Find Academic Supervisors

Yin GuoyinView profile

Professor

• Synthetic Chemistry
• Metal Catalysis
• Organic Chemistry
• +3 more

Yin Guoyin is a full-time Professor and doctoral supervisor at the Institute for Advanced Studies, Wuhan University. He serves as a Principal Investigator (PI) in multiple research centers, including the Interdisciplinary Research Center for Chemistry and Life Health and the Photoelectric Nanocatalysis and Industrial Application Research Center. He holds a part-time PI role at the Wuhan University Advanced Light Source Research Center. Education: PhD in Organic Chemistry (2006–2011), Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences Bachelor of Science in Applied Chemistry (2002–2006), Northeast Agricultural University Research Interests: His work focuses on synthetic chemistry and metal catalysis, particularly in the areas of metal migration-driven alkene transformations, catalytic reaction mechanisms, and the design of efficient synthetic pathways. His lab employs physical organic chemistry and computational methods to elucidate reaction mechanisms, with applications in developing novel catalysts and asymmetric synthesis techniques. Key Publications Trends: His recent work emphasizes nickel-catalyzed alkene functionalization, enantioselective boration reactions, and mechanistic studies of transition-metal-mediated transformations. The articles highlight advancements in regio- and stereoselective synthesis, catalyst-controlled divergent pathways, and the application of borylation and arylation strategies for complex molecule construction. Awards: National Natural Science Foundation of China Excellent Youth Fund (2021) Thieme Chemistry Journals Award (2017) Outstanding Doctoral Dissertation of the Chinese Academy of Sciences (2014) Humboldt Scholarship (2011) Advising & Labs: Yin’s group welcomes students and postdocs interested in synthetic chemistry and catalysis. His lab is part of the Wuhan University Advanced Light Source Research Center and collaborates internationally. Undergraduates are invited to join via graduation or innovation projects.

Hu DingView profile

Professor

• Algorithms
• Computational Geometry
• Machine Learning
• +4 more

Hu Ding is a pre-tenure Professor in the School of Computer Science and Engineering at the University of Science and Technology of China (USTC), where he directs the Data Intelligence, Algorithms, and Geometry (DIAG) research group. He previously held positions as a tenure-track Assistant Professor at Michigan State University (2016-2018) and a Simons-Berkeley Research Fellow jointly at Tsinghua University and UC Berkeley (2015-2016). Education: • Ph.D. in Computer Science, State University of New York at Buffalo (2015) • B.S. in Mathematics, Sun Yat-Sen University (2009) Research Interests: Hu Ding's research focuses on developing efficient algorithms for geometric optimization problems with applications in machine learning, big data, and biomedical imaging. His work bridges theoretical computer science (especially computational geometry) with practical challenges in distributed systems, outlier detection, and high-dimensional data analysis. Key areas include constrained clustering, truth discovery in crowdsourced data, and geometric methods for biomedical image analysis. Publication Trends: His recent publications demonstrate a strong focus on scalable algorithms for high-dimensional geometric optimization, particularly in distributed environments with noisy data. A consistent theme is developing theoretically-grounded solutions with practical efficiency, evidenced by work on sublinear-time algorithms, coreset constructions, and approximation frameworks for problems like k-center clustering and SVM optimization with outliers. Awards and Honors: Young Investigator Award, Ministry of Science and Technology (2021) Simons-Berkeley Research Fellowship (2015-2016) CCF Committee Member for Theoretical CS and Big Data (2021) Grants and Projects: USTC Innovation Group Grant: 'Toward Electronic Design Automation: Theories and Algorithms from AI' (2021) MOST Young Investigator Grant: 'Optimal Transportation in Medical Imaging' (3M RMB, 2021) Research Group: Leads the DIAG group with focus on geometric algorithms for data intelligence. Current team includes 6 PhD students and 15 Master's students working on problems in clustering, distributed optimization, and biomedical applications. Former students hold positions at Alibaba, ByteDance, and academic institutions.

