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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
• +5 more

LIN Meng is an Associate Professor at the Department of Mechanical and Energy Engineering , Southern University of Science and Technology (SUSTech) . He holds a Ph.D. in Mechanical Engineering from Swiss Federal Institute of Technology in Lausanne (EPFL) (2018) and has held postdoctoral positions at Caltech's Joint Center for Artificial Photosynthesis (2018-2019). Research Interests include solar thermal/thermochemical/(photo)electrochemical energy conversion devices , CO2 capture and utilization , and multi-scale modeling and simulation . His work focuses on optimizing energy systems through advanced computational models and cross-disciplinary integration of physics. Recent Publications highlight his contributions to solar fuel processing, CO2 conversion technologies, and hybrid electrochemical systems, with articles in Nature Communications , Joule , and Energy & Environmental Science . His research emphasizes scalable solutions for sustainable energy and carbon management. Scientific Awards ASME Graduate Student Award (2018) Outstanding Reviewer of Solar Energy (2018, 2015) Swiss National Science Foundation Postdoc Fellowship (2017) Shanghai Outstanding Master Thesis (2016) Shanghai Jiao Tong University Outstanding Graduate (2013)

• Solar Energy
• Thermochemical Conversion
• Carbon Capture
• +3 more

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
• +9 more

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
• +3 more

Li Zhongfei is a Chair Professor and Vice Dean of the School of Business at Southern University of Science and Technology (SUSTech). He is a member of the State Council's Discipline Review Group, National Outstanding Young Scientist, National Model Teacher, and recipient of the State Council's Special Government Allowance. His career spans roles as Distinguished Professor at Lingnan College, Executive Dean at Sun Yat-sen University, and leadership positions in academic societies such as the Chinese Society for Systems Engineering. Education : PhD in Management (1997-2000) and Master's in Operations Management (1988-1990) from the Chinese Academy of Sciences, and a Bachelor of Science in Mathematics from Lanzhou University. Research Interests : His work focuses on Technological Finance Green Finance Pension Finance Financial Engineering and Risk Management Insurance and Actuarial Science with applications to financial markets, digital finance, and sustainability. Scientific Trends from his publications include: ESG rating impacts on capital markets Green innovation under carbon pricing Machine learning in cryptocurrency forecasting Robust portfolio optimization under uncertainty Climate risk and policy analysis Post-pandemic economic recovery and systemic risk Scientific Awards : Recipient of the National Teaching Achievement Award, Guangdong Province Philosophy and Social Sciences prizes, Zhong Jiaqing Operations Research Award, and recognition as a Top 2% Scientist (Stanford, 2023). He was honored as a National Model Teacher and 'Top Ten Most Respected Business School Deans in China.' Grants & Projects : Principal investigator in NSFC key projects, including 'Intelligent Investment and Risk Management under Dual Carbon Strategy' and 'Financial Innovation and Risk Management.' His projects address fintech, pension funds, and climate risk. Labs & Teams : Leads advanced research teams in SUSTech's School of Business and collaborates with international institutions like the University of Waterloo and Hong Kong Polytechnic University.

• Technological Finance
• Green Finance
• Pension Finance
• +6 more

Shi Li is a Professor in the Theory Group at the Department of Computer Science and Technology, School of Computer Science, Nanjing University. He previously held faculty positions at the University at Buffalo (2015–2023) as Assistant and Associate Professor, and was a Research Assistant Professor at Toyota Technological Institute at Chicago (2013–2015). He earned his Ph.D. from Princeton University in 2014 under Moses Charikar and completed his B.S. in Computer Science and Technology at Tsinghua University, where he was part of Andrew Chi-Chih Yao’s Special Pilot Class. His research lies at the intersection of theoretical computer science and combinatorial optimization, with a focus on the design and analysis of algorithms for problems in clustering, scheduling, network design, facility location, and online algorithms. He also explores learning-augmented algorithms and differential privacy in algorithmic contexts. His work combines deep theoretical insights with practical algorithmic frameworks, often leveraging linear programming relaxations, iterative rounding, and randomized techniques. The recent publications highlight a consistent trend in approximation algorithms, particularly in clustering (e.g., correlation clustering, fair k-set selection), scheduling (e.g., unrelated machine scheduling, load balancing), and robust optimization. His work frequently appears in top-tier theoretical venues such as STOC, FOCS, SODA, and ICALP, with increasing emphasis on fairness, privacy, and efficiency in algorithm design. Best Paper Award of Track A, ICALP 2011 Co-winner of Best Paper Award, FOCS 2012 Invited to Special Issue of SICOMP (FOCS 2017 paper) Best Paper Award, COCOON 2018 Invited to Special Issue of SICOMP (STOC 2019 paper) Best Paper Award of Track A, ICALP 2024 Outstanding Paper Award, SPAA 2024 Shi Li has advised several PhD and master’s students, including Yuda Feng, Han Dai, Zihao Liang, and Jia Ye, and has mentored postdoctoral researcher Ruilong Zhang. He has served on numerous program committees (e.g., STOC, SODA, ICALP) and is an Editorial Board Member of ACM Transactions on Algorithms . He teaches core algorithm courses such as Design and Analysis of Algorithms and Advanced Algorithms , and actively collaborates with researchers worldwide. His lab focuses on theoretical foundations of efficient and fair algorithm design, with applications in large-scale data analysis and distributed systems.

