Eugene Feinberg is a Distinguished Professor in the Department of Applied Mathematics and Statistics at Stony Brook University's College of Engineering and Applied Sciences. He is renowned for his extensive contributions to Markov Decision Processes (MDPs), stochastic optimization, and inventory control. Research Interests: His work spans theoretical and applied aspects of Markov Decision Processes , stochastic optimization , inventory control , healthcare decision-making , and machine learning . He has particularly focused on solving complex decision-making problems under uncertainty, with applications ranging from operations research to medical decision-making. Scientific Awards: He has been honored with the title of Distinguished Professor , recognizing his outstanding contributions to his field. Advising and Grants: While specific details on students and grants are not provided, his prolific publication record and faculty status suggest active involvement in advising and securing research funding. Contact and Resources: His university webpage can be accessed at http://www.ams.sunysb.edu/~feinberg/ , and his Google Scholar profile is available at https://scholar.google.com/citations?user=LLt--pgAAAAJ&hl=en .
Julian Berger is a postdoctoral researcher at the Max Planck Institute for Human Development in the Center for Adaptive Rationality , where he explores how to enhance decision-making through hybrid human-AI systems. He is also a fellow of the Joachim Herz Foundation and has received funding from the Foundation of German Business and the Danish Data Science Academy. Education: M.A. Psychology in Business and Economics, Universidade Catolica Portuguesa (2021) B.A. Politics, Administration and International Relations, Zeppelin Universität (2018) His research spans human-AI collaboration , collective intelligence , and interpretable machine learning . A recurring theme in his work is developing methods to combine human expertise with AI capabilities for accuracy in domains like medical diagnostics , credit scoring , and football analytics . He has authored publications in high-impact venues such as PNAS , Nature Human Behavior , and Science and Medicine in Football . Scientific awards and funding include: Fellowship for interdisciplinary economics, Joachim Herz Foundation (2024) PhD funding from the Foundation of German Business (Stiftung der deutschen Wirtschaft) Research grant from the Danish Data Science Academy His recent article trends emphasize ensembling techniques that leverage complementary human and AI errors, algorithmic fairness, and practical heuristics like Hybrid Confirmation Trees. These works demonstrate significant improvements in diagnostic accuracy and decision cost-efficiency. Beyond academia, Berger works as a consultant and ML engineer with Simply Rational , focusing on interpretable models for financial and sports analytics. His work bridges theoretical research with real-world applications, prioritizing fairness, transparency, and human accountability in AI systems.
Matthew Stephenson is a Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence applications for games. He leads the Data for Decisions initiative within the Factory of the Future Transdisciplinary Hub, focusing on AI-powered scenario generation for smart digital twins. Additionally, he is a member of IRL CROSSING, an international lab studying human-autonomous agent teaming dynamics. PhD in Computer Science (Australian National University, 2019) B.Sc.(Hons) in Computer Science (University of Canterbury, 2015) His research applies AI, Machine Learning, and Data Science to game domains, including intelligent agent development for physics-based environments, procedural content generation, and game analytics. He also investigates deceptive behaviors in multi-agent systems and leverages games as testbeds for real-world AI solutions. Recent publications focus on large language models for game benchmarking, physical reasoning challenges, and evolutionary game generation. Scientific awards include an honourable mention at Foundations of Digital Games (FDG'18). He supervises students in procedural generation, game AI, and physics-based task creation, with teaching roles in computational intelligence and neural networks courses.
