جستجوی استاد راهنمای دانشگاهی

Zhu Yanمشاهده پروفایل

استاد

• Digital Transformation
• Digital Economy
• Industrial Blockchain
• +۴ مورد دیگر

Zhu Yan serves as Professor at Tsinghua University's School of Economics and Management, Department of Management Science and Engineering. He concurrently holds leadership positions as Dean of Tsinghua's Internet Industry Research Institute, Director of the Advanced Information Technology Business Application Laboratory, and Executive Deputy Director of the Medical Management Research Center. Education: Postdoctoral Fellow (1998-2000) and Ph.D. in Nuclear Energy Technology (1994-1998) at Tsinghua University, Bachelor's in Engineering Physics (1989-1994) Professional Experience: Professor (2010-present), Associate Professor (2002-2010), Lecturer (2000-2002); Visiting Scholar at MIT Sloan, CUHK, and Lancelot Institute Professor Zhu's research spans digital transformation , industrial blockchain , and digital production relations , with emphasis on practical applications in healthcare, construction, and finance. His work bridges theoretical frameworks with industry implementation, particularly in China's digital economy evolution. Current projects focus on industrial internet integration and digital finance systems. His 15 most recent publications demonstrate strong interdisciplinary focus, connecting information systems with healthcare analytics (40%), industrial digitalization (35%), and economic policy (25%). The research shows increasing emphasis on AI-driven diagnostic systems and pandemic-responsive economic strategies since 2020. Beijing Philosophy and Social Sciences Excellent Achievement Award (2020) China Petroleum and Chemical Automation Association Science and Technology Progress Award (2010) Multiple Beijing Science and Technology Progress Awards (2001, 2005) Tsinghua University Outstanding Teaching Award (1999) As academic advisor to national initiatives, Professor Zhu leads the China Technology Economics Society's Blockchain Division and serves as Chief Academic Officer for Chengdu University of Information Technology's Blockchain Industry College. His industry partnerships include SAP Global HR Advisory role since 2000 and CCTV Financial Commentary position since 2015. Current research funding focuses on digital infrastructure development through the Industrial Digital Finance Technology Application Laboratory. He directs the Advanced Information Technology Business Application Laboratory, which develops enterprise digital transformation frameworks, and co-leads the Medical Management Research Center's AI diagnostic initiatives. Current projects include national blockchain infrastructure development and pandemic-resilient supply chain systems.

• Computational Design and Fabrication
• Design for Additive Manufacturing
• Adaptive Process Planning
• +۶ مورد دیگر

Dr. Xiong Yi is an Assistant Professor at the School of System Design and Intelligent Manufacturing (SDIM) at Southern University of Science and Technology (SUSTech) in Shenzhen, China. He leads the Computational Design and Fabrication (CoDeFab) research group, focusing on the integration of computational design methods with advanced manufacturing technologies, particularly in the field of additive manufacturing. Dr. Xiong has established himself as a leading researcher in computational design for additive manufacturing, with a strong international research background spanning Europe and Asia. Dr. Xiong's educational journey includes: Doctor of Science (DSc) in Engineering Design and Production from Aalto University, Finland (2012-2016) Master of Science (MSc) in Machine Automation from Tampere University of Technology, Finland (2010-2012) Bachelor of Engineering (BEng) in Mechanical Engineering from Hubei University of Technology, China (2006-2010) Dr. Xiong's research primarily focuses on computational design and fabrication methodologies, with particular emphasis on design for additive manufacturing (DfAM), intelligent manufacturing systems, and smart materials. His work bridges the gap between theoretical design principles and practical manufacturing constraints, developing novel approaches for the production of complex engineered products. He has pioneered research in continuous fiber-reinforced composite additive manufacturing, developing innovative process planning and optimization techniques that enable the production of high-performance structural components. His research in electrothermally controlled origami and 4D printing of smart materials represents cutting-edge work at the intersection of materials science, mechanical engineering, and computational design. Dr. Xiong's recent publications reveal a strong focus on continuous fiber-reinforced composites, with significant contributions to 4D printing, metamaterials, and intelligent process planning. His work integrates computational design with manufacturing constraints, creating novel approaches for topology optimization, toolpath planning, and structural design that consider both performance requirements and manufacturability limitations. The research demonstrates increasing sophistication in materials science applications, particularly in programmable materials and multi-functional structures. Dr. Xiong has received multiple prestigious awards for his research contributions, including: Best Presentation Award at the 24th Chinese Conference on Mechanisms and Machine Science (IFToMM CCMMS2024) Best Presentation Award at the International Conference on Frontiers of Additive Manufacturing Research (RAAM 2024) Best Paper Award at the International Conference on Design for 3D Printing (ICD3DP 2023) PhD Scholarship from Aalto University (2016) Research Travel Grant from the International Association for Vehicle System Dynamics (IAVSD) (2013) National Scholarship from the Ministry of Education (2008) As a dedicated educator and mentor, Dr. Xiong serves as a PhD supervisor at SUSTech and has successfully guided students who have gone on to pursue advanced studies and careers at prestigious institutions including Hong Kong Polytechnic University, Beihang University, DJI Innovations, and Singapore's A*STAR research institute. His research is supported by multiple competitive grants, including key projects from the National Key R&D Program of China, the National Natural Science Foundation of China, and provincial and municipal funding agencies. Dr. Xiong also serves on the editorial board of the Journal of Engineering Design and as a guest editor for Composites Communications, contributing to the advancement of his field through scholarly service. Dr. Xiong leads the CoDeFab research group, which maintains a strong collaborative culture focused on 'design leading manufacturing, manufacturing driving design, and digital-intelligent integration.' The group has developed several advanced manufacturing platforms, including multi-axis continuous fiber-reinforced composite additive manufacturing systems, smart composite additive manufacturing platforms, and multifunctional soft matter open manufacturing platforms. With a focus on practical applications and innovation, the CoDeFab group actively collaborates with industry partners and has established a joint laboratory to bridge academic research with industrial implementation.