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Combinatorial Optimization
• +11 more

Kun An is a Professor at the Department of Traffic Information and Control Engineering within the College of Transportation Engineering at Tongji University. She has previously held academic positions at Monash University (Senior Lecturer, 2018–2019; Lecturer, 2016–2018) and conducted postdoctoral research at the University of Illinois at Urbana-Champaign (2015–2016) and The Hong Kong University of Science and Technology (2014–2015). Her academic journey includes a PhD in Civil Engineering from HKUST (2014) and a Bachelor's degree from Tongji University (2009). PhD: Civil Engineering, The Hong Kong University of Science and Technology (2014) Bachelor's: Transportation Engineering, Tongji University (2009) Dr. An specializes in intelligent transportation systems, focusing on optimizing complex traffic networks, characterizing traveler behavior in stochastic environments, and advancing electric vehicle sharing infrastructure. Her research spans urban transit planning, carsharing logistics, battery electric bus deployment, and real-time traffic signal optimization, with applications to mitigate rail disruptions and enhance multimodal connectivity. Her publications emphasize solving transport challenges through stochastic programming, game theory, and behavioral analysis. Key themes include autonomous vehicle integration, demand uncertainty modeling, and sustainable mobility solutions. Awards include the Hong Kong PhD Fellowship and multiple best paper recognitions. Hong Kong PhD Fellowship (2010–2014) TRBADB30 Best Paper Nomination (2014) Best Paper at 18th Hong Kong Transportation Annual Meeting (Second Author, 2013)

• Intelligent Transportation Systems
• Traffic Network Optimization
• Stochastic Demand Modeling
• +3 more

高建 (Gao Jian) is a Professor and doctoral supervisor at Tsinghua University's School of Economics and Management, where he also serves as Deputy Director of the Academic Committee and Director of the G20 Entrepreneurship Research Center. His prior leadership roles include Party Committee Secretary (2014–2019), Vice Dean (2012–2015), and Department Director. He holds visiting scholar credentials from Stanford University and MIT. Education: 2004: Visiting Scholar, Stanford University Graduate School of Management 2000: Visiting Scholar, MIT Sloan School of Management 1997: Visiting Scholar, MIT Sloan School of Management 1996: PhD, Tsinghua University Research Interests: Gao Jian specializes in venture capital, entrepreneurship, strategic management, and corporate transformation. His recent work explores G20 entrepreneurship policies, technology-driven ventures, sustainable business models, and digital innovation. His interdisciplinary approach integrates economics, psychology, and policy analysis to address global entrepreneurial challenges. Publications: His research spans empirical studies on entrepreneurial psychology, innovation ecosystems, venture financing, and policy impacts. Articles frequently analyze China's entrepreneurial landscape, emphasizing job creation, technology commercialization, and cross-border investment trends. Longitudinal and large-scale datasets underpin his work on startup success factors and ecosystem development. Awards & Honors: 2021–2020: Tsinghua SEM EMBA/Executive Education Teaching Excellence Awards 2020: National First-Class Undergraduate Course (co-led) 2019: Outstanding Master’s Thesis Supervisor 2018: National Education Award (Second Prize), Outstanding Doctoral Supervisor 2017: Beijing Education Award (First & Second Prize) 2014: Best Paper Award (China Strategy Forum) 2013: National Research Award (Third Prize) 2007: Ministry of Education ‘New Century Talent’ Teaching & Advising: He teaches courses across undergraduate, MBA, EMBA, and executive programs, including Entrepreneurial Management , Venture Capital , and Corporate Control . Recognized for mentoring excellence, he received Tsinghua’s Outstanding Thesis Supervisor awards (2018–2019) and led the design of nationally accredited curricula. Leadership: As Director of the G20 Entrepreneurship Research Center, he coordinates international policy analyses and promotes best practices in entrepreneurship ecosystems. The center’s outputs include comparative studies and global reports influencing G20 policy frameworks.

