doctoral Dissertation Supervisor designation from the Society for Management Science and Engineering Special Award for National Natural Science Foundation project on user behavior pattern discovery Professor Liu has secured leadership roles in major National Natural Science Foundation projects including Innovation Research Groups and international cooperation initiatives. His industry impact is demonstrated through patented recommendation systems adopted by multiple companies, particularly in personalized content delivery for live streaming and short video platforms. As an Outstanding Doctoral Dissertation Supervisor, he mentors the next generation of data science researchers. He serves as Deputy Director of Tsinghua University's Center for Artificial Intelligence and Management Research and holds key positions in national academic societies including the E-Commerce and Cyberspace Management Committee (China Management Modernization Research Association) and the Information Systems Engineering Committee (Chinese Society for Systems Engineering).

• Big data management and analysis
• machine learning
• data mining
• +۷ مورد دیگر

Jianke Zhu is a Professor at the College of Computer Science and Technology of Zhejiang University . He obtained his Ph.D. in Computer Science and Engineering from The Chinese University of Hong Kong and conducted postdoctoral research at the BIWI Computer Vision Lab, ETH Zurich . His research focuses on Computer Vision and Machine Learning , with a particular emphasis on 3D scene understanding, LiDAR-based mapping, and neural rendering. Dr. Zhu’s research spans several subfields, including 3D Reconstruction , Semantic Segmentation , Multimodal Learning , and Autonomous Driving . His work integrates Neural Networks , LiDAR Processing , and Uncertainty Quantification to address challenges in real-time and adverse conditions. Selected Recent Trends: 2025 publications highlight his work in Hexagonal Mesh-based Neural Rendering , Instance-aware 3D Scene Understanding , and Efficient Visual Projectors for Multimodal LLMs . Earlier works include Box2Mask for Instance Segmentation (2024) and Token Selection for Point Cloud Learning (2025). Scientific Awards : Senior member of the IEEE Advising and Grants : As a Doctoral Supervisor , he mentors students in advanced topics like LiDAR Odometry and Multi-view Stereo Recovery . His projects have attracted funding for autonomous driving , 3D scene modeling , and neural rendering .

• Computer Vision
• Machine Learning
• 3D Reconstruction
• +۳ مورد دیگر

Shengcai Liu is an Assistant Professor in the Department of Computer Science and Engineering at the Southern University of Science and Technology (SUSTech). Holding a PhD in Engineering, he has established himself as a researcher with over 10 publications as first or corresponding author in top artificial intelligence conferences and journals. His academic journey includes research positions at Singapore's Agency for Science, Technology and Research (A*STAR) before joining SUSTech's faculty. Education: PhD in Computer Science and Engineering, University of Science and Technology of China (2014-2020) Bachelor's in Computer Science and Engineering, University of Science and Technology of China (2010-2014) Dr. Liu's research centers on automatic algorithm design and evolutionary approaches to machine learning. He investigates how AI systems can autonomously construct efficient algorithms for complex optimization problems while maintaining robustness and reliability. His work bridges theoretical foundations with practical applications in combinatorial optimization, adversarial machine learning, and large language model development, with particular focus on making algorithm design processes more systematic and effective. His publication record demonstrates a clear trajectory from foundational work on algorithm portfolios to sophisticated integration of evolutionary methods with large language models. Recent work shows increasing focus on textual adversarial attacks, combinatorial optimization, and leveraging large language models as optimization tools themselves. This progression reflects both theoretical depth and practical relevance to current AI challenges. Professional Activities: Project Leader for Huawei-funded research on combinatorial optimization solvers (CNY 400,000) Member of IEEE, IEEE CIS, and AAAI Reviewer for top journals including TPAMI, TEVC, TCYB Conference reviewer for NeurIPS, ICML, AAAI, IJCAI Dr. Liu maintains active research collaborations through the Artificial Intelligence RAMS Technology Innovation Laboratory at SUSTech, where his team focuses on developing next-generation automatic machine learning systems with applications in optimization and security domains.

