جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Data Mining
• Machine Learning
• +۴ مورد دیگر

Wang Can is a Professor and Doctoral Supervisor at Zhejiang University's School of Computer Science and Technology, with research focusing on artificial intelligence, data mining, and large-scale graph intelligence algorithms. His work bridges theoretical innovation and practical applications in critical domains. His research interests span Artificial Intelligence , Data Mining , Machine Learning , and Large-Scale Graph Intelligence Algorithms , with significant contributions to intelligent barrier-free technology, financial risk systems, and big data analytics. His methodologies emphasize scalable algorithm design for real-world industrial applications. Notable scientific awards include: Best Paper Award at AAAI 2012 (landmark achievement for Chinese scholars) Best Paper Award at WSDM 2025 Triple First Prizes in Zhejiang Science and Technology Awards (2011, 2018, 2019) National and Provincial Teaching Achievement Awards (2014) As an educator, he led Zhejiang University's ACM International Collegiate Programming Contest team to World Finals victories in 2009 (Stockholm silver) and 2011 (Orlando gold), establishing 21 consecutive years of World Finals qualifications through 2024. He served as Zhejiang Provincial Special Representative for the China Computer Federation (2021-2022), organizing algorithm competitions nationwide. His research leadership includes over 20 projects: National Natural Science Foundation general/joint projects, Zhejiang Provincial Key Projects, National Science and Technology Support Program sub-projects, and international corporate collaborations. He holds more than 20 authorized invention patents.

Andrew Chi-Chih Yaoمشاهده پروفایل

استاد

• Algorithms
• Cryptography
• Quantum Computing
• +۳ مورد دیگر

Andrew Chi-Chih Yao is a distinguished Professor and Dean at Tsinghua University, leading the College of AI and the Institute for Interdisciplinary Information Sciences. He holds dual roles as Professor at Tsinghua's Center for Advanced Study and Distinguished Professor-At-Large at The Chinese University of Hong Kong. His academic journey includes professorships at MIT, Stanford, UC Berkeley, and Princeton University (1986–2004). Education: Ph.D. in Physics (Harvard, 1972) and Ph.D. in Computer Science (University of Illinois, 1975). Research focuses on Algorithms, Cryptography, Quantum Computing, and Artificial Intelligence. He pioneered foundational work in communication complexity, secure computation protocols, and quantum circuit theory. His contributions to computational theory include Yao’s minimax principle and the millionaires’ problem framework for privacy-preserving computation. Recent publications address AI safety, quantum replication, and secure systems for global challenges like DNA synthesis and emissions trading. His 2024 work on AI risk management underscores ongoing engagement with cutting-edge tech ethics. Awards: Kyoto Prize (2021), Turing Award (2000), Pólya Prize (1987), and over 20 honorary doctorates. Grants/Advisory Roles: Key contributor to interdisciplinary initiatives at Tsinghua, including AI and blockchain research. Advised projects on secure computing and cryptographic protocols. Labs/Teams: Leads teams in quantum computing, AI ethics, and secure multiparty computation at Tsinghua.

• Finance Theory
• Financial Engineering
• Corporate Finance
• +۵ مورد دیگر

Dr. Zhaojun Yang is an Associate Professor of Finance at the Department of Finance, Southern University of Science and Technology (SUSTech) since April 2016. Prior, he held a full professorship at Hunan University (Project 985/211) from 2002. His research focuses on finance theory, financial engineering, and applications of machine learning in finance. He leads a National Natural Science Foundation of China Key Program (2.52 million RMB) on blockchain-based asset securitization. He has visiting scholar experiences at the University of Leeds (2005-2006), Columbia Business School (2010, 2014), and University of Macau (2015). He serves on editorial boards of Journal of International Money and Finance , Cogent Economics and Finance , and Finance (in Chinese) . Key awards include Shenzhen High-Level Talent recognition and Nanshan District honors. He has published over 190 papers in top journals like Journal of Risk and Insurance and Journal of Corporate Finance . His grants include a NSFC Key Program on fintech applications. Office hours are Thursdays 9-11 AM at Room 511, SUSTech Business School.

