جستجوی استاد راهنمای دانشگاهی

Wei Zhangمشاهده پروفایل

استاد

• Control Theory
• Optimization Theory
• Machine Learning
• +۵ مورد دیگر

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 .

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.

• Media Economics
• Artificial Intelligence in Communication
• Film and Audiovisual Studies
• +۲ مورد دیگر

Dr. Mei Nan is an Associate Professor in the Department of Communication at Tongji University's School of Art and Media. With a career spanning since 2004, she previously held positions at Chang'an University before joining Tongji in 2017. Her academic credentials include a Master's from Shaanxi Normal University, postgraduate studies at Communication University of China, and ongoing doctoral research at Xi'an Jiaotong University's School of Economics and Finance. Research Expertise Her research bridges media economics, AI-driven communication paradigms, and film studies, with specific focus areas including: Media economics and corporate governance interactions Artificial intelligence's impact on communication theory Film/audiovisual language analysis Media culture evolution Marketing models in digital ecosystems Teaching Portfolio Dr. Nan teaches both undergraduate courses ( Audiovisual Language, Chinese/Foreign Film History, Media Culture, Chinese Film Appreciation ) and graduate seminars ( Intelligent Communication Theory and Practice ). Her pedagogical approach integrates contemporary media developments with theoretical foundations. Awards and Grants Tongji University Hongda Award (2021) Tongji Cup General Education Course Paper Competition Teaching Teacher Excellent Organization Award (2021) Principal Investigator: Shanghai Philosophy and Social Science Planning Project (2018BGL025) studying media impact on corporate recovery

Chao YUANمشاهده پروفایل

استاد

• Discrete Element Modeling
• Multi-physics and Multiphase Couplings
• Unsaturated Soil Mechanics
• +۱ مورد دیگر

Chao YUAN is a Professor in the Department of Engineering Mechanics at the School of Civil Engineering, Shandong University, China. He obtained his PhD in Geomechanics/Civil Engineering from Université Grenoble Alpes (France) in 2016, following MSc and BEng degrees from Shandong University. Education : PhD (2012-2016), MSc (2009-2012), BEng (2005-2009) Prior Appointments : Postdoctoral Associate at University of Calgary (2017-2019), Postdoctoral Research Fellow at Université Grenoble Alpes (2016-2017) Research Interests focus on granular material mechanics through advanced computational methods. His work includes discrete element modeling , multi-physics/multiphase couplings , unsaturated soil mechanics , and soil conditioning in Tunnel Boring Machines . Key contributions involve pore-scale simulations of hydromechanical interactions and stability analysis of tunnels and slopes. Publication Trends emphasize computational geotechnics , with studies on drainage dynamics, wetting-induced collapse, and machine learning applications in geomechanics. His articles span journals like Granular Matter , Proceedings of the National Academy of Sciences , and Acta Geotechnica , reflecting interdisciplinary approaches to granular media. Contact : chao.yuan@sdu.edu.cn , chaoyuan.geo@outlook.com

• Planetary atmospheres
• Exoplanet observations
• Martian atmospheric dynamics
• +۳ مورد دیگر

Siteng Fan is an Associate Professor in the Department of Earth and Space Sciences at Southern University of Science and Technology. His research focuses on planetary atmospheres, exoplanet observations, and Martian atmospheric dynamics, combining observational data from missions like TGO and EMM with climate models such as Mars PCM. Education: B.S. in Space Science and Technology from Peking University (2015), Ph.D. in Planetary Science from Caltech (2020). Research Interests: Dynamics of planetary atmospheres (Mars, Titan, Pluto), photochemistry, microphysical processes, and light curve analysis for exoplanet surface inversion. Scientific Awards: Xie Yibing Young Scientist Award (2023), Marie Skłodowska-Curie Postdoctoral Fellowship (2022), NSFC Excellent Young Scientists (Overseas) (2022). Publication Trends: Recent work spans Mars climate modeling, Pluto/Titan atmospheric haze, exoplanet proxy studies, and radiative transfer algorithms.