Xiao ZHANGView profile

Tutor

• Robotics
• Teleoperation
• Machine Learning
• +3 more

Xiao ZHANG is a Faculty Tutor at the School of Civil Engineering, Shandong University, specializing in advanced robotics, teleoperation systems, and machine learning applications in manufacturing. Their work bridges human-robot interaction, surgical robotics, and materials engineering. Research focuses on improving precision in telemanipulation, optimizing additive manufacturing processes, and developing context-aware robotic systems for healthcare and industrial automation. Key research interests include gaze-based control mechanisms, intent recognition in human-robot collaboration, and AI-driven quality assessment in manufacturing. Xiao ZHANG has extensively explored applications of neural networks and multi-agent systems to enhance robotic dexterity and safety, particularly in scenarios requiring real-time adaptation like laparoscopic surgery and autonomous vehicles. Recent Trends: Recent publications emphasize integrating machine learning with traditional manufacturing processes (e.g., laser additive manufacturing) and advancing human-centric robotics through shared control frameworks. Awards: No specific awards listed, but contributions span over two decades of peer-reviewed work. Grants/Advising: No explicit grants or student advisees mentioned in the provided text. Labs/Teams: Affiliated with robotics and manufacturing research groups at Shandong University, focusing on experimental and computational methods.

Kang DUANView profile

Professor

• Energy-related Geomechanics
• Computational Geomechanics
• Micromechanics of Rock Failure
• +3 more

Kang DUAN is a Professor at the School of Civil Engineering, Shandong University, and a Qilu Young Scholar. His research focuses on energy-related geomechanics, computational modeling of rock behavior, and physical model testing for underground infrastructure. PhD in Geotechnical Engineering, The University of Hong Kong (2016) Master in Geotechnical Engineering, Shandong University (2012) Bachelor in Civil Engineering, Shandong University (2009) His research in energy-related geomechanics examines hydraulic fracturing and underground cavern stability for energy storage. In computational geomechanics , he specializes in Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD) to model rock failure mechanisms. His work on micromechanics of rock failure investigates crack propagation and anisotropic behavior through numerical simulations and experimental testing. The 15 most recent publications showcase his expertise in hydraulic fracturing dynamics, rock creep behavior, and fracture mechanics. Articles from 2019-2020 emphasize numerical modeling of directional drilling instability, multi-joint rock deformation, and stress-induced borehole failure, with applications to energy extraction and underground construction. Outstanding Teaching Assistant Award 2014-2015, The University of Hong Kong Ringo Yu Prize for Best PhD Thesis in Geotechnical Studies 2016, HKIE

Ranhang ZhaoView profile

Professor

• Water resources development, utilization and management
• Wetland hydrology and water ecological environment
• Rain and flood management and disaster prevention and mitigation
• +1 more

Ranhang Zhao is a Professor and PhD supervisor in the Department of Water Conservancy and Hydropower Engineering at Shandong University's School of Civil Engineering. His work focuses on integrated water resources management, wetland hydrology, flood risk reduction, and advanced fuzzy-set methodologies for engineering applications. Research Interests: Water resources development, utilization and management Wetland hydrology and water ecological environment Rain and flood management and disaster prevention and mitigation Engineering Fuzzy Set Theory and Application While no specific publications or awards are listed in the provided text, Professor Zhao’s expertise lies at the intersection of hydraulic engineering, environmental hydrology, and computational intelligence, positioning him as a key contributor to sustainable water systems and disaster-resilient infrastructure.

Ruan YunView profile

Associate Professor

• Ecological water conservancy
• Optimize scheduling
• Numerical Simulation
• +2 more

Ruan Yun is an Associate Professor and Master Tutor at the Department of Water Conservancy and Hydropower Engineering , School of Civil Engineering , Shandong University . His research focuses on ecological water management, reservoir optimization, and flood control. Contact: yunruan@sdu.edu.cn . Academic Rank: Associate Professor Department: Water Conservancy and Hydropower Engineering School: School of Civil Engineering, Shandong University Research Interests: Ruan Yun’s work centers on ecological water conservancy , optimize scheduling , and numerical simulation , with significant contributions to flood control and drought resistance and irrigation and drainage . His research integrates computational methods like NSGA-II and noisy genetic algorithms to solve complex water resource problems. Publications: His recent articles (2008–2011) analyze reservoir operation , dynamic water levels , and stochastic modeling , bridging computational optimization and hydrological systems.