• Venture Capital
• Entrepreneurship
• Strategic Management
• +6 more

Yiming Luo is a Research Assistant Professor at the Advanced Institute for Ocean Research , Southern University of Science and Technology (SUSTech), with a Ph.D. in Marine Geology from the Southern China Sea Institute of Oceanology, Chinese Academy of Sciences (2020) and a visiting student experience at the University of Rhode Island (2019–2020). He holds a B.S. in Marine Sciences from Sun Yat-Sen University and an exchange program at National Chung Cheng University , Taiwan. His research focuses on ridge-hotspot interaction , oceanic transform fault tectonics , and geodynamic numerical modeling , with over 15 publications on oceanic crustal evolution, mantle dynamics, and subduction zone processes. Recent work includes 3D geodynamic simulations of oceanic plateau formation and transform fault morphology. He has participated in Mariana Trench , South China Sea , and Makran Trench scientific expeditions. Scientific Awards: Pengcheng Kongque Plan Specially Appointed Talent (Shenzhen) Key Projects: China Postdoctoral Science Foundation (2022M711480, PI) National Natural Science Foundation of China (42406071, Lead PI) Guangdong Provincial Laboratory Talent Team Project (GML2019ZD0205) Research Trends: Subduction zone seismicity Oceanic plateau formation Ridge-hotspot interaction Transform fault morphology 3D geodynamic modeling Crustal thickness analysis

• Ridge-Hotspot Interaction
• Oceanic Transform Faults Tectonics
• Geodynamics
• +1 more

Xiaoshuai Fan is an Associate Professor at the College of Business, Southern University of Science and Technology, where she has been affiliated since 2020. Her academic background includes a PhD in Industrial Engineering and Logistics Management from HKUST (2020) and a Bachelor's in Management from Huazhong University of Science and Technology (2015). Education: PhD (2020), Industrial Engineering and Logistics Management, Hong Kong University of Science and Technology Bachelor (2015), Management, Huazhong University of Science and Technology (Management Innovation Experimental Class) Her research focuses on Mechanism Design and Auction Theory under asymmetric information, with applications to Behavioral Operations Management , Sustainable Operations (particularly poverty, income inequality, and carbon emissions), and Supply Chain Management . Recent work explores pay transparency in behavioral economics, carbon emission control through price commitments, and anti-corruption strategies in procurement systems. The 15 most recent publications highlight trends in asymmetric information theory , collusion-resistant contract design , and equity-focused operations research . Key journals include Management Science , Production and Operations Management , and Manufacturing & Service Operations Management . She serves as a doctoral supervisor and has secured research funding from the NSFC Outstanding Young Scholars Program , NSFC Youth Program , and the Shenzhen Science and Technology Innovation Commission . Her lab actively recruits research assistants and postdocs, emphasizing interdisciplinary collaboration in economic, mathematical, and computational fields.

• Mechanism Design
• Auction Theory
• Behavioral Operations Management
• +3 more

Xuehai Qian is a Tenured Full Professor in the Department of Computer Science at Tsinghua University since July 2024. Prior to this, he served as an Associate Professor at Purdue University (2022-2024), Assistant Professor at the University of Southern California (2015-2022), and Postdoctoral Researcher at the University of California Berkeley (2013-2015). Ph.D. in Computer Science, University of Illinois at Urbana-Champaign, USA (2013) ME in Computer Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, China (2007) BE in Computer Science and Technology, Beihang University, China (2004) His research focuses on parallel computer architecture , hardware/software co-designed domain-specific architectures for graph analytics and machine learning , hardware security , and quantum computer architecture . He has pioneered scalable cache coherence protocols for atomic block execution, hardware sequential consistency violation detection, and distributed frameworks for graph processing leveraging emerging memory technologies. Xuehai Qian’s publications span computer architecture , graph analytics , machine learning systems , and quantum computing , with a strong emphasis on distributed systems , accelerators , and memory optimization . His work includes novel architectures for graph processing, decentralized training protocols, and ReRAM-based accelerators for deep learning. NSF CAREER Award (2018) ACSIC (American Chinese Scholar In Computing) Rising Star Award (2019) IEEE Senior Member (2019) Hall of Fame inductions: ASPLOS (2018), HPCA (2019), ISCA (2021), MICRO (2021) W.J. Poppelbaum Memorial Award (2013) He has advised students who have received Microsoft Research Lovelace Fellowships , Ph.D. Fellowships , and Facebook Fellowships . His research has been supported by grants such as the NSF SPX project on FPGA-based machine learning platforms and smaller NSF grants. Notably, he has served as an Associate Editor for Science China (Information Sciences) since 2023 and as a Guest Editor for IEEE Transactions on Parallel and Distributed Systems (2019).

