Program Correctness Professors and Supervisors in Germany | ApplySharif

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استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۴۹۶-۵۱۰ از ۵۳۰ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Björn Fisselerمشاهده پروفایل

پژوهشگر

FernUniversität in HagenGermany

Björn Fisseler serves as a Research Associate in Specialized Media Didactics within the Dean's Office of the Faculty of Psychology at FernUniversität in Hagen, Germany's national distance learning university. His position bridges academic research with institutional leadership in digital accessibility and inclusive education. Dr. Fisseler's research focuses on digital accessibility, universal design for learning, and inclusive educational technology, with particular emphasis on creating accessible learning environments for students with disabilities. His work examines the intersection of technology, disability, and education across multiple dimensions including institutional policies, faculty development, and practical implementation strategies. He has developed frameworks for understanding accessibility challenges in higher education and has contributed significantly to understanding how digital transformation can either enhance or hinder inclusion. His publication portfolio shows a clear trajectory toward increasingly sophisticated analyses of digital accessibility, with recent work exploring the implications of artificial intelligence for inclusive education. The breadth of his research spans theoretical frameworks, empirical studies using methodologies like Q-method, and practical implementation guides for educators. Dr. Fisseler has received recognition through a Google Scholar h-index of 9 and i10-index of 8, reflecting the impact of his work in the field of digital accessibility and inclusive education. His research has been cited across multiple disciplines including education, psychology, rehabilitation technology, and library science. He actively contributes to academic discourse through numerous keynote addresses, invited lectures, and conference presentations at major international venues including CSUN Assistive Technology Conference, EDULEARN, and University:Future Festival. His work bridges academic research with practical implementation, as evidenced by his involvement in developing institutional guidelines like the "Leitfaden zur Digitalen Barrierefreiheit" (Guideline for Digital Accessibility).

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Myra Cohenمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Myra Cohen is a Professor and the Lanh and Oanh Nguyen Chair in Software Engineering in the Department of Computer Science at Iowa State University. Previously, she held the position of Susan J. Rosowski Professor at the University of Nebraska-Lincoln where she was a member of the ESQuaReD software engineering research group. She serves on the ASE Steering Committee and has held leadership roles including general chair of ASE 2015 and program co-chair for ICST 2019 and ESEC/FSE 2020. Dr. Cohen earned her Ph.D. from the University of Auckland, New Zealand, her M.S. from the University of Vermont, and her B.S. from the School of Agriculture and Life Sciences at Cornell University. Her academic journey includes lecturing positions at both the University of Auckland and University of Vermont during her graduate studies. Her research spans several interconnected domains focused on software quality and assurance. A significant portion of her work addresses software testing challenges in highly-configurable systems, where she applies search-based techniques and combinatorial designs to create efficient test suites. More recently, her research has expanded into innovative areas including software testing for biological systems, quantum computing applications, and security testing through genetic improvement techniques. Her work demonstrates a consistent theme of addressing complex verification challenges through creative application of formal methods and automated techniques. Analysis of her recent publications reveals a growing focus on emerging domains including quantum software testing, molecular/biological computing systems, and assurance cases for safety-critical systems. She has increasingly incorporated AI techniques, particularly large language models, into traditional software engineering problems while maintaining her foundational work in configurable systems and metamorphic testing. NSF CAREER award recipient AFOSR Young Investigator Award recipient ACM Distinguished Scientist Recipient of 4 ACM Distinguished Paper awards Dr. Cohen has served as chair and committee member for numerous conferences including ASE, ICSE, ISSTA, ESEC/FSE, and ICST. She has mentored numerous students through the doctoral symposiums and student research competitions at major software engineering conferences. Her research has been supported by significant grants including those from NSF and AFOSR. She leads the LaVA-OPs (Laboratory for Variability-Aware Assurance and Testing of Organic Programs) research group at Iowa State University, which focuses on testing challenges in biological and organic computing systems.

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Johnathon Aurandمشاهده پروفایل

پژوهشگر

Max Planck Institute for Security and PrivacyGermany

Johnathon Aurand is a researcher at The Ohio State University specializing in software engineering, with a focus on static analysis techniques for improving software reliability through automated error detection in unit type systems. His research spans critical areas of modern software development: Static Program Analysis Type Systems and Type Theory Unit Testing Methodologies Error Detection and Prevention Software Verification Program Correctness These interests address fundamental challenges in ensuring computational accuracy, particularly for physical unit consistency in safety-critical applications. At ASE 2022, Aurand introduced SA4U—a practical static analysis tool for unit type error detection—demonstrating a significant shift toward deployable analysis techniques that bridge theoretical type systems with real-world development workflows. This work highlights growing industry-academia convergence in static analysis tools, emphasizing usability and integration into existing software pipelines while targeting preventable errors that cause catastrophic system failures in engineering domains.