Yiguo Xueمشاهده پروفایل

استاد

• Geotechnical Engineering
• Structural Engineering
• Tunnel Engineering
• +۲ مورد دیگر

Yiguo Xue is a Professor and PhD Tutor at the Geotechnical and Structural Engineering Center, School of Civil Engineering, Shandong University. He has contributed extensively to tunnel engineering, subsea infrastructure, and slope stability analysis through advanced prediction models and numerical simulations. Research Interests: New tunnel geological condition prediction technologies Subsea tunnel and underground energy storage systems High slope stability evaluation Engineering exploration methods His recent work focuses on tunnel safety, subsea structural mechanics, and AI-driven hazard prediction models. Publications highlight his expertise in rockburst analysis, water inrush risk, and excavation optimization using machine learning and numerical frameworks. Scientific Awards: Recipient of China's Top 100 Most Influential Domestic Academic Paper Award (2008 paper on tunnel geological hazard forecasting) He has secured multiple national invention patents for tunnel monitoring devices (e.g., vibration sensors, collapse prediction systems) and developed specialized software for displacement prediction and rock classification.

Daohong Qiuمشاهده پروفایل

دانشیار

• Geotechnical Engineering
• Underground Engineering
• Structural Health Monitoring
• +۲ مورد دیگر

Daohong Qiu is an Associate Professor and Master Tutor at the Geotechnical and Structural Engineering Center, School of Civil Engineering, Shandong University. His research focuses on advanced geological prediction in tunnels, surrounding rock stability, structural health monitoring for urban rail transit, and TBM tunneling performance optimization. Position: Associate Professor Affiliation: School of Civil Engineering, Shandong University Email: qiudh@sdu.edu.cn Research Interests: He specializes in geotechnical engineering challenges related to underground construction, including rock burst prediction , disaster control , and machine learning applications in geological modeling. His work emphasizes integrating advanced computational methods like quantum genetic algorithms and RBF neural networks with field data to improve tunnel safety and efficiency. Publication Trends: His recent 2019 studies address subsea tunnel risk assessment , rock burst prediction in underground caverns, and machine learning-driven surrounding rock classification . Earlier works (2014-2015) explore SVM/GA-SVM for geological disaster forecasting, while pre-2010 papers focus on optimization theory and stress field analysis. Patent Contributions: He holds multiple invention patents for geological prediction devices, including three-dimensional geological network modeling , seismic signal detection , and concrete elevation control systems .