• Artificial Intelligence
• Evolutionary Algorithms
• Automatic Machine Learning
• +۴ مورد دیگر

Liao Shasha serves as a Lecturer in the Department of Animation at Tongji University's School of Art and Media, where she has taught since 2007 while holding administrative roles as Secretary of the Animation Department and Director of the College Library. Her academic journey includes a Bachelor's in Computer Science from North China University of Technology (2002) and a Master's in Software Engineering from Peking University (2007). Her research centers on animation short film creation and health communication , with significant contributions to experimental animation pedagogy, 3D animation production, and the integration of traditional Chinese crafts like Diancui (kingfisher feather art) into contemporary art education. She has developed specialized courses including Animation Storyboarding, 3D Animation, and Traditional Art Design that emphasize hands-on learning and interdisciplinary approaches. Analysis of her 11 publications (2006-2022) reveals a clear trajectory toward educational applications of animation, particularly in health communication initiatives and digital preservation of intangible cultural heritage. Her work consistently bridges technical animation skills with social impact through projects like medical科普 (science popularization) and traditional craft revitalization. Liao Shasha's scholarly impact is reflected in numerous awards: 2005-2007: Multiple awards for animations 'Plant' and 'Injustice' including China Academy Award wins and DigiCon6+3 Gold 2018: 1st Prize at 'Guoqing Cup' for 'Kingfisher Phoenix Headwear' 2020: Tongji University Xincheng Award and dual 'Excellent Mentor' titles 2020-2022: Nine national teaching awards including NCDA 'Excellent Guidance Teacher' honors As an educator, she has secured eight principal-investigator teaching grants totaling over 500,000 RMB, including the 'Virtual Simulation Software for Digital Shadow Play Animation' project (2020). Her mentorship has guided students to 32 competition awards including the National Network Culture Festival Animation First Prize (2019). She actively contributes to Tongji's Media Experiment and Practice Teaching Center and Omnimedia Research Institute, developing innovative animation pedagogy that merges traditional craftsmanship with digital media.

• Animation
• Animation Short Film Creation
• Health Communication
• +۳ مورد دیگر

Prof. Zhaoyuan Ma is a tenured professor at the School of Automation and Intelligent Manufacturing, Southern University of Science and Technology (SUSTech), with prior appointments at Tsinghua University's Future Lab (2018-2022), University of Sheffield (2017-2020), and Chinese Academy of Sciences (2009-2015). He holds a PhD in Atomic and Laser Physics from the University of Oxford (2005) and a B.Sc. in Nuclear Physics from Peking University (2001). Education: D.Phil., Atomic and Laser Physics, University of Oxford (2005) B.Sc., Nuclear Physics, Peking University (2001) His research spans Smart Manufacturing , Quantum Control , and Artificial Intelligence , with notable work on quantum engineering in microgravity environments and AI-driven biomedical imaging systems. Recent publications focus on coronary artery segmentation algorithms, optical lattice design for quantum systems, and cold atom dynamics. Key trends in his 15 most recent articles include AI applications in cardiovascular disease diagnosis, precision cooling techniques for quantum gases in microgravity, and optical lattice manipulation for quantum simulations. His work bridges theoretical quantum physics with practical manufacturing innovations. Scientific Awards: Hundred Talents Professor of Chinese Academy of Sciences (2009) Fellow of the Institute of Physics Prof. Ma has held leadership roles including Assistant Dean of Tsinghua Shenzhen International Graduate School (2020-2021) and directed the Data Driving Manufacturing Research Center at Tsinghua University's Future Lab (2018-2022). His career includes postdoctoral research at NIST, University of Maryland, UC Berkeley, and University of Oxford.

