Find Academic Supervisors

• Deontic Logic
• Artificial Intelligence
• Cognitive Robotics
• +4 more

Prof. Leon van der Torre is a full professor of computer science at the University of Luxembourg, affiliated with the Lab for Intelligent and Adaptive Systems (ILIAS). He specializes in formal models of reasoning and interaction in intelligent systems, with research spanning deontic logic, argumentation theory, cognitive robotics, and compliance technologies. He was granted the Bao Yugang Chair Professorship at Zhejiang University (2023) and has held visiting positions, including at Stanford University's CSLI (2013). His research focuses on integrating logical formalisms with computational systems to address normative reasoning, multiagent coordination, and ethical AI. Key contributions include work on argumentation frameworks, deontic logic applications, and formal models of normative systems. He teaches courses such as 'Introduction to Intelligent Systems' and 'Game Theory', reflecting his expertise in AI and computational reasoning. Prof. van der Torre actively participates in international conferences (e.g., DEON, PRIMA) and has authored over 400 publications. His work bridges theoretical foundations with practical applications, addressing challenges in AI ethics, legal reasoning, and multiagent systems coordination.

Kaj StorbackaView profile

Professor

• Market Shaping
• Service-Dominant Logic
• Value Co-Creation
• +5 more

Kaj Storbacka is a Professor of Marketing at the Hanken School of Economics in Helsinki, Finland. He holds a PhD in Marketing from the same institution. His research focuses on market shaping strategies, value co-creation in service ecosystems, and the evolution of business markets in the digital age. He is actively involved in interdisciplinary research collaborations, particularly with colleagues in the HUMLOG Institute and Marketing departments at Hanken. Storbacka's work emphasizes systemic innovation and the role of managerial agency in transforming markets. His recent studies address topics such as digital sales automation, cultural market dynamics, and sustainable market systems. He has published extensively in leading journals and contributed to over 100 peer-reviewed articles since 1994, with a notable h-index of 30. Education: PhD in Marketing (Hanken School of Economics) Affiliations: HUMLOG - Humanitarian Logistics Institute, Marketing Department Research Interests: Market innovation, service-dominant logic, strategic account management His research has explored the dark side of market shaping, institutional work in ecosystems, and the transition from product-based to solution-oriented business models. Collaborative theorizing with practitioners is a hallmark of his work, bridging academic rigor and practical relevance.

Andy TolmieView profile

Professor

• Educational Neuroscience
• Developmental Psychology
• Cognitive Skills in Science Learning
• +5 more

Professor Andy Tolmie is Chair of Psychology and Human Development at University College London's Institute of Education (IOE). He leads the Centre for Educational Neuroscience, a tri-institutional partnership with Birkbeck and UCL's Institute of Cognitive Neuroscience. His roles include Deputy Director of this Centre and Programme Leader for the Educational Neuroscience MSc. He also oversees the Bloomsbury and UCL ESRC Doctoral Training Centres, instrumental in social science doctoral training across multiple universities. His research focuses on cognitive development, particularly in science learning, executive function, and child pedestrian safety. Key projects include the EEF/Wellcome Trust initiative on executive function in STEM education and interventions to improve group work efficacy in primary classrooms. He has developed behavioral training programs for child pedestrians adopted nationwide. Dr. Tolmie's academic leadership spans editorship of the British Journal of Educational Psychology and roles in the British Psychological Society. His work bridges developmental psychology with educational practice, emphasizing evidence-based strategies for teaching science and fostering critical thinking skills.

Kirsten WinterView profile

Professor

• Formal Verification
• Concurrent Programming
• Computer Security
• +3 more

Dr. Kirsten Winter is an Honorary Senior Fellow at the University of Queensland's School of Electrical Engineering and Computer Science. Her research focuses on formal verification, concurrent programming, and weak memory models. She has contributed significantly to areas such as model checking, railway interlocking systems, and behavior trees. Her work spans theoretical foundations (e.g., linearizability, concurrency semantics) and practical applications in security and embedded systems. Recent projects include the Program Analysis Cell and BASIL: Boogie Analysis for Secure Information-Flow Logics. Winter has collaborated extensively with researchers like Graeme Smith and Robert Colvin. Her most recent publications address speculative execution vulnerabilities and compositional reasoning in weak memory architectures.