Binglei WangView profile

Associate Professor

• Mechanics of micro/nanostructures
• Electromechanical coupling in dielectrics
• Smart materials and structures
• +4 more

Binglei Wang is an Associate Professor at the Department of Engineering Mechanics, School of Civil Engineering, Shandong University. He holds a Ph.D. in Engineering Mechanics from Shandong University and Columbia University, an MS in Solid Mechanics from Xi'an Jiaotong University, and a BS in Engineering Mechanics from Xi'an Jiaotong University. Ph.D. : Engineering Mechanics, Shandong University/China & Columbia University/USA (2008–2011) MS : Solid Mechanics, Xi'an Jiaotong University/China (2002–2005) BS : Engineering Mechanics, Xi'an Jiaotong University/China (1998–2002) His research spans micro/nanostructural mechanics , engineering simulation optimization (with expertise in ANSYS and ABAQUS software), and solid waste recycling (including intelligent sorting systems and recycling equipment). His work on strain gradient elasticity theory and flexoelectricity has produced groundbreaking models for MEMS/NEMS systems, with applications in energy harvesting from thin sheets and micro/nanoscale beam dynamics. Publications since 2010 include 15+ high-impact papers, notably an ESI Highly Cited Paper. He has presented at major international conferences like ICTAM and SES, and serves as a reviewer for journals such as International Journal of Solids and Structures . He teaches Theoretical Mechanics and Continuum Mechanics , and was a visiting researcher at the University of Houston (2017–2018). Scientific Recognition : ESI Highly Cited Paper Professional Roles : Member of Chinese Society of Mechanics; Expert evaluator for Ministry of Education; Reviewer for Polish Natural Science Foundation

Qianqing ZhangView profile

Professor

• Geotechnical Engineering
• Structural Engineering
• Pile Foundation Analysis
• +3 more

Qianqing Zhang is a Professor at the School of Civil Engineering, Shandong University, affiliated with the Geotechnical and Structural Engineering Center. His work focuses on pile foundation mechanics and geotechnical engineering. Research interests include: Analysis of pile-soil interaction under tension/compression Nonlinear settlement prediction models Stability of cofferdams and underground structures Geotechnical risk assessment for karst tunnels Recent publications emphasize computational methods (e.g., Runge-Kutta, hyperbolic models) for pile response prediction, with applications in marine geotechnics and mining environments. Key trends include progressive deformation mechanisms, arching effects in soils, and numerical validation of field observations. He holds 3 software copyrights for pile foundation analysis tools and 10 first-ranked patents for geotechnical engineering devices, including: Grouting reinforcement systems Deformation monitoring equipment Sliding force measurement devices

Chen GuoqingView profile

Professor

• Business Intelligence
• Big Data Analysis
• E-commerce
• +4 more

Chen Guoqing is a Professor and Senior Professor of Humanities at Tsinghua University's School of Economics and Management, where he serves as Deputy Director of the Academic Committee. He chairs the National Natural Science Foundation of China's Big Data Major Research Program Guidance Expert Group and directs the Ministry of Education's Higher Education Management Science and Engineering Professional Teaching Guidance Committee, with additional roles on national informatization and New Liberal Arts committees. Education: Bachelor's Degree, Renmin University of China (1982) Master's Degree, University of Leuven, Belgium (1988) Doctorate, University of Leuven, Belgium (1992) Research Focus: Professor Chen pioneers research in Business Intelligence and Big Data Analysis, developing frameworks like PAGE for data-driven decision-making. His work spans E-commerce, IT Strategy, and Fuzzy Logic, with recent emphasis on personalized recommendation systems, online consumer behavior, and AI-human collaboration in business contexts. His publications reveal a trajectory from foundational fuzzy logic research to cutting-edge big data applications, consistently bridging technical innovation with managerial relevance. Awards: AIS Fellow (first from mainland China) IFSA Fellow Fudan Management Outstanding Contribution Award Changjiang Scholar Distinguished Professor National Science Fund for Distinguished Young Scholars National Outstanding Doctoral Dissertation Advisor Leadership: As former Executive Vice Dean of Tsinghua SEM and Vice President of IFSA, he has shaped academic policy globally. He leads major NSFC projects and international collaborations while advising government bodies on informatization strategy. His teaching includes national-level courses like "Management Information Systems" and "Management in the Big Data Era."