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

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

Liang Yongمشاهده پروفایل

دانشیار

• Data-Driven Decision Analytics
• Supply Chain Management
• Disruption Management
• +۵ مورد دیگر

Liang Yong serves as Associate Professor in the Department of Management Science and Engineering at Tsinghua University's School of Economics and Management. Currently maintaining office hours on Thursdays at 10:00 in Room B424 of Lihua Building, he teaches undergraduate, doctoral, and MBA courses including Production and Operations Management, Advanced Operations Research, and Data, Models, and Decision Making. His educational background includes a B.A. in Engineering Physics from Tsinghua University (2005), Master's in Nuclear Engineering from Purdue University (2008), and Ph.D. in Industrial Engineering and Operations Research from UC Berkeley (2013). Prior to academia, he worked as a Quantitative Analyst at Google Inc. (2013-2014). Liang's research focuses on Data-Driven Decision Analytics , Supply Chain Disruption Management , and Mechanism/Contract Design , with particular emphasis on integrating learning algorithms with operations research. His work addresses critical challenges in omnichannel retail, energy systems, and transportation networks. His 11 recent publications in premier journals like Operations Research and Manufacturing & Service Operations Management demonstrate consistent contributions to operations analytics, with notable recognition including the 2019 POMS-JD.com data-driven paper competition winner prize. Winner prize, POMS-JD.com data-driven paper competition (2019) He actively supervises PhD students, both independently and through co-advisement with faculty like Jian Chen and Yongbo Xiao. His research addresses practical industry challenges through collaborations with major technology companies and government entities, with current work focusing on resilient supply chain design and smart energy systems.

• Operations Management
• Global Supply Chain Management
• Sustainable Operations
• +۵ مورد دیگر

Kanglin Chen is an Assistant Professor at the School of Business, Southern University of Science and Technology, since 2021. His research focuses on operations management, particularly in global supply chain management, sustainable operations, and platform operations. He has published in top journals including Management Science and Production and Operations Management . PhD in Operations Management, Hong Kong University of Science and Technology (2017-2021) BSc in Industrial Engineering, South China University of Technology (2012-2016) His research interests span global supply chain management , sustainable operations , platform operations , and game theory applications . His work explores carbon emission control, cross-border e-commerce disruptions, and strategic timing in co-opetitive supply chains. Kanglin's publications reveal trends in digital supply chains , sustainability policy , and platform economics , with methodological foundations in game theory and data-driven optimization . Recent work examines livestream selling, tariff impacts, and consumer preference uncertainty. First Prize, Guangdong Philosophy & Social Sciences Awards (2021, 2024) Second Prize, Higher Education Scientific Research (Humanities) (2024) As a reviewer for 6+ journals, Kanglin actively contributes to academic peer evaluation. His work bridges theoretical modeling and practical implementation in global operations.

• Data-driven decision optimization
• Supply chain management
• Emergency management
• +۵ مورد دیگر

Professor Yu Guodong is a faculty member in the Department of Project Management and Industrial Engineering at Shandong University's School of Management. He holds the title of Qilu Young Scholar and leads an excellent young innovation team. His research focuses on data-driven decision optimization , particularly in small data environments, with applications in supply chain management, emergency response, and industrial systems. He has pioneered methods like Wasserstein distributionally robust optimization and fairness-aware resource allocation frameworks. His work addresses challenges in high-end manufacturing, emergency logistics, and low-probability event scenarios. Yu has published extensively in top-tier journals including Manufacturing & Service Operations Management , Production and Operations Management , and INFORMS Journal on Computing . He has secured 12 national and provincial grants, including key projects from the National Natural Science Foundation of China. Collaborations with industry leaders like Weichai Power and Jereh Petroleum Equipment demonstrate his applied research impact. His team develops computationally efficient algorithms (e.g., Benders decomposition, Branch-and-Benders-cut) to solve complex optimization problems under uncertainty. Notable contributions include integrating inverse optimization with historical data for contract pricing, quantifying fairness-efficiency trade-offs via robust optimization, and designing resilient service networks for emergencies. His research bridges theoretical advancements and practical implementation, enhancing decision-making resilience in data-scarce scenarios.