• Distributed Systems
• Cryptography
• Electronic Voting
• +3 more

Michael J. Fischer is a Professor of Computer Science at Yale University, renowned for foundational contributions to distributed systems theory, cryptography, and parallel algorithms. His work includes the seminal impossibility result for distributed consensus with faulty processes and the development of the parallel prefix algorithm fundamental to modern parallel computing. His educational background: B.S. in Mathematics, University of Michigan (1963) M.A. in Applied Mathematics, Harvard University (1965) Ph.D. in Applied Mathematics, Harvard University (1968) Fischer's research spans theoretical and applied computer science with emphasis on distributed systems (consensus protocols, fault tolerance), cryptography (information-theoretic security, card-based protocols), and electronic voting systems . His work bridges abstract theory with practical security applications, particularly in trust modeling for e-commerce. Current investigations focus on algorithmic approaches to establishing trust relationships in distributed environments. His publication trajectory reveals evolving expertise from early parallel algorithms (1970-80s) to distributed consensus breakthroughs (mid-1980s), then cryptographic protocols and secure e-voting systems (1985-2000s), with recent work synthesizing these domains through trust frameworks. Key thematic threads include fault tolerance in unreliable networks and verifiable security mechanisms. Scientific recognition: ACM Fellow Fischer has held significant leadership roles including Editor-in-Chief of the Journal of the ACM , chair of the Max-Planck-Institute for Computer Science International Scientific Advisory Board, and founding member of the Computing Research Association's subcommittee on Women in Computer Science. His advisory work extends to the National Science Foundation and Wuhan University's State Key Laboratory on Software Engineering. Outside academia, he actively participates in the Yale Figure Skating Club, having served multiple terms as president. He maintains international collaborations as Guest Professor at Wuhan University and through editorial roles including Acta Informatica , while continuing to teach core computer science courses from data structures to cryptography at Yale.

Fabrizio RiguzziView profile

Professor

• Logic Programming
• Statistical Relational Artificial Intelligence
• Probabilistic Logic Programming
• +3 more

Fabrizio Riguzzi is a Full Professor at the Department of Mathematics and Computer Science of the University of Ferrara, Italy. His academic career spans over two decades at the same institution, having served as Associate Professor (2014-2020) and Assistant Professor/Ricercatore (1999-2014). He is an active researcher in the fields of Logic Programming and Statistical Relational Artificial Intelligence with numerous publications and leadership roles in international conferences. His educational background includes: PhD in Electronic and Computer Engineering from the University of Bologna (1999) Laurea in Computer Engineering from the University of Bologna (1995) Riguzzi's research focuses on probabilistic approaches to artificial intelligence, particularly probabilistic logic programming and statistical relational AI. His work bridges symbolic reasoning with probabilistic methods, developing frameworks for uncertain knowledge representation and reasoning. He has made significant contributions to probabilistic answer set programming, neuro-symbolic integration, and applications in areas like network intrusion detection and knowledge graph completion. His research demonstrates how logical formalisms can be enhanced with probabilistic reasoning to tackle real-world problems with uncertainty. An analysis of his recent publications reveals a strong trend toward integrating neural and symbolic approaches in AI, with significant work on probabilistic answer set programming frameworks. His research spans theoretical foundations of probabilistic logic programming, practical implementations, and applications in cybersecurity, knowledge graphs, and decision-making under uncertainty. The interdisciplinary nature of his work connects computer science theory with practical AI applications. His notable awards include: Alain Colmerauer 10-Year Test-of-Time Award at ICLP 2021 Best Paper Award for "BUNDLE: A Reasoner for Probabilistic Ontologies" at RR-2013 Highly Commended Paper Award for "Probabilistic declarative process mining" at KSEM 2010 Riguzzi has supervised several PhD students to completion, including Elena Bellodi, Riccardo Zese, and Giuseppe Cota, who have gone on to win prestigious awards for their theses. He has served in numerous editorial roles, including Associate Editor of the Journal of Artificial Intelligence Research and Editor in Chief of Intelligenza Artificiale. His leadership extends to organizing major conferences like ILP 2018 and serving on program committees for top AI venues including IJCAI, AAAI, and ECAI. He is a member of the ML@unife research group and has developed several online systems including cplint, TRILL, and an Online AUC calculator. His work has fostered collaborations across the AI research community, particularly in the areas of probabilistic logic programming and neuro-symbolic AI.