Liu ChunView profile

Associate Professor

• Capital Markets
• Financial Measurement
• Risk Management

Liu Chun is an Associate Professor in the Department of Finance at Tsinghua University's School of Economics and Management. He holds a PhD from the University of Toronto (2002-2007), a Master's (1999-2001) and Bachelor's (1995-1999) in Economics and Management from Tsinghua University. His research focuses on capital markets, financial measurement, and risk management. Professor Liu teaches courses including Intermediate Financial Theory, Financial Data Analysis, and Financial Practice Classes. His research explores diverse aspects of China's financial system including local government financing, SME credit access, investor behavior, and market microstructure. Recent work analyzes policy impacts using advanced econometric methods like Bayesian latent variable models and survival analysis. His publications predominantly appear in finance and economics journals, with thematic concentrations in: Chinese financial market dynamics Behavioral finance and investor decision-making Policy evaluation and regional development Financial econometrics and statistical modeling Market microstructure and volatility analysis Fintech innovations and digital finance Professor Liu maintains research collaborations across departments and supervises projects on financial infrastructure development. His office is located in Room B310 of Tsinghua University's Lihua Building in Beijing.

刘潇View profile

Professor

• Experimental Economics
• Behavioral Economics
• Computational Economics

刘潇 is a Professor in the Department of Economics at Tsinghua University's School of Economics and Management. She joined Tsinghua in 2012 as an Assistant Professor and advanced through roles including Associate Professor (2016-2021), Tenured Associate Professor (2021-2025), and Professor (2025-). She holds a Bachelor's degree from Renmin University of China (2006) and a PhD from the University of Michigan (2012). Her research focuses on Experimental Economics , Behavioral Economics , and Computational Economics , utilizing field experiments and game theory to analyze human decision-making. Recent work explores AI-driven economic rationality, incentive structures in digital platforms, and behavioral interventions in social policies. Her publications emphasize experimental methodologies applied to diverse contexts like online education, labor incentives, and environmental markets. Trends include increasing integration of computational tools and cross-disciplinary collaboration with computer science. Awards & Honors: Advanced Worker, Tsinghua University (2021) Advanced Worker, Tsinghua SEM (2014, 2020) Outstanding Student Work Award (2020) Outstanding Class Advisor (2017) Advanced Research Work Award (2014) She serves as Associate Editor for Management Science , Journal of Economic Behavior & Organization , and Journal of Behavioral and Experimental Economics , and holds leadership roles in academic committees including the Economic Science Association.

卫强View profile

Professor

• Big data analysis
• Information systems
• E-commerce
• +4 more

Professor Qiang Wei is a faculty member at the Department of Management Science and Engineering, Tsinghua University School of Economics and Management. With a PhD in Management from Tsinghua (1999-2003), he has held academic positions including Department Head and Deputy Secretary of the Party Branch. His research focuses on big data analysis, information systems, e-commerce, business intelligence, data mining, and management simulation. Doctor of Management, Tsinghua School of Economics and Management (1999-2003) Master of Tsinghua School of Economics and Management (1997-1999) Bachelor of Science, Tsinghua School of Economics and Management (1992-1997) His recent research explores big data analysis , online review systems , and personalized recommendation through machine learning and neural network frameworks. Articles span topics including monetary incentives in crowdsourcing , temporal consistency in review ranking , and product relationship discovery via embeddings . He has published in top journals like Management World, INFORMS Journal on Computing, and Information Systems Research. Key awards include: 2021 Ten Best Papers Award, Management World 2020 Ministry of Education Second Prize in Philosophy and Social Sciences 2018 Theory Contribution Award, China Society for Information Economics He teaches courses such as Information Technology and Management , Big Data and Business Analysis , and Data Structure and Algorithm . His work bridges computational methods with business applications, including cybersecurity analysis, mobile technology impact studies, and competitive intelligence systems.

