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Vahid YazdanpanahView profile

Assistant Professor

• Multiagent Systems
• Artificial Intelligence
• Responsibility of AI Systems
• +3 more

Vahid Yazdanpanah is an Assistant Professor (Lecturer) of Computer Science at the University of Southampton and a Visiting Lecturer at the University of Twente. He holds a PhD from the University of Twente (2019), an MSc in Artificial Intelligence from Utrecht University (2015), and an MBA from the University of Greenwich (2012). His research focuses on multiagent systems, AI responsibility, and circular economy applications. He leads the Agents, Interaction and Complexity (AIC) research group and is an RRI Champion for the UKRI CDT in AI for Sustainability (SustAI). Research interests include agent-based computing, formal logics for multiagent decision-making, and socio-technical systems. Notable awards include the Best Paper Award at PRIMA 2016 and recognition at AAMAS 2021. He teaches courses such as COMP2211 (Software Engineering) and supervises PhD students in AI and sustainability. Active projects include the ARGOS (AI Resilience Governance) and AutoTrust (Internet of Vehicles) initiatives. He has served on program committees for AAAI, IJCAI, and AAMAS, and reviews for journals like AI & Society and Annals of Operations Research. His work bridges technical AI advancements with ethical, legal, and societal challenges in responsible AI deployment.

Jonathan GratchView profile

Research Professor

• Affective Computing
• Cognitive Modeling
• Human-Computer Interaction
• +6 more

Jonathan Gratch is a Research Professor at the University of Southern California (USC) with joint appointments in Computer Science , Psychology , and Media Arts and Practice . He serves as Director for Virtual Human Research at USC's Institute for Creative Technologies and leads the USC Affective Computing Group . His work focuses on computational models of human cognitive and social processes, particularly emotions, and their applications to virtual environments. Education: Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign (1995) Gratch's research spans Affective Computing , Cognitive Modeling , and Human-Computer Interaction , with a focus on creating emotionally intelligent virtual agents. His projects include the development of computational emotion models (e.g., EMA) and virtual human systems for training, healthcare, and social interaction studies. Key applications include the Mission Rehearsal Exercise and Stability and Support Operations prototypes. Recent publications (2023) highlight his exploration of LLM-based emotion modeling , social influence dynamics in human-agent interactions, and ethical implications of AI assistants . Earlier work (2014-2015) established foundational frameworks for automated negotiation and rapport-building virtual agents . His methodological contributions include parasocial consensus sampling and appraisal theory-based emotion architectures. Scientific honors include Fellowships from AAAI, AAAC, and the Cognitive Science Society, the SIGART Autonomous Agents Award , and Senior Membership in IEEE . As founding Editor-in-Chief of IEEE Transactions on Affective Computing , he has significantly shaped the field's academic discourse. Gratch's virtual humans leverage immersive audio-visual environments (8'x30' screens, 10.2-channel audio) to study socio-emotional dynamics. His team's work demonstrates that anthropomorphism in machines can enhance interaction but may produce unintended consequences, informing design principles for effective human-machine collaboration.

Marco ValtortaView profile

Professor

• Artificial Intelligence
• Bayesian Networks
• Causal Inference
• +5 more

Marco Valtorta is a Professor and Graduate Director in the Department of Computer Science and Engineering at the University of South Carolina’s Molinaroli College of Engineering and Computing. He specializes in Artificial Intelligence, with a focus on normative reasoning under uncertainty, Bayesian networks, causal models, and computational complexity. His work includes developing algorithms for structure learning in graphical models, causal inference, and applications in multiagent systems. Education: Ph.D., Computer Science, Duke University (1987) M.A., Computer Science, Duke University (1984) Laurea, Electrical Engineering, Politecnico di Milano (1980) Research Interests: Dr. Valtorta’s work integrates logical and probabilistic reasoning, with contributions to causal models, chain graphs, and adversarial machine learning. His funded projects include collaborations with the Office of Naval Research (ONR), IARPA, and the U.S. Department of Agriculture (USDA). Notable collaborations include applying Bayesian networks to healthcare and developing frameworks for trustworthiness assessment in AI systems. Grants & Collaborations: Multi-institution IARPA project on Wigmorean/Bayesian networks for argumentation ONR-funded research on Markov properties of directed hypergraphs with Dr. Linyuan Lu Causal analysis for performance modeling of configurable systems His recent publications emphasize causal inference in AI, automated evaluation of text and sentiment analysis systems, and robustness of foundation models. He has pioneered algorithms for learning chain graphs and addressing adversarial attacks in probabilistic models.