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Yuriy Brunمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Yuriy Brun is a Professor at the Manning College of Information & Computer Sciences at the University of Massachusetts Amherst. He leads research in software engineering with a focus on improving the construction of intelligent, self-adapting systems while ensuring fairness and correctness. His research spans several key areas: software fairness, self-adaptive systems, automated program repair, and formal verification. Brun's work has pioneered the field of software fairness, establishing it as a fundamental software engineering concern. His lab, LASER, conducts high-risk, high-impact research aimed at fundamentally improving how engineers build systems. Brun's publications demonstrate a strong focus on automating formal verification and ensuring fairness in machine learning systems. His recent work leverages large language models for proof synthesis and develops techniques for guaranteeing fairness constraints in software systems. His research has shown significant evolution from distributed systems and collaborative development toward formal verification and AI safety. NSF CAREER Award recipient IEEE Fellow Multiple ACM SIGSOFT Distinguished Paper Awards Google Inclusion Research Award recipient Amazon Research Award recipient Microsoft Research Software Engineering Innovation Foundation Award Brun actively mentors students, with current PhD advisees including Zhanna Kaufman, Hadeel Eladawy, and Abhishek Varghese. His former students have gone on to positions at institutions including Oregon State University, University of California San Diego, and Microsoft. He teaches courses including Introduction to Software Engineering and Software Engineering Project Management.

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Wing-Kwong Chanمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Wing-Kwong Chan is an Associate Professor in the Department of Computer Science at City University of Hong Kong. With a background that includes industry experience as a software engineer, Dr. Chan returned to academia and has established himself as a leading researcher in software engineering with a focus on emerging technologies. Dr. Chan received his BEng, MPhil, and PhD all from The University of Hong Kong. His academic journey began with a hardware-oriented Computer Engineering degree before shifting to software engineering for his graduate studies. His research interests center on software engineering, particularly the technical aspects interfacing with machine learning, blockchain, and GPU technologies. He addresses challenges in program analysis and concurrency, with recent work focusing on deep learning model verification and robustness. His publications span top venues including TOSEM, TSE, ICSE, ESEC/FSE, and ASE. Dr. Chan's recent publications demonstrate a strong trend toward integrating software engineering principles with deep learning systems, particularly in verification, testing, and robustness of AI models. His work bridges theoretical software engineering concepts with practical applications in emerging technologies. Best Paper Award from COMPSAC'04 Best Paper Award from COMPSAC'08 Best Paper Award from COMPSAC'10 Best Paper Award from QSIC'11 Best Paper Award from QRS'16 Best Paper Award from ISET'18 CityU President's Award 2017 Dr. Chan has successfully advised numerous PhD and MPhil students, with alumni dating back to 2006. He has secured substantial research funding through multiple Hong Kong Research Grants Council projects, ITF grants, and international collaborations. His current research focuses on patch robustness certification for deep learning models, reflecting his ongoing commitment to advancing software engineering practices for emerging technologies. As Program Leader for the MSc in E-Commerce program from the CS Department, Dr. Chan also contributes significantly to academic administration and curriculum development at City University of Hong Kong.