• Artificial Intelligence
• Intelligent Agents
• Software Engineering
• +4 more

Claudio Ulises Cortes Garcia is a Professor at the Department of Computer Science , Technical University of Catalonia, and leads the IDEAI-UPC (Intelligent Data Science and Artificial Intelligence Research Group) and KEMLG (Knowledge Engineering and Machine Learning Group). He is affiliated with the Barcelona Supercomputing Center (BSC-CNS) and the Barcelona School of Informatics (FIB). With a Doctor en Informática (PhD in Computer Science) and Ingeniero Industrial y de Sistemas (Industrial and Systems Engineering) degrees, his work spans Artificial Intelligence , Intelligent Agents , and Assistive Technology . His research integrates European Programs and Internet with applications in Second Life and Software . His recent publications focus on Post-COVID cognitive effects , AI ethics , and agent-based modeling for urban water management. He received the Doctor Honoris Causa from Universitat de Girona in 2024 and has collaborated on projects like DIGITAfrica and HUB D'INNOVACIÓ PEDIÀTRICA . His work bridges Neuroscience , Environmental Modeling , and Digital Humanities , with over 650 activities recorded in his academic career. ORCID : 0000-0003-0192-3096 WoS Researcher ID : B-7284-2009 Scopus Author ID : 7004065770

• Digital Trust
• Cybersecurity
• Blockchain
• +12 more

Dr. Felix Härer is a Lecturer and researcher at the University of Applied Sciences FHNW, School of Business, Basel, Switzerland, and also teaches externally at the University of Fribourg. He is affiliated with the Digital Trust Competence Center, where he conducts research and teaching in IT Security, Cybersecurity, Digital Trust, Blockchain, AI, Cloud Computing, and Systems Modeling. His research interests span a broad and interdisciplinary range, including: Digital Trust and Cybersecurity Blockchain and Decentralized Systems AI and Knowledge-based Systems (including LLMs and RAG) Software and Systems Modeling (BPMN, ArchiMate) Data Science and ETL-based Analytics Zero Trust and Secure Architectures His recent publications (2020–2023) demonstrate a strong focus on blockchain interoperability, model-driven engineering, decentralized applications, and the integration of AI with conceptual modeling. He explores scalable architectures, cross-chain query languages, and secure attestation mechanisms, often combining modeling approaches with emerging technologies. His work bridges academic rigor with practical implementation in distributed and cloud environments. Scientific awards include: Best Paper Award at IEEE PKIA 2023 He actively supervises bachelor’s and master’s theses and student projects in digital trust and related domains. He has served on PhD committees externally and is a reviewer and program committee member for journals and conferences such as IEEE Transactions, WWW, CAiSE, and EMISAJ. His professional experience includes industry work at Siemens Healthineers in software engineering. He is a member of the IEEE Blockchain Group (Switzerland) and contributes to UN/CEFACT standards for e-commerce and supply chain data. He is involved in organizing workshops and conferences, including B4ISE 2025, B4TDS 2023–2024, and DESRIST 2023, and has delivered keynotes on Computational Trust and Blockchain Interoperability.

Eui-kyung ShinView profile

Professor

• Social Studies Education
• Geographic Thinking
• GIS in Education
• +6 more

Eui-kyung Shin is a Professor in the Department of Curriculum and Instruction at Northern Illinois University’s College of Education. Her work centers on social studies education, particularly geographic thinking and the integration of geospatial technologies in K–12 classrooms. Her research interests include: Geographic thinking and spatial reasoning Integration of GIS and tablet apps in education Global perspectives in curriculum Teacher professional development Learning progressions in geography Elementary and secondary social studies instruction Dr. Shin’s recent publications and presentations highlight a strong focus on spatial skills, curriculum standards, and the role of technology in enhancing geographic education. Her work bridges cognitive development with innovative pedagogy, emphasizing the importance of geospatial literacy in modern classrooms. Notable scientific awards and recognitions include: Journal of Geography Award (2017) Dissertation Award, 1st Place, National Council for Geography Education (2004) Exceptional Contributions to Scholarly and Creative Activity Award, NIU College of Education (2008) Editorial Board, Journal of Geography (2011–present) Book Review Editor, Journal of Geography (2015–2016) Member, Road Map for Geography Education Project, National Geographic Society (2010–2012) She has advised various research initiatives and contributed to national educational projects. Dr. Shin has taught courses such as TLEE 342 (Teaching of Social Studies in Elementary School), TLCI 737 (Design of Instructional Models), and TLCI 762 (Seminar in Secondary Education). She is actively engaged in scholarly work and continues to influence geography and social studies education through research, service, and leadership.