• Consumer Behavior
• Product and Service Experience
• Decision Science
• +۳ مورد دیگر

Maggie Wenjing Liu is a tenured Associate Professor in the Department of Marketing at Tsinghua University's School of Economics and Management (SEM). She holds leadership roles as Associate Director of the Computational and Behavioral Science Lab and China Retail Research Center, and Chair of the Marketing Department's Academic Seminar Committee. Education: Ph.D. in Marketing, Rotman School of Management, University of Toronto M.S. in Marketing, NUS Business School, National University of Singapore Bachelor in Economics, University of International Business and Economics Research Focus: Her work centers on consumer behavior , product/service experience , decision science , and pricing , examining psychological mechanisms through experimental and analytical methods. Key themes include ritualistic consumption, AI-human interaction in marketing, visual branding effects, and cross-cultural service responses. Publication Trends: Recent work (2017-2025) appears in top journals like Production and Operations Management (UTD) and Journal of Consumer Psychology (FT50), revealing strong interdisciplinary connections between behavioral science, marketing strategy, and data-driven consumer insights with increasing focus on AI applications and crisis response. Scientific Awards: National Natural Science Foundation Youth Project Outstanding Evaluation (2017) National Natural Science Foundation General Project Outstanding Evaluation (2021) Tsinghua University teaching reform project Grade A (2020) Beijing Higher Education Young Elite Scholar Award Two-time Outstanding Expert Reviewer (Journal of Marketing Science) Society of Asian Retailing and Distribution Best Paper Award Advising & Grants: As a doctoral advisor, she mentors PhD candidates who frequently co-author publications. She secured three National Natural Science Foundation General Programs, one Youth Project, three provincial/ministerial grants, and multiple Tsinghua projects, with two NSFC projects rated Outstanding upon completion. Labs & Leadership: She co-directs Tsinghua SEM's Computational and Behavioral Science Lab and China Retail Research Center, driving research at the intersection of marketing analytics, consumer neuroscience, and retail innovation while serving on editorial boards for Marketing Letters and Journal of Business Research .

Wei Huمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Graphs
• Semantic Web Technologies
• +۵ مورد دیگر

Wei Hu is a full Professor and Ph.D. supervisor in the Department of Computer Science and Technology at Nanjing University, China. He earned his Ph.D. and B.S. from Southeast University in 2009 and 2005, respectively, and joined Nanjing University faculty in 2009. He has held visiting positions at Stanford University (2014-2015), University of Texas at Arlington (2016-2017), and University of Toronto (2017) as a visiting scholar/professor. Research Interests focus on Knowledge Graphs : Representation learning, foundation models, and error detection Databases : Entity alignment, crowdsourcing, and blockchain integration Digital Medicine : Collaboration with Nanjing University's National Institute of Health Data Science Publication Trends show expertise in knowledge graph reasoning, federated learning, and biomedical applications. Recent works include in-context learning for graph reasoning and blockchain-based data fusion systems. Scientific Awards include Huawei 2025 Challenges Spark Award ASE 2024 Distinguished Paper Award CHIP 2021 Best Paper Award CCKS 2018 Best English Paper Award Nanjing University Study Abroad Program Awardee (2013) IBM China Excellent Student (2008) Advising involves leading the Knowledge Fusion Group at Nanjing University, mentoring 18 current and former Ph.D. and Master's students. Professional services include editorial roles at Transactions on Graph Data and Knowledge and Big Data Research , plus committee memberships in CCF, CIPSC, and JSCS.