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Xiang Gaoمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Xiang Gao is a Pre-tenure Associate Professor in the School of Software at Beihang University, China. His research focuses on applying program analysis, test generation, and formal methods to improve software quality through automated bug fixing and program synthesis. He has established significant collaborations with Fujitsu Laboratories of America, Microsoft Research, and other leading institutions in the software engineering field, demonstrating strong industry-academia connections. Dr. Gao received his Bachelor's degree in Computer Science (Elite Class) from Shandong University in 2016, followed by a Ph.D. from the School of Computing at the National University of Singapore, where he also served as a Postdoctoral Fellow until December 2021. His educational background spans both Chinese and Singaporean academic institutions, providing him with a global perspective on software engineering research. His primary research interests span multiple cutting-edge areas of software engineering: Program Analysis techniques for detecting and fixing software bugs with formal methods Software Security vulnerabilities with focus on automated repair methods Automated Program Repair systems that generate high-quality patches without overfitting Program Synthesis for creating transformation rules from examples Software Engineering for Artificial Intelligence (SE4AI) to improve AI model reliability and security Mobile Software Engineering with particular attention to UI testing and automation Deep Learning Security including model protection and obfuscation techniques Dr. Gao's recent publication trajectory shows a strategic evolution toward integrating large language models with traditional software engineering approaches, particularly in test generation and program repair. His work on DNN modularization (NeMo, CNNSpliter, SeaM) represents an innovative approach to enhancing model reusability and security in resource-constrained mobile environments, addressing critical challenges in deploying AI on edge devices. His scientific contributions have been recognized with multiple prestigious awards: ACM SIGSOFT Distinguished Paper Award for "ProveNFix: Temporal Property guided Program Repair" at FSE'24 IEEE TCSE Distinguished Paper Award for "Investigating and Detecting Silent Bugs in PyTorch Programs" at SANER'24 ACM SIGSOFT Distinguished Paper Award for "Modularizing while Training: A New Paradigm for Modularizing DNN Models" at ICSE'24 Distinguished Artifact Award for "Automated Patch Backporting in Linux (Experience Paper)" at ISSTA'21 Dr. Gao actively mentors students at various levels, seeking "self-motivated Ph.D, master, undergraduate students and interns with strong programming skills" for his research projects. He serves on numerous program committees for top software engineering conferences including ICSE, ASE, ISSTA, and FSE, demonstrating his growing influence in the academic community. His research has been supported through collaborations with industry partners including Microsoft Research and Fujitsu Laboratories of America, translating theoretical advances into practical applications. His laboratory focuses on several key research projects including Automated Software Vulnerability Repair (with techniques like Fix2Fit, VulnFix, and ExtractFix that address the overfitting problem in program repair), Program Synthesis for Program Transformation (including Semi-supervised synthesis and FixMorph for automated patch backporting in Linux), and Software Engineering for Artificial Intelligence (with projects like CNNSpliter, SeaM, and Sensei that apply software engineering principles to improve AI model usability and robustness). These projects represent cutting-edge work at the intersection of traditional software engineering and modern AI techniques, addressing critical challenges in software reliability and security.

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Mohammad Hamdaqaمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Mohammad Hamdaqa is an Associate Professor at the Department of Computer Engineering and Software Engineering at Polytechnique Montréal (Canada), where he leads the Software and Emerging Technologies Lab. He received his PhD in Software Engineering from the University of Waterloo in Canada in 2016 and holds multiple advanced degrees including a Master of Applied Science in Software Engineering and an MBA with a minor in Management Information Systems. His educational background includes: Ph.D. in Electrical and Computer Engineering, University of Waterloo, Canada Master in Electrical and Computer Engineering, Concordia University, Canada Master in Business Administration, New York Institute of Technology, USA Bachelor in Computer Engineering, Jordan University of Science and Technology, Jordan Dr. Hamdaqa's research focuses on the intersection of software engineering and emerging technologies. His work explores how software engineering approaches can be tailored to address the complexities of architecting, building, and deploying applications for new platforms like Cloud Computing and Blockchain. He is particularly interested in how emerging technologies can advance software creation, evolution, and management practices. His research spans model-driven software engineering, cloud computing, blockchain, and the application of AI in software development processes. His recent publications demonstrate a strong focus on smart contract security, infrastructure as code, model-driven engineering, and the application of large language models in software engineering tasks. His work bridges theoretical software engineering concepts with practical applications in cutting-edge technology domains, with particular emphasis on addressing security, sustainability, and maintainability challenges in next-generation software systems. Dr. Hamdaqa has received recognition through service on program committees for major software engineering conferences including ASE, ICSE, MODELS, and SANER. He serves on the editorial board of Service Transactions on Internet of Things and is a Member of the IEEE Computer Society and the Association for Computing Machinery. He has supervised multiple Master's students to completion, with recent theses focusing on OCL generation, smart contract auditing, epidemiological modeling, and infrastructure as code security. His current research group continues to explore innovative approaches at the intersection of software engineering and emerging technologies. Dr. Hamdaqa leads the Software and Emerging Technologies Lab at Polytechnique Montréal, which brings together researchers and students to investigate cutting-edge challenges in software engineering for new technology platforms. The lab focuses on practical solutions that balance theoretical rigor with real-world applicability.