Wei-Chen HungView profile

Professor

• Problem Solving
• Human-Computer Interaction
• Performance Support Systems
• +7 more

Wei-Chen Hung is a Professor and Department Chair in the Department of Educational Technology, Research and Assessment at Northern Illinois University’s College of Education. He holds a Ph.D. in Instructional Systems Technology from Indiana University-Bloomington and is actively engaged in teaching, research, and leadership in educational technology. Ph.D., Instructional Systems Technology, Indiana University-Bloomington (with Minor in Information Science) His research focuses on problem solving, human-computer interaction (HCI), and performance support systems in educational contexts. He explores how technology can scaffold learning, enhance problem-solving skills, and support teachers in instructional design and classroom management. His work spans K–12, higher education, and professional training environments. The recent publications highlight a strong trend in developing and evaluating technology-enhanced learning environments, including intelligent tutoring systems, 3D virtual worlds, educational simulations, and performance support tools. These works span disciplines such as STEM education, nursing, and social sciences, reflecting an interdisciplinary approach to solving instructional challenges through technology. Wei-Chen Hung has secured significant research funding from agencies including the National Science Foundation, NASA, and the Illinois Department of Education. He has served as Principal Investigator and Co-Principal Investigator on multiple grants focused on educational simulations, research methods training, and assistive technologies. National Science Foundation: Web-based Interactive Landform Simulation Model (WILSIM), $236,041, 2013–2016 (Senior Faculty Expert) Elgin Community College: Information security awareness, $10,000, 2011–2012 (Principal Investigator) National Science Foundation: Intelligent tutoring system for research methods, $150,000, 2008–2012 (Co-Principal Investigator) NASA: MARS Valley Networks Project, $20,000, 2005–2007 (Faculty Expert) Illinois Department of Education: Assistive technology for blind and visually impaired children, $75,000, 2005–2007 (Faculty Expert) He has contributed to the development of software tools and systems such as the Cause and Consequence behavior management system and performance support systems for educators. His lab and research initiatives emphasize applied design, usability testing, and evaluation of educational technologies in real-world settings.

• Game Theory
• Epistemic Game Theory
• Quantum Game Theory
• +7 more

Adam M. Brandenburger is the J.P. Valles Professor at the Leonard N. Stern School of Business, New York University, with additional appointments as Distinguished Professor at the Tandon School of Engineering, Faculty Director of the NYU Shanghai Program on Creativity + Innovation, and Global Network Professor. He previously served as a professor at Harvard Business School from 1987 to 2002. His academic foundation includes a B.A., M.Phil., and Ph.D. from the University of Cambridge. His research focuses on game theory , epistemic game theory , quantum game theory , and business strategy . He has made foundational contributions to the understanding of rationality, belief hierarchies, and the intersection of quantum mechanics with decision theory. His work spans economics, philosophy, computer science, and cognitive neuroscience, reflecting a deeply interdisciplinary approach. The recent publications show a strong trend toward integrating quantum foundations , information theory , and behavioral economics . Themes include epistemic reasoning in non-classical systems, the role of symmetry in strategic interactions, and the neural basis of decision-making. His work increasingly explores the limits of classical probability and cognition, using tools from quantum information and sheaf theory. While no formal scientific awards are listed, his publications in Nature Communications , Econometrica , and Philosophical Transactions of the Royal Society indicate high scholarly impact. His collaborations with leading researchers across disciplines suggest a central role in advancing interdisciplinary science. He advises and collaborates extensively, though specific students are not listed. His leadership in the NYU Shanghai Program on Creativity + Innovation highlights his commitment to global education and innovation. He has not received any grants explicitly mentioned, but his sustained publication output suggests active funding support. He is associated with research initiatives bridging game theory, quantum information, and cognitive science. His recent unpublished work on quantum-assisted observatories and large language models points to forward-looking research at the intersection of AI, quantum technology, and strategic reasoning.

Kaiyi JiView profile

Assistant Professor

• Large-scale optimization
• Machine learning
• Multi-task learning
• +6 more

Kaiyi Ji is an Assistant Professor in the Department of Computer Science and Engineering at the University at Buffalo, SUNY. He earned his PhD in Electrical and Computer Engineering from Ohio State University in 2021 and completed a postdoctoral fellowship at the University of Michigan. His research focuses on large-scale optimization, machine learning, and foundation models. PhD: Electrical and Computer Engineering, Ohio State University (2021) Postdoc: University of Michigan (2022) BSc: University of Science and Technology of China (2016) Research interests include bilevel optimization, multi-task learning, continual learning, and AI4Science, with applications in robotics and crystal property prediction. Recent work explores efficient algorithms for LLM training and optimization. His publications span top venues like ICLR, ICML, NeurIPS, and IEEE Transactions on Information Theory. He received the CSE Junior Faculty Research Award (2023) and NSF CAREER Award (2025). He advises PhD students and actively participates in departmental service as Associate Chair for Graduate Student Admissions and organizer of academic workshops.