YUE MEIمشاهده پروفایل

دانشیار

• Computational Mechanics
• Biomedical Engineering
• Advanced Intelligent Materials
• +۳ مورد دیگر

YUE MEI is an Associate Professor at Dalian University of Technology's School of Mechanics and Aeronautics. He holds a doctoral degree in Mechanical Engineering from Texas A&M University and has postdoctoral experience at Swansea University (UK) and Saint-Etienne Mines (France). His research focuses on computational mechanics, biomedical applications, and CAE software development, particularly addressing national needs in industrial software autonomy. He leads major national projects including National Key R&D Programs and National Natural Science Foundation grants. Awards include the Liaoning Provincial Talent Aggregation Plan and Dalian High-level Talents designation. His work spans mechanical inversion methods, multi-physics finite element analysis, and structural nondestructive testing. Education: PhD in Mechanical Engineering, Texas A&M University (2013-2017) MSc in Solid Mechanics, South China University of Technology (2010-2013) BSc in Engineering Mechanics, China University of Petroleum (2006-2010) Research Interests: Integrating computational mechanics with biomedical and advanced materials fields. Key areas include: Mechanical inversion techniques for medical/industrial applications Multiphysics finite element methods (fluid-structure, electromagnetics) Development of autonomous CAE software tools Grants & Projects: Leads 7+ ongoing projects including 'Jointly Driven Cross-Scale Mechanical Analysis' (Liaoning Provincial) and 'General CAE Implicit Solver Engine' (National Key R&D). Recent papers focus on topology optimization in biomechanics, soft tissue characterization, and energy harvesting.

Hu Dingمشاهده پروفایل

استاد

• Algorithms
• Computational Geometry
• Machine Learning
• +۴ مورد دیگر

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 ZHANGمشاهده پروفایل

مربی

• Robotics
• Teleoperation
• Machine Learning
• +۳ مورد دیگر

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.

Chen Guoqingمشاهده پروفایل

استاد

• Business Intelligence
• Big Data Analysis
• E-commerce
• +۴ مورد دیگر

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."

陆瑶مشاهده پروفایل

استاد

• Corporate finance
• Investment
• Financing
• +۵ مورد دیگر

Lu Yao serves as a Professor of Finance at the School of Economics and Management, Tsinghua University, where she also directs the China Financial Research Center. She has been selected for the National High-level Talent Program, reflecting her significant contributions to finance research in China. Ph.D. in Business Economics from the Ross School of Business at the University of Michigan--Ann Arbor Master's degree in statistics-financial engineering from the Stern School of Business at New York University Bachelor's degree in economics from the Central University of Finance and Economics Professor Lu's research spans multiple dimensions of finance and corporate governance. Her work focuses on corporate finance, investment, financing, mergers and acquisitions, corporate governance, labor economics and finance, finance and law, and capital market development and internationalization . Her interdisciplinary approach bridges traditional finance with labor economics and legal frameworks, offering novel insights into how corporate decisions impact employees and broader economic systems. Recent research increasingly incorporates digital technology analysis and machine learning methodologies to examine corporate behavior and market dynamics. Professor Lu teaches advanced courses including Mergers and Acquisitions (EMBA/MBA) , Corporate Governance (EMBA/MBA) , Corporate Finance (MBA) , Corporate Valuation (MBA/Master of Finance) , and Introduction to Writing Methods for Economics and Management Dissertations . Her recent publications demonstrate a strong trend toward analyzing the intersection of finance with technology, labor markets, and institutional reforms in China, with particular attention to state-owned enterprise reforms and digital transformation. National Natural Science Foundation Excellent Young Scientist Fund Tsinghua University Academic Newcomer Award Professor Lu has secured substantial research funding through numerous prestigious projects, including the National Natural Science Foundation Excellent Young Scientist Fund, Ministry of Finance research projects, People's Bank of China commissions, and major Tsinghua University initiatives. She leads multiple research teams focusing on China's financial system transformation, state-owned enterprise reforms, capital market development, and the impact of digital technologies on corporate finance. Her current work includes the "Dual High" Plan Innovation Direction Construction Special Project on China's Technology Financial Development Path and research on digital finance applications in cutting-edge fields.

Mao Xiaojieمشاهده پروفایل

دانشیار

• Causal inference
• Data-driven optimization decision-making
• Machine Learning
• +۳ مورد دیگر

Mao Xiaojie is an Associate Professor at the Department of Management Science and Engineering, Tsinghua University's School of Economics and Management . Holding a PhD in Statistics and Data Science from Cornell University (2021) and a bachelor's in Mathematical Economics and Finance from Wuhan University (2016), Mao specializes in causal inference and data-driven optimization decision-making . PhD: Cornell University (2016-2021) Bachelor: Wuhan University (2012-2016) Mao's research bridges machine learning , statistics , and operations research to address challenges in contextual optimization, algorithmic fairness, and robust causal inference. Recent work focuses on data combination , surrogate variables , and minimax methods for handling unobserved confounding and limited outcome data. Key trends in Mao's publications include: Advancing bandit algorithms for efficient contextual decision-making Developing debiased machine learning frameworks for quantile treatment effects Designing robust optimization models under noisy and incomplete covariates Scientific recognition includes: Applied Probability Society Best Student Paper Competition Finalist (2020) Multiple teaching excellence awards at Tsinghua University (2022-2024) Research grants from the National Natural Science Foundation of China Mao currently teaches Empirical Methods in Management Science (PhD), Data Analysis: Inference and Decision Making (Master), and Probability Theory and Mathematical Statistics (Undergraduate). Research collaborations span institutions like Cornell and MIT, with publications in top venues including NeurIPS , ICML , and Operations Research .