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Fuyuki Ishikawaمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Fuyuki Ishikawa is an Associate Professor at the Information Systems Architecture Science Research Division of the National Institute of Informatics (NII) in Tokyo, Japan, where he also serves as Director of the GRACE Center. Additionally, he holds positions as Associate Professor at Sokendai (The Graduate University for Advanced Studies) and Visiting Associate Professor at The University of Electro-Communications. His research program, which he describes as 'Trustworthy & Smart Software Engineering,' focuses on dependability in Cyber-Physical Systems and Machine Learning Systems through techniques of formal methods and automated test generation. He investigates verification, reasoning, optimization, automated test generation, and self-adaptation by utilizing various models for requirements, specifications, and designs. His group promotes international and industry-academia collaborations with members from different organizations. Ishikawa's recent work has increasingly concentrated on quantum program testing, autonomous driving systems verification, and quality assurance frameworks for AI systems. His publications demonstrate significant contributions to software engineering, particularly in applying formal methods to emerging domains like quantum computing and machine learning. His research often bridges theoretical foundations with practical applications in safety-critical contexts, particularly for autonomous systems. Awards for Science and Technology (Research Category) from the Minister of Education, Culture, Sports, Science and Technology (April 2024) IPSJ/IEEE Computer Society Young Researcher Award for 'Research on Intelligence-driven Engineering of Dependable Smart Systems' (March 2020) Multiple Best Paper Awards at conferences including ICFEM 2020, SEKE 2020, ICECCS 2019, and ISSRE 2019 Industry Track Best Artifact Award at ISSTA 2015 Ishikawa actively supervises research projects and interns through the ERATO-MMSD Project and MIRAI-eAI Project. He has served on numerous program committees for major software engineering conferences including ASE, ICSE, and ICST, and has organized workshops on machine learning systems engineering (SIG-MLSE) and quality assurance for AI systems (QA4AI). His laboratory provides two main research directions: generative AI for trustworthy software engineering and testing/trust exploration for AI systems, with specific focus on autonomous driving and deep learning applications.

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Yun Linمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Yun Lin is an Associate Professor and Deputy Head of the Department of Computer Science and Technology at Shanghai Jiao Tong University's School of Computer Science. Prior to joining SJTU, Lin served as a Research Assistant Professor at the National University of Singapore working with Prof. Dong Jin Song. Lin leads the CoPhi ("Code Philia") research group, which focuses on the intersection of Software Engineering, AI, and Security. Lin's research spans three major areas: Automatic Programming (including code editing, software testing, and debugging), Explainable AI (focusing on representation interpretation and training data attribution), and Web Misinformation (particularly phishing and scam detection). The research has resulted in numerous tools including CoEdPilot for code editing recommendation, DeepDebugger for interactive debugging of deep classifiers, and Phishpedia for phishing webpage detection. Lin's recent publications demonstrate a strong trend toward integrating AI techniques, particularly large language models and vision language models, with traditional software engineering and security tasks. The work shows increasing sophistication in understanding project context, handling interactive nature of programming tasks, and addressing security challenges in the age of generative AI. Key themes include consistency-based approaches for anomaly detection, agent-based frameworks for complex tasks, and hybrid models that combine symbolic reasoning with neural approaches. ACM Distinguished Paper Award in ICSE'18 for "Towards Optimal Concolic Testing" Distinguished Reviewer Award in FSE'25 2nd prize Research Prototype Award in ChinaSoft'24 Lin advises a large team of PhD, Master's, and undergraduate students, with several publications co-authored with students appearing in top venues. Current research is supported by collaborations with National University of Singapore, particularly with Prof. Dong Jin Song, and includes projects on code editing, GUI testing, and phishing detection. The CoPhi group maintains active development of multiple research tools and datasets. The CoPhi research group under Lin's leadership focuses on building practical tools that bridge the gap between theoretical advances and real-world programming and security challenges. The group's work spans from fundamental program analysis techniques to applied security solutions, with an increasing emphasis on leveraging AI capabilities while maintaining explainability and reliability.