Wei Chenمشاهده پروفایل

استاد

• Data Visualization
• Visual Analytics
• Biomedical Image Computing
• +۵ مورد دیگر

Wei Chen is a Professor at the State Key Laboratory of CAD&CG, College of Computer Science, Zhejiang University, Hangzhou, China. His academic journey began and ended at Zhejiang University, where he earned both his Bachelor's (1996) and Ph.D. (2002) in Computer Science, followed by a visiting Ph.D. position at the Fraunhofer Institute in Germany (2000-2002) and a visiting scholar role at Purdue University (2006-2008). Research Focus: Visualization, Visual Analytics, Biomedical Image Computing, Big Data Analytics. Academic Leadership: Served on editorial boards of journals like IEEE Transactions on Visualization and Computer Graphics, Journal of Visual Informatics, and as Chair of IEEE Pacific Visualization Symposium. Impact: Over 110 IEEE/ACM Transactions and CCF-A papers, four Chinese textbooks on visualization, and two monographs on big data technology. His recent publications (2023-2024) span domains like visual analytics for health insurance fraud detection, quantum circuit visualization, federated learning visualization, urban mobility modeling, and AI-enhanced cultural heritage preservation. A thematic trend shows integration of deep learning, large language models, and human-in-the-loop systems with visual interfaces. Scientific Awards include the Zhejiang Province Natural Science First Prize (2021, 2017), CCF Technology Invention First Prize (2020), Wu Wenjun Artificial Intelligence Science and Technology Progress First Prize (2023), and multiple Best Paper/Poster recognitions at IEEE VIS and Pacific Visualization conferences. He actively mentors graduate students and leads the Visual Analytics Group , contributing to national and international standards in visualization research. His editorial and organizational roles in top conferences further solidify his influence in shaping the field.

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."

刘潇مشاهده پروفایل

استاد

• 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.

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 .

卫强مشاهده پروفایل

استاد

• Big data analysis
• Information systems
• E-commerce
• +۴ مورد دیگر

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
• +۶ مورد دیگر

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.

• Computational Intelligence
• Evolutionary Multi-objective Optimization
• Evolutionary Machine Learning
• +۵ مورد دیگر

Professor Hisao Ishibuchi is Chair Professor of Computer Science and Engineering at Southern University of Science and Technology (SUSTech) in Shenzhen, China, a role he has held since April 2017. Previously, he spent nearly three decades at Osaka Prefecture University, progressing from Research Associate (1987-1993) to Assistant Professor (1993), Associate Professor (1994-1999), and full Professor (1999-2017). He is an IEEE Fellow , served as Vice-President of the IEEE Computational Intelligence Society (2010-2013) , and is currently President of the Japan Society for Evolutionary Computation (2016-2018) . He is Editor-in-Chief of IEEE Computational Intelligence Magazine (2014-2019) and the Journal of the Japan EC Society (2014-2018). Education: Ph.D. in Engineering, Osaka Prefecture University, 1992 M.S. in Engineering, Kyoto University, 1987 B.S. in Engineering, Kyoto University, 1985 Research Focus: Professor Ishibuchi is internationally recognised as a pioneer of computational intelligence , with seminal contributions to evolutionary multi-objective optimisation , evolutionary machine learning , fuzzy systems , neural networks , and hybrid intelligent systems . He introduced the first multi-objective memetic algorithm and early methods for multi-objective fuzzy rule-based classifier design that balance accuracy and interpretability. Publications & Impact: With over 100 journal papers in top-tier venues such as IEEE Transactions on Evolutionary Computation and nearly 500 conference papers, his work has attracted more than 24 000 Google-Scholar citations and an h-index of 68. His recent articles concentrate on many-objective optimisation, fuzzy machine learning, and transfer learning techniques. Honours & Awards: IEEE Computational Intelligence Society Fuzzy Systems Pioneer Award 2019 IEEE Fellow 2014 JSPS Prize 2007 (Japan’s most prestigious mid-career award) Multiple Best Paper Awards from GECCO, FUZZ-IEEE, SCIS & ISIS, WAC, ACIIDS, HIS-NCEI, and others Teaching & Mentoring: At SUSTech he teaches Advanced Algorithms and Advanced Optimization Algorithms , covering greedy algorithms, hyper-heuristics, memetic algorithms, multi-objective optimisation, and performance assessment. His research group actively recruits post-doctoral fellows and research assistants in evolutionary computation, fuzzy systems, and neural networks. Labs & Teams: He leads the Computational Intelligence Research Group at SUSTech, maintaining active collaboration networks across Asia, Europe, and North America, and supervising several post-doctoral researchers and graduate students working on next-generation intelligent systems.