Professor Christian Deutscher is a prominent sports economist at Bielefeld University's Faculty of Psychology and Sport Science, specializing in the Department of Sport Science within Division V - Sport and Business. As both Research Officer and Internationalization Officer, he leads significant work in sports economics, particularly focusing on betting markets, match-fixing detection, and sports integrity. His research has attracted funding from major institutions including the German Research Foundation. Deutscher's research interests span sports economics, betting market efficiency, match-fixing detection, sports management, and the business aspects of professional sports. His work combines advanced statistical modeling with practical applications in sports integrity monitoring. He has extensively analyzed live betting markets, Bundesliga economics, and the impact of technological innovations like VAR in football. His research often examines the intersection of sports performance, economic incentives, and market behavior. Analysis of his recent publications reveals a strong focus on empirical studies of sports betting markets, particularly live and in-play betting dynamics. His work demonstrates sophisticated use of state-space models and other advanced statistical techniques to detect market inefficiencies and potential integrity issues. Deutscher frequently collaborates with statisticians and economists to develop warning systems for match-fixing, with particular attention to German football leagues. His research bridges theoretical economics with practical applications in sports governance. Professor Deutscher actively contributes to the European Sport Economics Association (ESEA), having edited special issues of conference proceedings and serving in editorial capacities. His work has been published in leading journals including Journal of Sports Economics, Economic Inquiry, and Applied Stochastic Models in Business and Industry. As Research Officer for the Faculty of Psychology and Sport Science, Deutscher oversees research initiatives and international collaborations. His current projects include data-based fraud detection in live betting markets, funded by the German Research Foundation across multiple phases. He also serves on various university committees including the Quality Improvement Commission and Examination Board for the Department of Sport Science. Deutscher maintains strong connections with sports organizations and betting industry stakeholders, ensuring his research has practical relevance for sports integrity monitoring. His work on betting market inefficiencies has direct applications for regulatory bodies seeking to protect the integrity of sporting competitions.
Toshiharu Sugawara is a Professor in the Department of Computer Science and Engineering at Waseda University's Faculty of Science and Engineering, School of Fundamental Science and Engineering, a position he has held since April 2007. With a Ph.D. in Engineering from Waseda University, his research spans multiple domains in artificial intelligence and multi-agent systems, maintaining active collaborations across international institutions and contributing significantly to the field through numerous publications and awards. Dr. Sugawara received his BS and MS degrees in Mathematics from Waseda University in 1980 and 1982, respectively, followed by his Ph.D. in 1992. Before joining Waseda University as faculty, he worked as a Research Scientist at NTT Laboratories from 1982 to 2007, with a visiting researcher position at the University of Massachusetts at Amherst in 1992-1993. He also held part-time lecturer positions at University of Electro-Communications (2003-2007), Waseda University (2004-2006), and Tokyo University of Agriculture and Technology (1990-1991). His research interests focus on artificial intelligence with particular expertise in multi-agent systems, machine learning, cooperation and coordination mechanisms, soft computing, computational social science, and social informatics. His work bridges theoretical foundations with practical applications in network management and information systems. Recent publications demonstrate a strong trajectory toward interpretable multi-agent reinforcement learning, efficient path planning algorithms, and modeling social behaviors in complex networks. His research group has made significant contributions to multi-agent path finding, cooperative task execution, and understanding virtual economies in social media platforms. Dr. Sugawara has received numerous prestigious awards including multiple Best Paper Awards at JAWS conferences (2014, 2015, 2018), ACM SAC 2015, and various research paper awards from Japanese academic societies. His work on multi-agent systems has been consistently recognized for its theoretical rigor and practical impact. As an advisor, Dr. Sugawara has mentored numerous students who have become prominent researchers in their own right, with many co-authoring papers that have received awards. His laboratory maintains strong collaborations with industry partners, particularly in the areas of network management and intelligent systems. Current research directions include developing interpretable multi-agent reinforcement learning frameworks, optimizing multi-agent coordination in constrained environments, and analyzing social dynamics in virtual economies.