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Yiling Louمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Yiling Lou is an incoming Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign (starting Spring 2026), currently serving as a Pre-tenure Associate Professor at Fudan University. Previously a Postdoctoral Fellow at Purdue University under Prof. Lin Tan, Dr. Lou holds a Ph.D. and B.S. in Computer Science from Peking University supervised by Prof. Lu Zhang and Prof. Dan Hao. Research interests span Software Engineering synergized with Artificial Intelligence and Programming Languages , specifically focusing on LLM4Code, Agent&SE, Vulnerability Detection, and Software Testing/Debugging. Current projects include AgentIssue-Bench for agent system maintenance and INFERROI for enhancing static analysis with LLMs. Research trends show increasing integration of LLMs with traditional SE techniques, particularly in code generation (ClassEval, CodeGen4Libs), debugging (interactive runtime comparison), and vulnerability detection. Recent work emphasizes practical applications in agent systems and resource leak detection. ACM SIGSOFT Distinguished Paper Award (ESEC/FSE 2023) IEEE TCSE Distinguished Paper Award (ICSME 2021) Advises a large research group including 7 Ph.D. and 8 MS students at Fudan University, actively recruiting for UIUC starting Fall 2026. Leads the LLM4Code workshop series and serves on numerous program committees including ICSE, ASE, and FSE. Currently organizing research on Code Agents, Code LLMs, and AI&Security with strong industry relevance. Coordinates the Siebel School research group at UIUC focusing on the intersection of AI and Software Engineering, with particular emphasis on developing robust agent systems for code maintenance and security applications.

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Christian Lehmannمشاهده پروفایل

استاد

Berlin University of Applied SciencesGermany

Professor Christian Lehmann is a faculty member at HTW Berlin in Department 2: Engineering Sciences - Technology and Life, where he serves as Professor and Laboratory Manager for the Robotics Laboratory. He teaches across multiple programs including Mechanical Engineering (Bachelor's), Computer Science in Engineering (Master's), and Industrial Engineering (Bachelor's). His research focuses on industrial robotics, production automation, and manufacturing technology, with particular emphasis on human-robot collaboration, compliant robotics, and practical implementations in manufacturing environments. Professor Lehmann leads the Robotics Laboratory at Wilhelminenhof Campus, which houses advanced robotic systems including KUKA and Fanuc robots, drone systems, and sophisticated testing equipment for human-robot interaction. Analysis of his publication record shows consistent contributions to industrial robotics, particularly in fault-tolerant programming, compliant robot applications, and manufacturing integration. His work bridges theoretical robotics with practical industrial implementation, with numerous publications appearing in IEEE journals and conference proceedings from 2013-2019. Active supervision of student research projects and theses Management of the Robotics Laboratory with state-of-the-art equipment Multiple ongoing research collaborations with industry partners Development of practical robotics solutions for manufacturing challenges Professor Lehmann's teaching portfolio includes Fundamentals of Robotics, Production Automation, Mechatronics, and Manufacturing Technology courses across multiple engineering programs. His laboratory-based approach provides students with hands-on experience in industrial robotics systems and practical problem-solving in manufacturing environments.

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Heinz Cornelمشاهده پروفایل

استاد

Alice Salomon University of Applied Sciences BerlinGermany

Professor Heinz Cornel is a lecturer at the Center for Continuing Education at ASH Berlin, specializing in social work within criminal justice contexts. His academic degree status is listed as 'external,' indicating a potentially adjunct or visiting role while maintaining primary affiliation elsewhere. His research interests focus on social work in delinquency contexts , juvenile justice systems , offender rehabilitation , and resocialization processes . Professor Cornel advocates for community-based approaches to offender support, particularly emphasizing alternatives to traditional punishment models for young offenders. His publications from 2011 reveal a consistent focus on practical applications of social work principles in criminal justice settings, with particular attention to outpatient support systems, transitional facilities, and youth justice alternatives. These works demonstrate his commitment to developing effective rehabilitation frameworks that prioritize social integration over punitive measures. Professor Cornel's teaching responsibilities for Winter Semester 2025/26 include two specialized courses examining life worlds and intervention methods in social work related to delinquency, reflecting his practical approach to preparing social work professionals for this challenging field.