ZHOU Xianghongمشاهده پروفایل

استاد

• Urban Public Service Management
• Medical Care and Health Policy
• Poverty Reduction
• +۳ مورد دیگر

ZHOU Xianghong is a Professor and PhD Advisor at the School of Economics and Management, Tongji University. Currently serving as Assistant Dean, she specializes in urban public service management, medical care, and health policy. Her academic and professional work bridges public administration, poverty reduction, and sustainable development. Doctor of Laws (Sociology), Nanjing University (1999–2002) Post-doctorate in Management Science and Engineering, Tongji University (2002–2005) Her research focuses on macro-level policy analysis, particularly in urban public service management , medical care and health policy , and poverty reduction mechanisms . She has led studies on smart city development, agricultural carbon emission efficiency, and health resource allocation. The 15 most recent publications span interdisciplinary topics, including environmental economics, machine learning for recommendations, and public health governance. Her work emphasizes quasi-experimental methods, regional disparities, and policy evaluation in urban and rural contexts. ZHOU has secured grants from the National Natural Science Foundation of China (NSFC) and Shanghai government agencies for projects on smart city governance, poverty reduction, and environmental policy. She has taught courses across MPA, MBA, and executive programs, focusing on public affairs, policy analysis, and urban innovation.

• Multi-agent systems
• Distributed artificial intelligence
• Autonomous unmanned systems
• +۳ مورد دیگر

Zhiyun Lin is Dean and Tenured Professor at the School of Automation and Intelligent Manufacturing, Southern University of Science and Technology (SUSTech). He holds affiliations as Foreign Academician of the Russian Academy of Engineering, Fellow of IEEE, IET, and AAIA. Previously, he served at Zhejiang University (2007-2017) and Hangzhou Dianzi University (2017-2021), with visiting positions at Yale University, ANU, and University of Tokyo. Education: PhD in Electrical and Computer Engineering, University of Toronto (2005) MSc in Control Theory, Zhejiang University (2001) BSc in Industrial Automation, Yanshan University (1998) Research Focus: Develops theoretical frameworks for multi-agent coordination, distributed AI algorithms, and cyber-physical systems. His work enables robust autonomous swarm behaviors in robotics and sensor networks through novel control strategies and optimization techniques. Publications: 230+ papers predominantly in IEEE Transactions journals demonstrate sustained contributions to formation control, distributed localization, and networked systems. Recent works (2021) advance resilient beamforming and finite-time stabilization for robotic formations. Awards: Natural Science Second Prize, Zhejiang Province (2020, 2013) Science and Technology Innovation First Prize (2020) Industry-University-Research Cooperation Innovation Award (2021) Prestigious fellowships: IEEE/IET/AAIA Leadership: Directs SUSTech's School of Automation and Intelligent Manufacturing. Formerly established the Artificial Intelligence Institute at Hangzhou Dianzi University and led research centers at Zhejiang University. Serves as Associate Editor for IEEE Systems Journal and IEEE Control Systems Letters.

• Social Networks
• Platform Economy
• Online Word-of-Mouth Marketing
• +۵ مورد دیگر

Tao Lu serves as an Assistant Professor and Doctoral Supervisor at the Business School of Southern University of Science and Technology (SUSTech) since September 2020. His academic appointments focus on bridging information systems, finance, and artificial intelligence research within a business context. Education: Ph.D. in Information Systems, The Chinese University of Hong Kong (2020) M.Phil. in Information Systems, Hong Kong University of Science and Technology (2017) B.S. in Physics/Economics, Tsinghua University (2015) Dr. Lu's research spans three interconnected domains: (1) Social network dynamics and online word-of-mouth marketing using analytic modeling and experimental design; (2) Quantitative finance focusing on distributional uncertainty in asset pricing and neural network applications; (3) Algorithmic bias mitigation in machine learning systems. His work combines rigorous theoretical modeling with empirical validation, often translating to practical applications in quantitative finance. Scientific Recognition: Innovation Research Award of China Information Economics Society (2022) Dr. Lu actively supervises research through his team's recruitment of research assistants and postdoctoral fellows, with projects applying to real-world trading systems in quantitative hedge funds. His research group focuses on developing computational models for financial markets and social platforms, emphasizing both theoretical contributions and practical implementation.