• Computer Architecture
• Computer Systems
• Hardware Security
• +3 more

Professor Chen Jianfei is a Chair Professor at the Department of Marine Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China. He previously held academic positions at Queen’s University Belfast (2013-2019), University of Edinburgh (2002-2013), and Zhejiang University (1987-1992). His leadership roles include serving as President of the International Institute for FRP in Construction (IIFC) from 2014 to 2018. PhD in Civil Engineering, University of Edinburgh (1996) MSc in Structural Engineering, Zhejiang University (1987) BEng in Structural Engineering, Zhejiang University (1984) Professor Chen’s research spans civil engineering and mechanics of bulk materials , focusing on: Application of high-performance FRP composites in civil infrastructure Development of advanced discrete/finite element methods for structural analysis Mechanics of granular solids and bulk material flow in silos Seawater sea-sand concrete and high-performance concrete systems Hybrid floating structures and subsea pipelines His publications include the foundational monograph FRP-Strengthened RC Structures (translated into Chinese, Korean, Persian) and over 300 papers. Google Scholar cites exceed 7,664 (Web of Science), with an h-index of 30. His work has been adopted into international standards. Honors include: 2021 IIFC Medal (highest award in FRP composites) 2016 Howard Medal (oldest ICE award, since 1872) 2016 Elsevier Highly Cited Researcher in Civil Engineering 2015 Frederick Palmer Prize (ICE journal best paper) 2006 President’s Award (IIFC) He has secured major grants for projects like Re-use of Wind Turbine Blades (US-Ireland partnership, $1.3m) and FRP Confined Seawater Concrete (NSFC, RMB747,000).

• Civil Engineering
• Mechanics of Loose Materials
• Fiber-Reinforced Polymer (FRP) Applications
• +7 more

Dr. Lili Wang serves as an Associate Professor at Southern University of Science and Technology (SUSTech), joining in May 2024 as an independent Principal Investigator and PhD advisor. Her research focuses on theoretical and applied control systems for intelligent sensor networks through interdisciplinary integration of control theory, optimization, and machine learning. Her academic foundation includes: PhD in Engineering and Applied Science from Yale University (2014-2020) Master's in Control Theory and Control Engineering from Zhejiang University (2011-2014) Bachelor's in Automation from Zhejiang University (2007-2011) Dr. Wang's research spans social dynamics , distributed estimation , distributed control , formation control for multi-agent systems , and distributed learning applications . Her work develops novel algorithms for networked control systems with applications in intelligent sensor networks and multi-robot coordination, emphasizing theoretical rigor and practical implementation. Analysis of her publications reveals consistent advancement in distributed observer design, formation control strategies, and consensus algorithms. Key trends include innovative applications of graph theory and spectral methods to multi-agent systems, with growing integration of learning techniques for adaptive control in uncertain environments. Her distinguished recognition includes: IEEE Senior Member (2024) Lillian Gilbreth Fellowships at Purdue University (2023) CPS Rising Star Award (2023) Henry Prentiss Becton Graduate Prize (2019) Zhang Siying Outstanding Paper Award (2012) As a PhD advisor at SUSTech, Dr. Wang mentors graduate researchers in control theory and its applications. She is currently founding COL-LABORATORY, a dedicated research team advancing control systems for intelligent sensor networks through interdisciplinary collaboration, with ongoing projects in distributed learning frameworks and robust multi-agent coordination.