Daniel A LevinthalView profile

Professor

• Organizational Adaptation
• Strategic Management
• Technological Competition
• +2 more

Daniel A Levinthal is the Reginald H. Jones Professor of Corporate Strategy and Professor of Management at the Wharton School, University of Pennsylvania. With extensive publications on organizational adaptation and industry evolution in technological contexts, he serves as Editor-in-Chief for Strategy Science and Organization Science. Research Interests Industry evolution Organizational learning Technological competition His 2024 research examines organizational search strategies, showing how cautious exploitation combines slow belief updating with strong explicit exploitation for effective adaptation. Recent work explores how political coalitions drive organizational change, with hierarchical belief influence structures proving more effective than flat designs in certain environments. Earlier studies developed the "Mendelian executive" framework and advanced Carnegie School decision-making theory. Scientific Awards Fellow of Strategic Management Society Fellow of Academy of Management Distinguished Scholar Awards (3 divisions) Irwin Award as Distinguished Educator 4 Honorary Doctorates Levinthal teaches advanced strategy courses (MGMT9000, MGMT9150) and graduate enterprise management (MGMT6110). His research has established foundational insights about organizational capabilities, knowledge aggregation, and strategic inertia.

Lukasz SzpruchView profile

Professor

• Probability Theory
• Stochastic Analysis
• Theoretical Machine Learning
• +10 more

Lukasz Szpruch serves as Professor at the University of Edinburgh's School of Mathematics and Programme Director for Finance and Economics at The Alan Turing Institute. He leads the FAIR research programme on responsible AI adoption in financial services and co-investigates the UK Centre for Greening Finance & Investment (CGFI), directing partnerships with the National Office for Statistics, Accenture, Bill & Melinda Gates Foundation, and HSBC. He maintains affiliations with the Oxford-Man Institute for Quantitative Finance. His research focuses on probability theory , stochastic analysis , and theoretical machine learning , with current investigations into deep learning foundations, mean-field models, reinforcement learning, game theory, multiagent systems, and computational optimal transport. These theoretical frameworks are rigorously applied to financial economics problems including market dynamics, risk modeling, and regulatory compliance, emphasizing mathematical precision in AI system design. Recent publications reveal a strategic shift toward responsible AI deployment in finance , addressing large language model governance, synthetic data privacy, and non-asymptotic sampling theory. His work consistently bridges abstract mathematics with financial sector applications, particularly through the FAIR programme's industry collaborations that translate theoretical advances into practical frameworks for trustworthy AI adoption. As Principal Investigator of FAIR and CGFI co-Investigator, Szpruch manages significant research funding streams focused on AI ethics in financial services and sustainable finance. His academic leadership drives cross-sector initiatives where theoretical research directly informs regulatory policy development and industry best practices, though specific student mentoring details remain unspecified in source materials. Szpruch operates at the nexus of three critical research ecosystems: the FAIR programme's industry partnerships, CGFI's sustainability-focused finance research, and the Oxford-Man Institute's quantitative finance initiatives. These interconnected teams combine mathematical rigor with real-world financial applications, developing frameworks for AI assurance, green finance metrics, and synthetic data validation that address systemic challenges in modern financial systems.

• Robotics
• Artificial Intelligence
• Machine Learning
• +3 more

Dr. Danesh Tarapore is an Associate Professor at the University of Southampton specializing in robotics and AI. He focuses on human-robot interaction, swarm intelligence, and autonomous systems. His current research involves developing resilient robotic teams and optimizing learning algorithms for constrained environments. He supervises 6 PhD students in the iPhD MINDS and Computer Science programs. Dr. Tarapore's work bridges theoretical advancements with practical applications in autonomous navigation, multimodal dataset creation, and quality-diversity optimization. His publications span conferences like HRI and journals in robotics and AI. He collaborates with institutions like the University Hospital Southampton and the Boldrewood Innovation Campus. Research Interests: Human-robot collaboration, swarm systems, machine learning, and adaptive control Key Contributions: HRI-SENSE dataset, evolutionary subset selection algorithms, forest navigation frameworks Grants and Funding: Active projects in multi-agent systems and resilient robotics Dr. Tarapore maintains active roles in the robotics community through conference participation and interdisciplinary collaborations.