• Infrastructure
• Big Data Analytics
• Sustainable Infrastructure Networks
• +۳ مورد دیگر

CAO Dongping is an Associate Professor in the Department of Construction Management and Real Estate at School of Economics and Management, Tongji University . He holds a Ph.D. in Construction Engineering and Management from The Hong Kong Polytechnic University (2013-2016) and Tongji University (2009-2015), with a visiting research experience at the University of Manchester (2010-2011). M.Sc. in Management Science and Engineering, Tongji University (2006-2009) B.Sc. in Construction Engineering and Management, Chongqing University (2002-2006) His research focuses on Infrastructure Big Data Analytics and Sustainable Infrastructure Networks , with a strong emphasis on Building Information Modeling (BIM) adoption, project governance, and network dynamics. His recent work explores contagion mechanisms in BIM implementation, urban infrastructure development, and AI integration in construction. CAO Dongping's selected publications (2023-2025) span topics from BIM policy diffusion and high-speed rail network dynamics to AI in construction and labor migration. His articles highlight interdisciplinary approaches combining network analysis, behavioral modeling, and optimization techniques. 2024 Outstanding Advisor Award, China Engineering Management Case Competition for Graduate Students 2022-2025 multiple awards for teaching excellence and scientific progress 2018-2020 grants from National Natural Science Foundation of China, Shanghai Municipal Transportation Commission, and Tongji University He has served as Principal Investigator for projects on BIM adoption, digital construction technologies, and urban infrastructure maintenance. His teaching interests include Virtual Design and Construction and Project Management .

Mao Boمشاهده پروفایل

دانشیار

• Information Systems
• Knowledge Management
• Virtual Communities
• +۳ مورد دیگر

Mao Bo serves as Associate Professor in the Department of Management Science and Engineering at Tsinghua University's School of Economics and Management. His academic career is anchored at China's premier institution with continuous service in the department since his advanced degrees from Tsinghua. His research spans critical domains of modern information systems, with primary focus on Chinese enterprise information strategy , virtual community knowledge management , and complex supply chain systems . His work bridges theoretical frameworks with practical implementations in organizational contexts, particularly examining how digital platforms transform knowledge sharing and operational coordination. Teaching responsibilities include core courses on Information Systems Analysis and Design , Management and Organization , and specialized instruction in knowledge management systems. His academic trajectory includes a significant visiting scholar appointment at MIT's Sloan School of Management during 2001. Publications reveal consistent contributions from 2000-2009 with predominant focus on virtual community dynamics, supply chain analytics, and knowledge infrastructure design. His methodology frequently integrates multi-agent systems, data mining, and operations research techniques to solve complex organizational problems. Professional engagement demonstrates deep institutional commitment through campus-wide initiatives including academic research platform development and laboratory modernization projects at Tsinghua University.

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.

• High Performance Computing
• Distributed Systems
• Cloud Computing
• +۲ مورد دیگر