Tridas Mukhopadhyay is the Deloitte Consulting Professor of e-Business at Carnegie Mellon University's Tepper School of Business, where he has served on the faculty since 1986. His academic journey at CMU progressed from Instructor of Information Systems (1986-1987) to Assistant Professor (1987-1993), Associate Professor (1993-1997), Professor (1998-present), and Deloitte Consulting Professor of e-Business (2000-present). He also served as Director of the MS in Electronic Commerce program from 1999-2004. Ph.D. in Computer and Information Systems, University of Michigan–Ann Arbor, 1987 M.B.A. in Computer and Information Systems, Indian Institute of Management Calcutta, 1981 B. Tech. in Electrical Engineering, Indian Institute of Technology Kharagpur, 1978 Professor Mukhopadhyay's research spans multiple critical areas in information systems and technology management. His work on strategic IT use examines how organizations derive business value from information technology investments. He has conducted extensive research on business-to-business commerce, particularly focusing on e-procurement systems, web-based marketplaces, and electronic intermediation models. His cybersecurity research investigates the economic aspects of cyber security, including liability mechanisms and patch release strategies. In software engineering, he has studied productivity, quality metrics, and offshore software development contracts. His most recent publications reveal several key trends in his research trajectory. There's a growing focus on digital platform economics, examining advertising models, virtual currency systems in gaming, and sharing economy dynamics. His work increasingly incorporates behavioral aspects, studying how users respond to personalized content and how backers exert control in crowdfunded projects. Methodologically, his research employs sophisticated analytical approaches including hierarchical Bayesian models, structural equation modeling, and natural experiment designs. CART Research Frontier Award, Carnegie Mellon, 2005 Distinguished Ph.D. Alum, Michigan Business School, 2004 Best Paper, International Conference on Information Systems, 2001 Best Paper, MIS Quarterly, 1995 Xerox Research Chair, Tepper School of Business, 1988-1989 Information Systems Society Distinguished Fellow, 2012 Professor Mukhopadhyay has served on numerous editorial boards including Information Systems Research (1994-2003), Management Science (1999-2003), and MIS Quarterly (1997-1999), demonstrating his significant contributions to the field. His consulting work with major organizations including Alcoa, Chrysler, Ford, General Motors, IBM, and governmental agencies like the United States Post Office and Pennsylvania Turnpike has provided practical insights that inform his academic research. He has been actively involved in university governance through committee service including the Business Technology Faculty Search Committee and the CMU Faculty Senate. His research has been supported through various industry partnerships and academic grants, though specific grant details aren't provided in the source material. His teaching focuses on Business Computing and Strategic IT courses, reflecting his expertise in both foundational information systems concepts and strategic applications of technology in business contexts.
Johanna Pirker serves as an Associate Professor at the Institute of Human-Centred Computing, Graz University of Technology, where she holds teaching authorization in Applied Computer Science. Her work bridges academic research with practical applications in interactive technologies, maintaining active consultation hours for students every Monday morning. Her research centers on human-centered computing with emphases on virtual/augmented reality systems, serious game design, and AI-driven interactive experiences. She investigates player behavior, user experience optimization, and therapeutic/educational applications of immersive technologies across diverse contexts including rehabilitation, engineering education, and social platforms. Recent 2025 publications reveal strong trends in AI integration for gaming ecosystems (toxicity detection, dialogue systems), VR-based educational tools across disciplines, and cross-cultural analyses of gaming communities. Her work consistently combines experimental user studies with novel system development to address real-world challenges. While specific grant details and student advising records aren't documented in source materials, her extensive publication output across venues like FDG and iLRN indicates active leadership in interdisciplinary collaborations focused on advancing immersive technologies for societal benefit.
R. Michael Alvarez , Flintridge Foundation Professor of Political and Computational Social Science at Caltech, is a leading scholar in election technology, political methodology, and machine learning applications in social science. Affiliated with the Caltech/MIT Voting Technology Project , the Social and Decision Neuroscience Program , and the Resnick Sustainability Institute , his work bridges technology and democracy. Education: B.A. from Carleton College, Ph.D. from Duke University Academic Career: Caltech faculty since 1992 His research spans: Election Integrity : Monitoring election security, fraud detection, and ballot systems Computational Social Science : Applying machine learning to voter behavior and policy analysis Climate Policy : Examining public attitudes and behavioral interventions for sustainability Online Behavior : Analyzing toxicity in gaming and social media dynamics Key article trends show focus on election forensics (2025 Nature Climate Change study), game toxicity analysis (2025 CHI Play paper), and LLM applications in social science. His students include Jacob Morrier, Mitchell Linegar, and teams of postdocs and undergraduates in Caltech's SURF program. Scientific recognition includes: Google Cloud Research Innovators Class of 2022 Co-editor of multiple academic series including Cambridge Elements in Quantitative Methods
Dr. Miriam Sturdee is a Lecturer in Human-Computer Interaction (HCI) at the School of Computer Science, University of St Andrews. Her work focuses on advancing HCI through innovative methods in design, education, and interdisciplinary collaboration. She actively contributes to research areas such as visual data analysis, blended experiences, and healthcare technology, with notable expertise in sketching techniques and their applications in user-centered design. Dr. Sturdee supervises PhD candidates Jess McGowan and Junyu Zhang, guiding their research in HCI-related domains. Her research interests span HCI pedagogy, cybersecurity visualization, and sustainable design, emphasizing inclusivity and accessibility. Collaborations include workshops on digital-physical integration and participatory design for healthcare communication. She has co-authored a practical guide on sketching theory and actively participates in academic conferences, contributing to discussions on knowledge production and materiality in HCI. Dr. Sturdee’s work aligns with UN Sustainable Development Goals, particularly in advancing healthcare equity and sustainable practices. She engages in outreach activities, such as the Doors Open @ Computer Science event, fostering public engagement with technology. Her publications reflect a commitment to bridging artistic expression with computational methods, exploring topics like parasocial interactions in games and remote sketching in distributed teams.