• Smart Manufacturing
• Quantum Control
• Artificial Intelligence
• +۴ مورد دیگر

Jie Tang is a Professor at the Department of Computer Science, Tsinghua University , and a Fellow of ACM, AAAI, IEEE . His research focuses on Artificial General Intelligence (AGI) , with significant contributions to large pre-trained models like GLM-130B, ChatGLM, CogView, CogVideo, and CodeGeex. Research Trends : Jie Tang's work spans AGI development with human-like reasoning Graph Neural Networks for network representation Social network mining and influence modeling Academic knowledge graph construction (AMiner system) Advancing foundation models for cross-modal tasks Scientific Awards : SIGKDD Test-of-Time Award SIGKDD Service Award NSFC Distinguished Young Scholar 2nd National Award for Science & Technology Advising and Grants : He mentors highly-motivated students and postdocs in AGI research. His work has received extensive funding and recognition, including over 400 publications in top conferences (IJCAI, AAAI, NeurIPS, KDD) and journals (TPAMI, TKDE).

• Artificial General Intelligence (AGI)
• Data Mining
• Social Networks
• +۲ مورد دیگر

Jiong Zhang is an Associate Professor and Deputy Head of the Department of Hydraulic Engineering at the School of Civil Engineering, Shandong University. He holds a Ph.D. in Civil Engineering from INSA de Rennes, France, and has been affiliated with Shandong University since 2012, initially as a Lecturer and promoted to Associate Professor in 2015. His research focuses on pavement materials and computational simulations (CFD & DEM) for analyzing multi-phase flows and clogging in porous media. Education: Ph.D. in Civil Engineering (INSA de Rennes, 2012), M.Eng. in Environmental Engineering (Ocean University of China, 2008), B.Eng. in Water and Wastewater Engineering (Shandong Institute of Architecture & Engineering, 2003) His recent publications emphasize numerical and experimental studies on clogging mechanisms in pervious pavements, stormwater runoff impacts, and structural integrity of concrete piles under seismic and vehicular loads. Key themes include computational fluid dynamics, material durability, and geotechnical responses to environmental stressors. Selected grants include projects funded by the National Natural Science Foundation of China Youth Project and Shandong Province Key R&D Program, focusing on clogging analysis, restoration techniques for pervious pavements, and machine vision-based pavement performance evaluation. Collaborators in his research span multiple institutions, though formal student advisement details are not explicitly listed.

• Pavement materials
• CFD & DEM Simulation
• Environmental Engineering
• +۱ 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.

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

JIANG Liguang is an Assistant Professor in the School of Environmental Science and Engineering at Southern University of Science and Technology (SUSTech). He received his MSc from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences in 2014, and his PhD in Remote Sensing & Hydrology from the Technical University of Denmark in 2018. Prior to joining SUSTech in March 2021, he completed a postdoctoral fellowship at the Technical University of Denmark. Dr. Jiang's research spans both remote sensing and hydrological sciences, with a focus on satellite altimetry applications for inland water monitoring and modeling. His work investigates the hydrological dynamics of surface water bodies such as lakes, reservoirs, and rivers in the context of climate change. He has made significant contributions to hydrodynamic modeling using distributed altimetry-derived Water Surface Elevation data, broadening the applications of satellite altimetry in hydrology. His recent publications reveal a strong focus on advancing satellite altimetry techniques for river and lake monitoring, with particular emphasis on Sentinel-3, CryoSat-2, and SWOT missions. His research integrates machine learning approaches with traditional hydrological modeling, demonstrating innovative methods for streamflow prediction and water resource assessment. The interdisciplinary nature of his work connects remote sensing technology with practical water management applications. Scientific Awards: 2023 Reviewer Award of The Innovation Geoscience 2023 Reviewer Award of IAHS Hydrological Sciences Journal 2021 Shenzhen Overseas High-Caliber Personnel 2019 Otto Mønsteds Fund Travel award 2018 Outstanding Reviewer of the Remote Sensing of Environment Dr. Jiang serves as an Associate Editor for Sustainable Water Resources Management (Springer Nature) and as a Young Editorial Board Member for the Journal of Remote Sensing. His funded research projects include significant work with international organizations such as the European Space Agency, NASA/CNES, and Danish research agencies, demonstrating strong international collaboration in his field.