Giorgia RamponiView profile

Assistant Professor

• Machine Learning
• Mathematical Modelling
• Reinforcement Learning
• +3 more

Giorgia Ramponi is an Assistant Professor with Tenure Track at the Faculty of Business, Economics and Informatics at the University of Zurich. She is also an affiliated professor at the ETH AI Center and the Data Science and AI, Computer Science and Engineering department at Chalmers University of Technology. Her educational background includes a Ph.D. in Information Technology from Politecnico di Milano (completed June 2021 with honors), advised by Marcello Restelli, and a Master of Science in Computer Science with Honours Programme (110/110 cum laude) from la Sapienza (July 2017), advised by Flavio Chierichetti and Alessandro Panconesi. Dr. Ramponi's research focuses on machine learning and mathematical modeling, with particular emphasis on reinforcement learning and multiagent learning. Her work bridges theoretical foundations with practical applications, exploring how learning algorithms can make optimal decisions in complex environments. She has made significant contributions to areas including inverse reinforcement learning, multi-agent systems, constrained Markov decision processes, and human-AI interaction through preference learning. Her recent publications demonstrate a strong trend toward addressing fundamental challenges in reinforcement learning, particularly in multi-agent settings, constrained optimization, and learning from human feedback. Her work combines theoretical rigor with practical applications across robotics, economics, and decision-making systems. Hassler Research Grant for "Unified Feedback Integration Framework for Reinforcement Learning" Dr. Ramponi actively contributes to the academic community through conference participation, invited lectures (including at the Mediterranean Machine Learning Summer School), and teaching. She designed and taught the "Data Science and Machine Learning" course for the ETH-Ashesi Master program. She is also a member of the ELLIS community, which connects excellence in AI research across Europe. Her research group focuses on developing frameworks for reinforcement learning with various feedback types, including preferences, rewards, and demonstrations. The group aims to advance the theoretical understanding of learning algorithms while addressing practical challenges in real-world applications.

Haibo HeView profile

Professor

• Computational Intelligence
• Neural Networks
• Reinforcement Learning
• +5 more

Dr. Haibo He is the Robert Haas Endowed Professor in the Department of Electrical, Computer, and Biomedical Engineering at the University of Rhode Island (URI). As an IEEE Fellow and NSF CAREER awardee, his research focuses on computational intelligence, neural networks, and reinforcement learning with applications to smart grids and microgrid systems. Ph.D. in Electrical Engineering, Ohio University, 2006 M.S. in Electrical Engineering, Huazhong University of Science and Technology, 2002 B.S. in Electrical Engineering, Huazhong University of Science and Technology, 1999 His research interests include: Computational Intelligence Adaptive Dynamic Programming Reinforcement Learning Deep Learning for Power Systems Distributed Control in Microgrids Imbalanced Data Learning Recent research trends from publications (2018-2025) show a focus on: Multi-agent reinforcement learning for energy systems Digital twin frameworks for grid security Event-triggered control mechanisms Finite-time convergence algorithms Cyber-attack resilient control systems Evolutionary computation in power networks Awards: IEEE Fellow (2018) NSF CAREER Award (2017) Dr. He leads the Computational Intelligence and Self-Adaptive Systems (CISA) Laboratory at URI, which conducts fundamental research on computational intelligence methods with applications to power systems, data mining, and neural networks.

• Artificial Intelligence
• Knowledge Graphs
• Semantic Technologies
• +5 more

Dr Zhe Wang is a Senior Lecturer at the School of Information and Communication Technology, Griffith University, focusing on artificial intelligence, knowledge graphs, and semantic technologies. He earned his PhD in Computer Science from Griffith University (2011) and previously worked as a Research Fellow at the University of Oxford (2011-2013) on ontology-based systems. Research: Specializes in knowledge graph construction, rule mining for explainable AI, and integrating machine learning with logical reasoning. Led development of the scalable RLvLR rule-mining system and contributed to the HermiT ontology reasoner. Teaching: Instructs undergraduate and postgraduate courses including Introduction to Artificial Intelligence, Secure Development Operations, and Software Engineering Fundamentals. Grants: Funded by Australia's Economic Accelerator Ignite Grant (2025) for AI-driven marine life survey systems and Office of National Intelligence projects (2021-2022). Publications: Active in top venues like AAAI, ICASSP, and ISWC, with recent work on temporal knowledge graph reasoning, auction design algorithms, and neurosymbolic AI systems.

Ceyhun EksinView profile

Associate Professor

• Networked Multi-Agent Systems
• Game Theory
• Distributed Optimization
• +5 more

Ceyhun Eksin is an Associate Professor and the Corrie and Jim Furber '64 Faculty Fellow at the Texas A&M University Industrial & Systems Engineering Department. He is also affiliated with the Electrical & Computer Engineering Department. His research focuses on networked multi-agent systems, integrating game theory, distributed optimization, and control theory to address challenges in autonomous systems, energy systems, and epidemiological modeling. Education: Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania (2015), followed by a postdoctoral fellowship at Georgia Institute of Technology (hosted by Professors Jeff S. Shamma and Joshua S. Weitz). Research interests emphasize the design and analysis of complex systems, including distributed algorithms for autonomous teams, epidemic dynamics influenced by behavioral changes, and optimization in smart grids. His work bridges theoretical foundations with practical applications in cyber-physical systems and social networks. Notable awards include the NSF CAREER Award (2023) and TAMIDS Career Initiation Fellowship (2023). His research has been published in top journals like Proceedings of the National Academy of Sciences and IEEE Transactions . Lab activities center on the NetMaS (Networked Multiagent Systems) Lab, focusing on theoretical and algorithmic innovations for multi-agent systems. Collaborations span academia and industry, addressing real-world challenges in energy, healthcare, and robotics.