Zhuozhao Li is an Assistant Professor in the Department of Computer Science and Engineering at Southern University of Science and Technology (SUSTech) in Shenzhen, China. He joined SUSTech in August 2021 after serving as a Postdoctoral Scholar at the University of Chicago from July 2018 to July 2021. His research focuses on high-performance computing, distributed systems, and cloud/edge computing, with applications across scientific domains. Ph.D. in Computer Science, University of Virginia, May 2018 M.S. in Computer Science, University of Southern California, May 2012 B.E. in Computer Science, Zhejiang University, July 2010 Dr. Li's research spans several critical areas in modern computing infrastructure. His primary focus is on High Performance Computing , where he develops novel approaches to optimize computational efficiency in scientific applications. In Distributed Systems , his work addresses challenges in large-scale system coordination and resource management. His contributions to Cloud/Edge Computing focus on improving virtualization techniques and resource allocation strategies. Additionally, he explores applications in the Internet of Things , examining how distributed computing paradigms can enhance IoT infrastructure. Dr. Li's publication record demonstrates a consistent focus on advancing distributed computing systems and their scientific applications. His recent work shows a clear progression from foundational research on data-parallel frameworks and job scheduling toward more applied systems for scientific computing. His contributions to projects like funcX and DLHub represent significant advancements in making distributed computing more accessible for scientific workflows. A notable trend is the increasing interdisciplinary nature of his work, with applications spanning from computational biology (SARS-CoV-2 research) to privacy-preserving spatial crowdsourcing. ACM HPDC Best Paper Nominees, 2019 IEEEMASS Service Award, 2019 Outstanding Graduate Research Assistant, University of Virginia, 2018 Dr. Li actively mentors students and researchers, currently recruiting PhD students, Master's students, postdocs, and research assistants for his research group at SUSTech. His research has been supported through various collaborative projects, including significant contributions to the U.S. Department of Energy National Virtual Biotechnology Laboratory Project about COVID-19, which was awarded the Secretary of Energy Achievement Award. His work on funcX, DLHub, and Parsl represents major software infrastructure development efforts with broad scientific impact. Dr. Li is affiliated with multiple research initiatives, including the Globus Lab (during his postdoc at University of Chicago) and various collaborative projects involving high-performance computing resources. At SUSTech, he leads a research group focused on distributed systems and high-performance computing. His work often involves collaboration with researchers across institutions, particularly in projects related to scientific computing infrastructure like funcX and DLHub.

• Random Matrix Theory
• High dimensional Statistics
• Time Series Analysis
• +۱ مورد دیگر

Li Zeng is an Associate Professor in the Department of Statistics and Data Science at Southern University of Science and Technology (SUSTech) since January 2021, following her Assistant Professor role at the same institution from August 2019 to December 2020. Previously, she was an Eberly Postdoctoral Fellow at Pennsylvania State University under Prof. Runze Li (2017-2019) and a Research Assistant at the University of Washington with Dr. Fang Han (2017). Ph.D. in Statistics and Actuarial Science from the University of Hong Kong (2017), advised by Prof. Jianfeng Yao M.Sc. in Statistics from Renmin University of China (2012) B.Sc. in Mathematical Science from Beijing Normal University (2009) Her research centers on Random Matrix Theory and High Dimensional Statistics , with significant contributions to eigenvalue/singular value distributions in large-dimensional matrices. She extends these theoretical foundations to Time Series Analysis for lagged auto-correlation structures and applies them to Machine Learning problems including neural network optimization and regularization. Her work bridges asymptotic probability theory with practical data science applications, developing robust methods for high-dimensional inference. Analysis of her 15 most recent publications (2016-2025) reveals a dominant focus on high-dimensional statistical theory with increasing machine learning integration. Key trends include asymptotic analysis of covariance/correlation matrices (60% of publications), factor modeling innovations (20%), and deep learning applications (20%). She consistently publishes in top-tier venues including Annals of Statistics (5 papers), Journal of the American Statistical Association , and machine learning conferences (ICML, ECCV), demonstrating exceptional interdisciplinary impact. Excellent Teaching Assistant Award (5 times) from HKU Department of Statistics and Actuarial Science (2012-2017) Dr. Li actively recruits postdoctoral researchers specializing in probability theory and high-dimensional statistics, emphasizing candidates with strong mathematical backgrounds. As a referee for premier journals including Annals of Statistics , JASA , and Journal of the Royal Statistical Society: Series B , she contributes significantly to scholarly review. Her research is institutionally supported through SUSTech faculty positions, with potential external funding inferred from extensive publication output and conference participation. Within SUSTech's Department of Statistics and Data Science (established 2019), Dr. Li contributes to a rapidly expanding research ecosystem focused on high-dimensional data analysis. The department supports multiple research directions including biostatistics and financial statistics, with active graduate programs (M.Phil/Ph.D.) and developing initiatives in data science education. Her teaching portfolio includes undergraduate Statistical Calculation and Software and graduate-level High Dimensional Statistics courses.