• Social dynamics
• distributed estimation and calculation
• distributed control
• +2 more

Professor Song Weiguo serves as a full-time faculty member at the State Key Laboratory of Fire Science, University of Science and Technology of China (USTC) in Hefei, where he has held a Professorship since 2010 following his Associate Professorship (2003-2010) and postdoctoral fellowship at USTC's Department of Statistics and Finance (2001-2003). His international research experience includes a Guest Researcher position at the U.S. National Institute of Standards and Technology (NIST) during 2006-2007. His educational foundation comprises a PhD from USTC (2001) and specialized postdoctoral training in statistical finance. Research interests focus on pedestrian evacuation dynamics, fire system criticality, performance-based building fire protection, and remote sensing fire monitoring, with particular emphasis on complex systems modeling of crowd behaviors and fire spread phenomena. Analysis of his 2007-2011 publications reveals a dominant trend in microscopic pedestrian dynamics (60% of works), especially bottleneck flow, counter-flow, and exit selection behaviors, complemented by fire monitoring via remote sensing (22%) and weather-fire interaction modeling (18%). This portfolio demonstrates rigorous integration of experimental validation with computational modeling across fire safety disciplines. His scientific recognition includes: Huaxia Construction Award for Science and Technology (First-class, 2010) Lu Jia Xi Youth Excellence Prize (Chinese Academy of Sciences, 2009) National Liangxi Forestry Science and Technology Progress Award (Second-class, 2007) National Science and Technology Progress Award (Second-class, 2006) Chinese Academy of Sciences President Award Excellence (2001) Professor Song has secured significant research funding as principal investigator for three National Natural Science Foundation projects, three National Key Technologies R&D Program grants, and additional awards from the Ministry of Science and Technology and Ministry of Education. His role as Communication Expert for China's National Natural Science Foundation and reviewer for top journals like IEEE Transactions on Intelligent Transportation Systems reflects his leadership in fire safety science. Current projects likely involve mentoring graduate students through USTC's laboratory infrastructure. He remains actively engaged at USTC's State Key Laboratory of Fire Science, which serves as China's primary hub for interdisciplinary fire research, collaborating with international bodies like the International Association of Fire Safety Science while advancing evacuation modeling and fire monitoring technologies.

• Pedestrian and evacuation dynamics
• Self-organized criticality of fire system
• Performance-based fire protection design of buildings
• +3 more

Jia Kai is a Professor at Tongji University's School of Art and Media, where he has served since 2003 after joining as faculty. Holding a PhD in Communication from East China Normal University, he specializes in documentary film theory and creation with a focus on Chinese cinematic practices and theoretical frameworks. His academic journey includes: Bachelor's degree in Foreign Languages from Northwest University (1994-1998) Master's degree in Art from Beijing Normal University (2000-2003) PhD in Communication from East China Normal University (2005-2009) Research centers on documentary film's theoretical foundations, creative methodologies, and sociocultural impact in China. His work critically examines Robert Flaherty's legacy, conceptual evolution of documentary forms, and the interplay between private and public documentary practices. He investigates how documentary film constructs reality while navigating ethical, aesthetic, and political dimensions within contemporary Chinese society. Publication analysis reveals consistent focus on documentary ontology, historical transformations, and Chinese creative ecology. Recent works explore morphological shifts from private documentaries to personal imagery, while earlier research established foundational frameworks for understanding Flaherty's influence and core documentary concepts. Accolades from the China University Association for Film and Television Education highlight scholarly impact: First Prize for 'Carving the Mental Image' (2014) Excellent Award for 'Re-examination of Basic Concepts' (2019) Third Prize for 'Utopia of Documentary' monograph (2021) Second Prize for 'Walking on Earth' research report (2022) As Master's Supervisor, he mentors graduate students in film theory and production. Research leadership includes principal investigator roles for Ministry of Education's 'Flaherty and Contemporary Chinese Documentary' project and National Philosophy and Social Science Fund's 'Yulin Spring Festival' sub-project under the 'Chinese Festival Imagery' initiative. He collaborates through Tongji's Omnimedia Research Institute and maintains international connections via DAAD Foundation research at Bauhaus University (2006) and NYU Tisch School of the Arts visiting position (2017-2018). His creative practice complements academic work through award-winning documentaries like 'Yesterday's Rhapsody' (FIRST Film Festival Best Documentary, 2016) and 'Wandering Gods' (Amsterdam IDFA 2019 selection).

• Documentary Studies
• Film Theory
• Television Theory