• Database Systems
• Query Optimization
• Index Tuning
• +7 more

Surajit Chaudhuri is a Researcher at Microsoft , with a career spanning decades in database systems and data management . He has received the prestigious SIGMOD Edgar F. Codd Innovations Award (2011) for his contributions to query optimization , index tuning , and data lakes . Research Interests : His work focuses on database tuning , approximate query processing , fuzzy similarity joins , automated data transformations , and machine learning integration for scalable data systems. Recent Publications : In 2025, his research includes Auto-Test for unsupervised error detection in tables, Esc for budget-aware index tuning, and MMTU for multi-task table understanding benchmarks. Earlier works in 2024–2023 address spreadsheet formula recommendation , low-overhead index filtering , and time-series pattern recognition . Scientific Impact : He has co-authored influential papers in SIGMOD , VLDB , and IEEE Transactions , shaping practices in cloud databases , query optimization , and self-service BI . His collaborations span institutions like Microsoft, MIT, and ETH Zurich.

• Multi-agent Systems
• Intelligent Tutoring Systems
• Artificial Intelligence in Education
• +5 more

Ricardo Azambuja Silveira is a Professor at the Federal University of Santa Catarina, Brazil, with a distinguished research career spanning over two decades in the fields of multi-agent systems, intelligent tutoring systems, and semantic web technologies for education. His work bridges artificial intelligence with educational technology, creating innovative frameworks for adaptive learning environments and intelligent educational agents. Dr. Silveira's research interests focus on developing agent-based approaches to enhance educational experiences through technologies like BDI (Belief-Desire-Intention) architectures, ontology-based systems, and multi-context reasoning. His work particularly emphasizes the integration of intelligent agents with learning management systems to create personalized educational experiences. His recent publications demonstrate a continued evolution from foundational multi-agent frameworks to sophisticated neural-symbolic integrations and context-aware educational technologies. Throughout his career, he has published over 60 scholarly works, with consistent output from 2001 through 2024, demonstrating sustained research productivity. His publication trends show a clear trajectory from early work on JADE (Java Agent Development Framework) for distance education to current research on neural-symbolic integration in agent systems. The majority of his publications appear in prominent conferences like PAAMS, MICAI, and ICAART, reflecting his standing in the multi-agent systems community. Dr. Silveira has mentored numerous researchers who have become his frequent collaborators, including Arnoldo Uber Junior, Rodrigo Rodrigues Pires de Mello, and Thiago Ângelo Gelaim. His research has been supported through various academic grants that enabled the development of frameworks like Sigon (a multi-context system framework) and iEnsemble (for committee machine learning). He has been actively involved in the organization of academic events, particularly the Methodologies and Intelligent Systems for Technology Enhanced Learning (MIS4TEL) conference series, where he has served as both participant and organizer. His work contributes significantly to the theoretical foundations and practical implementations of intelligent educational technologies.

• Bioinformatics
• Computational Biology
• Pharmaceutical Drug Discovery
• +6 more

Leonard P. Wesley is an Associate Professor at the Computer Science Department, College Of Science, San Jose State University. With a Ph.D. and M.S. in Computer Science from University of Massachusetts and a B.A. in Physics and Math from Northeastern University, his work spans bioinformatics, pharmaceutical discovery, machine learning, robotics, and evidential reasoning. He has published extensively on SVM/QSAR-based drug prediction, autonomous systems, and uncertainty management. Ph.D., University of Massachusetts - Computer Science M.S., University of Massachusetts - Computer Science B.A., Northeastern University - Physics and Math His research focuses on developing predictive models for drug discovery, autonomous robotics, and data analytics. Recent publications emphasize SVM applications in medical diagnostics and pharmaceutical modeling. He has contributed to conferences in aerospace, robotics, and biotechnology, with invited talks at NASA and Los Alamos National Laboratory. 3D-QSAR & SVM prediction of drug inhibitors Evidential decision analytics Autonomous robotic control PCA/SVM-based sepsis diagnostics Hybrid network congestion management Professor Wesley teaches courses in artificial intelligence, bioinformatics, and advanced programming. His lab investigates applications of machine learning in biotechnology and aerospace, including biomarker identification and CFD expert systems. He has served as session chair at international conferences and collaborated with institutions like NASA and Advanced Decision Systems.