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Michael Pradelمشاهده پروفایل

استاد

Max Planck Institute for Biology TübingenGermany

Michael Pradel is a full professor in the Computer Science Department at the University of Stuttgart and faculty member at CISPA Helmholtz Center for Information Security (effective September 2025), where he leads the Software Lab. He is also affiliated with the International Max Planck Research School for Intelligent Systems and the Stuttgart ELLIS Unit, reflecting his interdisciplinary research approach. His research interests focus on software engineering, particularly program analysis, bug detection, and the application of machine learning to developer tools. Pradel's recent work increasingly explores LLM-based approaches for program repair, code analysis, and automated software development, as evidenced by projects like RepairAgent and ExecutionAgent. Pradel's publication record shows a clear trend toward integrating AI techniques with traditional software engineering methods, with recent papers focusing on LLM applications for program repair, change validation, and quantum software analysis. His work bridges theoretical foundations with practical tool development, as seen in frameworks like DyLin for Python analysis and LintQ for quantum programs. Ernst-Denert Software Engineering Award Emmy Noether grant (1.3 million Euro) by the DFG ERC Starting Grant (1.5 million Euro) Multiple ACM SIGSOFT Distinguished Paper Awards ACM Distinguished Member recognition Pradel actively mentors PhD students, with recent graduates including Matteo (specializing in quantum software) and Luca (focusing on software evolution). His group has received significant funding and maintains strong industry connections, including past sabbaticals at Facebook. He serves in leadership roles for major conferences, including PC co-chair for FSE 2027, demonstrating his standing in the software engineering community. The Software Lab maintains active collaborations with institutions worldwide, including CMU, Google, KAIST, and several European universities.

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Yang Liمشاهده پروفایل

دانشیار

ESMT BerlinGermany

Yang Li serves as Associate Professor of Marketing and Associate Dean for the MBA Program at Cheung Kong Graduate School of Business (CKGSB). Holding a PhD in Marketing from Columbia Business School alongside dual master's and bachelor's degrees from Columbia and Peking University respectively, he bridges advanced statistical methodologies with practical business applications. His research centers on statistical machine learning and Bayesian nonparametrics applied to consumer behavior analysis, with specialization in online personalization, text mining, and choice modeling. Recent work demonstrates significant focus on fragmented attention economies, ethical AI frameworks, and NFT network dynamics, reflecting contemporary digital market challenges. Management Science Marketing Science Journal of Marketing Research Journal of Consumer Research Harvard Business Review Professor Li's publications reveal evolving expertise from foundational pricing elasticity studies toward cutting-edge AI applications in consumer contexts. His work increasingly integrates generative models and graph neural networks to decode complex consumer collection behaviors and digital ecosystem dynamics. Scientific recognition includes being a Finalist for the 2021 Paul E. Green Best Paper Award. Industry impact is demonstrated through executive education programs and strategic consultancies with Tencent, Haier, and Tmall. As Associate Dean for MBA Programs, he oversees curriculum development while maintaining active corporate governance roles on boards of publicly traded companies across China and Hong Kong, directly applying his research insights to strategic decision-making in digital transformation initiatives.

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Wang Yijiangمشاهده پروفایل

استاد

ESMT BerlinGermany

Wang Yijiang is Professor of Human Resource Management and Economics at Cheung Kong Graduate School of Business (CKGSB) in Shenzhen, with prior appointments at the University of Minnesota's Carlson School of Management. He holds concurrent positions as research fellow at the University of Michigan's William Davidson Institute and senior fellow at Tsinghua University's National Center of Economic Research, while serving as vice president of the Chinese Economists Society of North America. His educational background includes a PhD from Harvard University. Research focuses on Chinese economic transformation, human resource systems, public finance mechanisms, organizational structures, and labor welfare frameworks within transitional economies. Wang's scholarly output reveals consistent thematic evolution from foundational work on township enterprises and ownership structures toward contemporary analyses of AI-driven business transformation, geopolitical economic shifts, and sustainability imperatives. His recent publications demonstrate increasing emphasis on China's global economic integration, technological disruption, and policy responses to anti-globalization pressures. International MBA 10th Anniversary Teaching Award, University of Hong Kong (2008) Selected as 'most influential piece on Chinese economy since reform' for Cambridge Series on Trade and Development McKnight Research Grants (multiple, 1990s) Graduate School Research Grants from University of Minnesota (multiple) Wang actively mentors through CKGSB's Business Scholars Program, EMBA, and Executive Education initiatives, leveraging industry partnerships for applied research. His grant history includes sustained McKnight Foundation support during the 1990s and University of Minnesota research funding, enabling longitudinal studies on China's economic transition. As faculty lead for CKGSB's Unicorn Program Series and Emerging Tech Management initiatives, he coordinates cross-disciplinary teams analyzing AI scalability, fintech innovation, and healthcare transformation across global markets.

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