Zhang Jiayinمشاهده پروفایل

دانشیار

• organizational theory
• organizational behavior
• human-artificial intelligence relationship
• +۵ مورد دیگر

Zhang Jiayin is a Tenured Associate Professor at the Department of Leadership and Organizational Management , School of Economics and Management , Tsinghua University , where he has been since 2019.12. Previously, he served as an Assistant Professor at the same department from 2014.7 to 2019.12. He also directs the Interactive Technology Industry Research Center at Tsinghua University. PhD in Management, MIT Sloan School of Management (2014) Master of Management Research, MIT Sloan (2013) Master of Laws, Department of Sociology, Tsinghua University (2008) Bachelor of Engineering, School of Information Science and Technology, Tsinghua University (2005) His research focuses on organizational theory , organizational behavior , human-technology interaction (particularly with big data, AI, and machine learning), business ethics , innovative and entrepreneurial leadership , and the sustainable development of high-tech enterprises. He adopts an interdisciplinary approach to study the social value and governance of platform enterprises, with publications in American Journal of Sociology , Social Forces , and Information Systems Research . His teaching includes courses such as "Management (Introduction to Business)", "Organizational Behavior", "Management Research Methods", "International Innovation and Entrepreneurship Practices", and "The Establishment and Growth of Technology Enterprises". The latter was selected for Tsinghua University's Global Open Courses in 2021, attracting over 260,000 views via livestream. Scientific Awards : 2021 Second Prize for Outstanding Paper in the First Rongzhi Corporate Social Responsibility Academic Award 2021 Outstanding Papers of the 16th Annual Conference of Chinese Academy of Management 2021 Tsinghua University Student Social Practice Bronze Award (Team Instructor) 2021 Tsinghua SEM Social Practice Gold Award (Team Instructor) 2020 Tsinghua SEM Student Work Second Prize 2020 Tsinghua "Challenge Cup" Student Works Competition Third Prize Instructor 2020 Honorary Title for Outstanding Online Teaching 2019 Tsinghua SEM Student Work Second Prize 2019 Tsinghua SEM Social Practice Silver Award (Team Instructor) 2019 Tsinghua "Challenge Cup" Outstanding Instructor 2017 Nominated for Academy of Management OCIS Best Paper Award 2015 Clifford Geertz Best Paper Award of the American Sociological Association (second place) He actively bridges academic research and industry practice, establishing collaborative mechanisms between academic teams and leading enterprises to drive industry-university-research synergies. His applied research appears in journals like Economic Observer and Tsinghua Management Review , with some excerpted in Xinhua Digest for their societal impact.

• Geophysics
• Seismology
• Full-Waveform Inversion
• +۵ مورد دیگر

Bao Xueyang is an Assistant Professor at the Department of Earth and Space Sciences (Faculty of Science) of Southern University of Science and Technology (SUSTech) , where he has worked since January 2019. His academic background includes a Ph.D. in Geology from the University of Missouri-Columbia (2011) , M.S. and B.S. degrees in Geophysics from the University of Science and Technology of China . Ph.D., Geological Sciences, University of Missouri-Columbia (2011) M.S., Earth and Space Sciences, University of Science and Technology of China (2005) B.S., Earth and Space Sciences, University of Science and Technology of China (2001) His research focuses on seismological full-waveform inversion , seismic wave attenuation measurement , and geophysical studies of tectonically active regions such as the Tibetan Plateau and Tethys domain. Methodologically, he develops techniques for: 3D full-waveform inversion Joint seismic-gravity inversion Seismic wave attenuation anisotropy Background noise tomography Wavefield simulation on complex topographies Seismic source parameter inversion Analysis of his recent publications reveals expertise in full-waveform sensitivity kernel development , ocean-bottom seismology , and cratonic lithosphere thermal structure through Rayleigh wave attenuation studies. His work spans both theoretical advancements in inversion algorithms and practical applications in energy resource characterization and tectonic studies. Scientific recognition includes: 2019 Shenzhen Overseas High-Level Talent 2022 Excellence Awards in Reviews of Geophysics and Planetary Physics He leads multiple National Natural Science Foundation projects while co-leading international research initiatives. His teaching portfolio includes undergraduate and graduate courses on geophysical inversion theory, covering both linear and nonlinear inversion methods with machine learning applications.