Carlo A. Furia is an Associate Professor at the Software Institute within the Faculty of Informatics at Università della Svizzera italiana (USI). He leads the ATOM research group and is actively involved in advancing formal methods in software engineering. His work bridges theoretical rigor with practical applicability, particularly in verification, automated repair, and empirical analysis of software systems. PhD in Computer Science, Politecnico di Milano Master of Science in Computer Science, University of Illinois at Chicago Laurea in Computer Science and Engineering, Politecnico di Milano His research focuses on making formal methods practical through automation, combining diverse techniques, and conducting thorough empirical evaluations. He is particularly interested in using Bayesian data analysis to assess software engineering data. His work spans program verification (e.g., AutoProof), contract inference, API usability, and multilingual program analysis. His recent publications highlight trends in automated program repair, JVM bytecode analysis, Android security, and empirical methodologies. These works reflect a consistent emphasis on correctness, reliability, and empirical validation in software development. Scientific service includes: Associate Editor, Empirical Software Engineering (EMSE) journal Program Committee member, FM 2026, FormaliSE 2026, ASE 2025, iFM 2025 He has advised students and leads the ATOM group, which develops tools for software analysis. He teaches courses such as Software Analysis, Programming Fundamentals, and Software Design & Modeling. Current research directions include improving empirical evaluation rigor and enhancing verification at lower code levels like bytecode.
Anupam Joshi is the Acting Dean of the College of Information Technology and Engineering and Oros Family Professor of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He also directs UMBC’s Center for Cybersecurity and leads the National Cybersecurity FFRDC for the University System of Maryland. His research focuses on networked computing, AI-driven cybersecurity, privacy-preserving technologies, and policy-driven security frameworks. He holds a Ph.D. in Computer Science from Purdue University (1993), an M.S. (1991), and a B.Tech in Electrical Engineering from the Indian Institute of Technology, Delhi (1989). Dr. Joshi’s work spans over 400 publications with 32,650+ citations (h-index 92) and nine patents. His grants include funding from NSF, DARPA, NASA, NIST, and industry partners like IBM and Northrop Grumman. Key contributions include developing CAPD frameworks for IoT security, FABULA for automated threat intelligence, and KiNETGAN for intrusion detection through synthetic data. He is an IEEE Fellow and pioneer in applying AI to secure critical infrastructure, smart grids, and healthcare systems. His research trends emphasize AI-empowered cybersecurity, privacy compliance in data sharing (e.g., agriculture, healthcare), and mitigating attacks on smart systems. Notable projects include combating fake cybersecurity reports using provenance analysis, securing EV charging infrastructure, and enhancing smart farming resilience through policy-driven access control. Awards: IEEE Fellow Grants: Over $30M from NSF, DoD, NASA, and industry collaborations Labs/Teams: Director of UMBC Center for Cybersecurity, Cybersecurity Knowledge Graph initiatives Future work includes advancing neurosymbolic AI for cybersecurity, semantic data extraction from scientific literature, and AI ethics in healthcare applications.