• Remote Sensing Hydrology
• Satellite Altimetry
• Hydrological Modeling
• +۵ مورد دیگر

Yepang Liu is a tenured Associate Professor in the Department of Computer Science and Engineering at Southern University of Science and Technology (SUSTech). He leads the Software Quality Lab and directs the Trustworthy Software Research Center under the Research Institute of Trustworthy Autonomous Systems. His academic journey includes a B.Sc. in Computer Science from Nanjing University (2010) and a Ph.D. in Computer Science and Engineering from The Hong Kong University of Science and Technology (HKUST) in 2015, followed by postdoctoral research at HKUST's CASTLE Lab and Cybersecurity Lab (2015–2018). Research interests focus on Software Testing and Analysis Empirical Software Engineering AI for Software Engineering (AI4SE) Trustworthy AI Mobile Computing Software Security Current projects explore automated testing for emerging technologies like HarmonyOS and extended reality (XR), leveraging large language models (LLMs) and reinforcement learning. Awarded thrice with ACM SIGSOFT Distinguished Paper Awards (ICSE 2021, ASE 2016, ICSE 2014) and a Platinum Level Research Artifacts Honor (FSE 2016), Liu has also received teaching accolades, including SUSTech's Junior Faculty of the Year (2021) and the Top-10 Most Popular Instructor Among 2024 Graduates. His work is funded by the National Natural Science Foundation of China, National Key Research and Development Program of China, and industry partnerships.

• Software Testing and Analysis
• Adaptive Systems
• Mobile Computing
• +۴ مورد دیگر

Liu Wei is a Research Professor in the Department of Mechanical and Energy Engineering at Southern University of Science and Technology (SUSTech). He holds a PhD in Computer Application Technology from the University of Chinese Academy of Sciences (2013) and has extensive experience in 3D imaging perception, computer vision, and embedded systems. Education: PhD (Computer Science, Chinese Academy of Sciences), MSc (Instrument Science, USTC), BSc (Measurement & Control, USTC) Current roles: Research Professor, postdoctoral advisor, and assistant dean at SUSTech Institute of Robotics Key research areas: 3D machine vision, industrial robots, surgical robotics, and intelligent autonomous systems His work spans both academic and industrial applications, including robotics for supermarket environments and medical surveillance devices. He has led multiple significant projects including 3D visual inspection robots and UAV joint labs. Scientific achievements include the IEEE ROBIO Best Conference Paper Award and multiple invention patents. His research combines computer vision with embedded systems for both industrial and biomedical applications. Contact details: 5th Floor, North Building, College of Engineering, SUSTech | Office: 0755-88011264 | Email: liuw2@sustech.edu.cn

• Computer Vision
• Robotics
• 3D Imaging
• +۴ مورد دیگر

DING Yulong is a Research Assistant Professor at the Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen. He holds a Ph.D. in Chemical Engineering from the University of British Columbia (2012) and M.S./B.S. in Chemical Engineering from Tsinghua University (2008/2005). His research focuses on Internet of Things (IoT) , Industrial IoT Safety and Security , Public Safety , and Low Power Wide Area Network Communication Technology . Ph.D., Chemical Engineering, University of British Columbia (2012) M.S., Chemical Engineering, Tsinghua University (2008) B.S., Chemical Engineering, Tsinghua University (2005) His work bridges IoT applications with cyber-physical systems, emphasizing safety-security requirement conflicts , anomaly detection in industrial processes, and low-power communication protocols like LoRa. He has pioneered methods for real-time positioning using UWB and reinforcement learning for network resource allocation. His scientific awards include the 2014 Shenzhen Overseas High-level Talents (Class B). He supervises research projects in industrial IoT security and mentors students in grant applications, protocol design, and cyber-physical systems. His lab is based in Room 645A, South Tower, College of Engineering, SUSTech.

• Internet of Things
• Industrial IoT Safety and Security
• Public Safety
• +۵ مورد دیگر