• Surrogate Modeling
• Space Mapping
• Microwave Device Optimization
• +۳ مورد دیگر

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.

• Groundwater Pollution
• Environmental Science
• Hydrology
• +۳ مورد دیگر

Zhilin Guo is an Associate Professor at the School of Environmental Science and Engineering of the Southern University of Science and Technology (SUSTech), Shenzhen. She earned her Ph.D. in Environmental Science (minor in Hydrology) from the University of Arizona and completed postdoctoral work at UC Davis. Research Leadership : Vice Chair of UNESCO Groundwater Youth Network, member of AGU and IAHR committees, and associate editor for top journals like Water Resources Research . Research Focus : Groundwater pollution mechanisms, non-Fickian transport modeling, contamination risk assessment, and sustainability under global change. Her work spans numerical simulation, upscaling methods, and reactive transport analysis. Scientific Awards : 2024 Ministry of Education Young Talents, 2024 Guangdong Environmental Science Society Gold Award, and multiple journal-specific honors. Her funded projects include national Key R&D programs and NSFC grants, totaling over 10 million RMB. Academic Contributions : Published 15+ papers in 2024 alone, covering groundwater modeling, pollution risk, and climate-water interactions. Her teaching includes bilingual courses on water resources and contaminant transport.

• Eco-hydrological modeling
• Water environmental simulation
• Numerical simulation of hydrological processes
• +۴ مورد دیگر

Dr. Han Feng is a Research Associate Professor at the School of Environmental Science and Engineering, Southern University of Science and Technology, collaborating with Professor Yi Zheng. He has been with the institution since 2015, progressing from Post-doctoral Research Fellow (2015-2018) to Research Assistant Professor (2018-2021), and currently holds his present position since 2021. His educational background includes a Ph.D. in Mechanics (Energy and Resources Engineering) from Peking University (2008-2015) and a Bachelor's degree in Theoretical and Applied Mechanics from the same institution (2004-2008). Dr. Han specializes in eco-hydrological and water environmental simulation, with research focusing on numerical simulation of hydrological processes, ecological processes, and water quality processes at watershed scale . His work encompasses development of new computational models, exploration of efficient model-data fusion methods, and investigation into coupling paradigms of deep learning and process-based models. His expertise spans eco-hydrological modeling, non-point source pollution simulation, data assimilation, uncertainty analysis, and machine learning applications in environmental systems. His publication record demonstrates significant contributions to the field, with over 40 papers including 38 SCI-indexed articles in top journals such as Water Research, Water Resources Research, and Journal of Hydrology. His recent work shows a clear trend toward integrating artificial intelligence with traditional hydrological modeling, particularly in applying physics-encoded deep learning to distributed hydrological modeling and using Bayesian approaches for assimilating sensor data in water quality modeling. National Natural Science Foundation of China青年科学基金 project (41807164) as PI (2019-2021) NSFC-CONICYT International Cooperation project (5191101522) as main participant (2020-2024) Chinese Academy of Sciences Strategic Priority Research Program (XDA20100104) as main participant (2018-2023) Shenzhen Municipal Engineering Lab of Environmental IoT Technologies as key member (2018-2020) China Postdoctoral Science Foundation project (2017M612505) as PI (2017-2018) As one of the main developers of the three-dimensional distributed eco-hydrological model HEIFLOW (Hydrological-Ecological Integrated watershed-scale FLOW), Dr. Han's research has been applied across diverse geographical contexts including the Heihe River Basin, Pearl River Basin, Luanhe River Basin, Miho Basin (South Korea), Skjern Basin (Denmark), and San Joaquin Basin (United States).

• Healthcare management and operations
• Operations management
• Digital platforms
• +۴ مورد دیگر

Hao Shuai serves as Assistant Professor at the School of Business, Southern University of Science and Technology (SUSTech), where he has been teaching since 2023. His research bridges operations management with practical applications in healthcare, technology, and business systems. His educational background includes: PhD in Operations Management, University of Illinois at Urbana-Champaign (2017-2023) Bachelor of Applied Physics, University of Science and Technology of China (2013-2017) Dr. Hao's research program focuses on empirical investigations in healthcare operations management, examining how digital platforms transform service delivery systems. His work extends to financial technology applications and human-computer interaction within business contexts, employing advanced methodologies including causal inference and machine learning. This interdisciplinary approach combines his physics background with business analytics expertise. As a new faculty member at SUSTech, Dr. Hao contributes to the university's mission of innovation in Shenzhen's dynamic economic environment. His research addresses contemporary challenges in service operations where technology intersects with human behavior and organizational efficiency.