Elise Lavoué is a full Professor in Computer Science at iaelyon School of Management, Jean Moulin Lyon 3 University, and a key researcher at the LIRIS laboratory (CNRS). She leads the SICAL research team and holds leadership roles including Editor-in-Chief of the STICEF journal, member of Labex ASLAN’s management committee, and member of the University of Lyon’s Research Ethics Evaluation Committee (CER-UdL). She is also affiliated with the ATIEF association. Her research focuses on enhancing motivation and engagement in digital learning environments through adaptive gamification, learning analytics, and human-computer interaction. She explores how tailored game elements, emotional awareness tools, and immersive technologies like virtual reality can support self-regulated learning, critical thinking, and skill development in complex digital contexts. Her recent publications span top journals such as IEEE Transactions on Learning Technologies, International Journal of Human-Computer Studies, Computers & Education, and CHI PLAY. These works reflect a strong trend in adaptive and personalized learning technologies, emotion-aware systems, and immersive training environments, particularly in educational and professional settings. Honorable Mention Award at ACM CHI PLAY 2019 (top 4%) Best Industrial Paper award at CSEDU 2020 Elise Lavoué actively supervises PhD students and post-doctoral researchers and leads multiple funded projects including LudiMoodle+, RENFORCE, Lex.gaMe, BODEGA, and Emoviz. These projects involve collaborations with institutions across France and focus on gamification, VR training, emotional dashboards, and vocabulary acquisition. She has secured funding from ANR, Labex ASLAN, CNRS, and other national bodies. Her work emphasizes interdisciplinary collaboration between computer science, education, and social sciences. She is involved in several research teams and labs, primarily the SICAL team within the LIRIS laboratory, a major interdisciplinary research unit in computer science, images, and information systems. Her projects often involve industry partners such as SpeakPlus and Woonoz, and she contributes to both scientific advancement and practical educational innovation.
Bernhard von Stengel is a Professor of Mathematics at the Department of Mathematics, London School of Economics and Political Science . His work bridges game theory, computational complexity , and mathematical economics , with a focus on equilibrium computation and algorithmic aspects. Developed Game Theory Explorer , open-source software for analyzing strategic and extensive-form games. Organized major workshops like What is Strategic Information? (2024) and Game Theory and Machine Learning (2023). Authored the textbook Game Theory Basics (Cambridge University Press, 2021). His research spans zero-sum games , correlated equilibrium , inspection games , and communication over noisy channels . Recent work includes characterizing the Condorcet dimension of metric spaces (2024) and stable-set bounds for Nash equilibria in bimatrix games. He has collaborated with institutions like the Game Theory Society and contributed to public discourse via talks on algorithms' societal impact (2021) and game theory in politics (2020).
Matti Vuorre is Research Associate at the Oxford Internet Institute studying psychological impacts of digital technologies through naturalistic behavioral data. Education: PhD in Experimental Psychology and Data Science. Research employs intensive longitudinal designs to examine causal relationships between technology use and mental health. Leads SHIFT Collective investigations into gaming impacts. Develops open-source statistical methods for behavioral research with applications in digital wellbeing studies.
James Hardy is a Professor in Sport & Exercise Science at Bangor University's School of Psychology and Sport Science , with a career spanning elite sports psychology research and teaching. He holds a BSc (First Class) from the University of Birmingham, and MA/PhD from the University of Western Ontario under Prof. Craig Hall. Key roles: Senior Lecturer, Deputy Head of School, Associate Editor for Journal of Applied Sport Psychology , and editorial board member for multiple journals. Research focuses on self-talk/imagery and group dynamics (team cohesion, leadership), funded by ECB, UK Sport, and Manchester City FC. Recent publications highlight his interdisciplinary approach, examining leadership effects, pressure training protocols, narcissism in teams, and injury risk factors via pattern recognition. Notable work includes Psychosocial Characteristics of Elite Rugby Players and Individualized Talent Development in beach sprint rowing. Scientific contributions include a Bangor University Teaching Fellowship and 30+ peer-reviewed articles . Grants like £80k from ECB and £56k from City Football Services underscore his applied impact.