• Operations Research
• Operations Management
• Queuing Theory
• +6 more

Yang Liu is a Tenured Associate Professor in the Department of Management Science and Engineering at Tsinghua University's School of Economics and Management, concurrently serving as an Adjunct Associate Professor at Johns Hopkins School of Public Health since 2018. His academic trajectory includes progression from Assistant Professor (2010-2014) to Associate Professor (2014-present) at Tsinghua, reflecting sustained scholarly impact in operations research and management science. Education: PhD in Decision Sciences, Duke University (2010) MS in High Performance Computing, National University of Singapore (2004) BE in Electronic Information Engineering, Tsinghua University (2003) Professor Liu's research integrates queuing theory, behavioral economics, and data analytics to solve critical problems in digital economies and healthcare systems. His work examines customer behavior in multi-channel retail, live-streaming commerce dynamics, and pandemic resource allocation, emphasizing practical applications of operations management principles. Recent projects focus on algorithmic recommendations in live-streaming platforms and data-sharing value for small businesses on digital marketplaces. His publication pipeline shows strong momentum with four 2024 working papers targeting Management Science, examining live-streaming e-commerce, Cournot competition, and digital platform analytics. This builds on established work in service operations (2023), mobile commerce (2020), and healthcare resource allocation (2009), demonstrating consistent evolution from theoretical foundations to contemporary digital economy challenges. Scientific Awards: Johns Hopkins Teaching Excellence Award (2019) Tsinghua Advanced Worker Award (2013) Duke Doctoral Scholarship (2004-2009) Singapore Government Scholarship (2003-2004) Professor Liu actively mentors graduate students through doctoral seminars and advanced statistics courses while maintaining robust industry collaborations, particularly with Alibaba. His role as Associate Editor for Management Science underscores his academic leadership. Current research focuses on behavioral operations in digital platforms, supported by active working papers under review at top journals, indicating substantial ongoing research activity and funding. Though no dedicated lab is specified, Professor Liu leads research within Tsinghua's Department of Management Science and Engineering, leveraging cross-institutional partnerships with Johns Hopkins and industry players like Alibaba to advance data-driven operations management in rapidly evolving digital ecosystems.

• Physics
• Topological states
• Strongly correlated systems
• +1 more

Weiqiang Chen is a Professor in the Department of Physics at Southern University of Science and Technology (SUSTech) since 2024. He previously served as Associate Professor (2011–2023) and Research Assistant Professor (2008–2011) at SUSTech and The University of Hong Kong, respectively. His research focuses on topological states, strongly correlated systems, and numerical simulations in condensed matter physics. Educational background: Ph.D. in Physics, Institute for Advanced Study, Tsinghua University (2006) B.S. in Physics, Tsinghua University (2000) Key research areas include: Topological states in quantum materials Strongly correlated electron systems Computational methods for correlated systems His work emphasizes theoretical and computational approaches to understanding exotic quantum phenomena in condensed matter systems.

• Surrogate Modeling
• Space Mapping
• Microwave Device Optimization
• +3 more

CHENG Qingsha is an Associate Professor at the Department of Electronic and Electrical Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China. He also holds an Adjunct Professorship at the University of Regina, Canada. With over 26 years of experience, he is a globally recognized expert in surrogate modeling, space mapping, and microwave device optimization. Education: Ph.D. in Electrical and Computer Engineering, McMaster University, Canada (2004) M.Eng. in Automation, Chongqing University, China (1998) B.Eng. in Automation, Chongqing University, China (1995) Research Interests: Dr. Cheng's research spans a wide range of topics in electromagnetic engineering and computational design. His primary focus includes surrogate modeling , space mapping optimization , rapid prototyping , and 3D printing for microwave and antenna applications. He has made foundational contributions to the Space Mapping algorithm , which has become a cornerstone in microwave CAD. His work also extends to AI-assisted optimization , metasurface antennas , millimeter-wave systems , and electromagnetic compatibility . Scientific Awards & Honors: IEEE Senior Member Member of Professional Engineers Ontario Associate Editor, International Journal of Numerical Modelling: Electronic Networks, Devices and Fields Co-organizer and Chair of multiple IEEE workshops and symposiums Teaching & Mentorship: Dr. Cheng has taught a broad range of courses including Signals and Systems , Advanced Microwave Engineering , Antenna Theory and Techniques , and Engineering Ethics . He has supervised over 30 graduate students and postdocs, many of whom have co-supervised with international collaborators from HKUST, NUS, CityU, University of Birmingham, and University of Regina. Lab & Team: He leads the Cheng Lab at SUSTech, which focuses on surrogate-based modeling and optimization for microwave and antenna systems. The lab is actively recruiting postdocs, PhD students, and research engineers.