Tim BaldeniusView profile

Professor

• Managerial Accounting
• Performance Measurement
• Corporate Governance
• +2 more

Tim Baldenius serves as the Paul M. Montrone Professor of Private Enterprise in the Accounting Division of Columbia Business School at Columbia University. He rejoined Columbia in 2017 after serving as Chair of NYU Stern's Accounting Department (2011-2016), and previously held faculty positions at Columbia Business School (1998-2011) where he chaired the Accounting Division (2009-2011). His teaching portfolio includes MBA courses in Financial Planning & Analysis, PhD seminars on managerial accounting, and executive education programs. His academic credentials include a Diploma in Business Administration from the University of Hamburg and a PhD in Accounting from the University of Vienna. Baldenius maintains editorial leadership as Associate Editor of Management Science and serves on the editorial boards of The Accounting Review , Review of Accounting Studies , and Review of Managerial Sciences . Professor Baldenius's research centers on managerial accounting systems, performance measurement frameworks, and corporate governance structures. His work examines how accounting information drives organizational decision-making, incentive design, and resource allocation. Key themes include transfer pricing mechanisms, cost allocation methodologies, and the interplay between managerial and tax objectives within multidivisional firms. His theoretical models often integrate contract theory with organizational economics to address real-world coordination challenges. His publication record spans top-tier journals in accounting, finance, and economics, revealing consistent focus on performance measurement systems (35%), transfer pricing (25%), corporate governance (20%), and incentive design (20%). The research demonstrates strong methodological diversity, employing game theory (40%), mathematical modeling (30%), and empirical analysis (30%) to investigate organizational decision processes. Baldenius has held significant leadership roles including Accounting Division Chair at Columbia (2009-2011) and Accounting Department Chair at NYU Stern (2011-2016). His teaching spans MBA, MS, PhD, and executive education programs with courses covering Financial Planning & Analysis, Accounting for Consultants, and Analytical Models in Accounting. His case studies on Sub-Micron Devices Inc. and Beanie Kids Holiday Camp are widely used in accounting pedagogy.

• 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.

• 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

Dana S. NauView profile

Professor

• Automated Planning
• Game Theory
• Artificial Intelligence
• +3 more

Dana S. Nau is a Professor in the Department of Computer Science and a member of the Institute for Systems Research at the University of Maryland. He is renowned for his contributions to automated planning and game theory, including landmark algorithms like SHOP and foundational studies on game-tree pathology and strategic planning in computer bridge. With over 500 refereed publications and an H-index of 61, his work bridges theoretical computer science and practical applications in multiagent systems and evolutionary game theory. His research interests include hierarchical task network (HTN) planning, Bayesian network inference techniques, and the evolution of social norms through evolutionary game theory. Recent work focuses on spatial evolutionary games, surrogate Bayesian models, and strategic communication in multiagent environments. Awards: AAAI Fellow (202?), ACM Fellow (202?) Key Collaborations: Co-authored papers with leaders like Malik Ghallab (LAAS-CNRS), Satyandra K. Gupta (USC), and Vincent Hsiao (Bayesian networks research). Grants/Advising: Supervised students including Sunandita Patra (17+ joint papers) and Ruoxi Li, contributing to HTN planning and reinforcement learning advancements. His labs and research teams actively explore AI planning systems, probabilistic reasoning, and the intersection of game theory with social science phenomena like gossip evolution.

Maria Birna van RiemsdijkView profile

Associate Professor

• Artificial Intelligence
• Autonomous Agent Systems
• Human-AI Interaction
• +7 more

Maria Birna van Riemsdijk is an Associate Professor in Intimate Computing at the University of Twente, Netherlands. Her research focuses on developing technologies that address human vulnerability in daily life through intimate computing , blending ethics with AI and robotics. She leads the Human-Media Interaction group and contributes to the Digital Society Institute. Awards: Vidi personal grant Dutch Prize for Research in ICT 2014 2020 IEEE Computer best paper award Leadership Roles: Editorial board member, Journal of Autonomous Agents and Multiagent Systems Board member, 4TU.NIRICT (ICT research consortium) Former board member, IFAAMAS (2012-2018) Her research bridges Artificial Intelligence , Human-AI Interaction , and Healthcare , emphasizing responsible design. Recent work explores conversational agents for behavior support, ethical frameworks, and AI in healthcare contexts. Key article themes include responsible computing , conversational strategies , and adaptable AI frameworks . She has contributed to 26 total research outputs and datasets in human-agent alignment and social situation modeling.