جست‌وجوی استاد و پژوهشگر

Antonio A. Sánchez Ruiz-Granadosمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Video Games
• +۴ مورد دیگر

Antonio A. Sánchez Ruiz-Granados is an Associate Professor at the Complutense University of Madrid in the Department of Software Engineering and Artificial Intelligence, Faculty of Computer Science. He teaches courses on data structures, algorithms, human-computer interaction, video game programming, and artificial intelligence. Research Focus : AI in video games, knowledge representation, machine learning, user modeling, and case-based reasoning Key Projects : AI for game behavior, user modeling in games, decentralized peer review systems His recent publications span collaborative AI in games, VQA methods, diabetic retinopathy diagnosis, dynamic difficulty adjustment, and explainable CBR systems. Notable work includes flow induction in Tetris, Siamese network similarity analysis, and blockchain-based peer review ecosystems. While no explicit awards are listed, his work demonstrates leadership in game AI and open science initiatives. He has organized workshops and contributed to CBR research through proceedings editorship.

• Artificial Intelligence
• Knowledge-Based Systems
• Decision Support Systems
• +۹ مورد دیگر

Carlos Fernando da Silva Ramos is a Full Professor at the School of Engineering , Polytechnic Institute of Porto (ISEP/IPP), with over 30 years of experience in Artificial Intelligence and Smart Systems . He holds a PhD and Habilitation in Electrical and Computer Engineering from the University of Porto and has held leadership roles including Vice-President for R&D at IPP and Pro-President for International Relations. His research spans AI Planning , Multiagent Systems , and Smart Grids , with applications in Energy Systems , Smart Cities , and Tourism . He founded GECAD, an FCT-ranked Excellent R&D unit, and contributes to LASI, Portugal's AI Associated Lab. Recent work focuses on Electricity Market Simulation , Smart Grid Data Management , and Context-Aware Tourism , as evidenced by high-impact publications in IEEE , Elsevier , and Springer venues. His projects include LAPASSION (ERASMUS+, €999k), MUWO (ITEA3, €7.478M), and ARANOUA (Samsung, €144k). Scientific Awards: 2024 Stanford Top 2% Scientist Ranking He has supervised 13 completed PhD projects and 2 ongoing , with grants from FCT, European Commission, and industry partners. His lab, GECAD, leads research in Intelligent Engineering and Computing for Advanced Innovation .

• Artificial Intelligence
• Machine Learning
• Autonomous Agents and Multiagent Systems
• +۷ مورد دیگر

Professor Mirco Musolesi is a leading academic in Computer Science at both University College London (UCL) and the University of Bologna . He directs the Machine Intelligence Lab at UCL, which is affiliated with the UCL Centre for Artificial Intelligence and the Intelligent Systems Group . His research spans multiple disciplines including AI, cybersecurity, and computational modeling of human behavior. PhD from University College London (2007) Laurea from University of Bologna (2002) Research Interests : Mechanisms for autonomous decision-making in single/multi-agent systems AI ethics, societal impacts of LLMs, and moral alignment Machine learning for mobile/cyber-physical systems Intersections of AI with cybersecurity, privacy, and computational social science Recent Article Trends : His work focuses on reinforcement learning applications, causal discovery through graph-based methods, and ethical frameworks for AI systems. Emerging themes include creativity assessment in LLMs, cost-aware urban resource allocation, and conflict modeling through game-theoretic approaches. Teaching Contributions : Autonomous and Adaptive Systems (U. Bologna, Spring 2023-25) Engineering Challenges (UCL, Winter 2020-25) Research Methods (UCL, 2021-24) External Examiner roles at King's College London and U. Sussex

• Complexity Sciences
• Quantum Technologies
• Artificial Intelligence
• +۴ مورد دیگر

Carlos Pedro dos Santos Goncalves is an Associate Professor at Lusofona University's School of Economic and Organizational Sciences. His research focuses on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Intelligence and Security, FinTech, and Financial Risk Modeling. He is a programmer with expertise in Quantum Computing (Qiskit/IBM Quantum), Python-based AI/ML, and Netlogo for multiagent systems. His work includes open-source contributions such as the Strategy Analyzer AI module and QNeural quantum neural network simulator, both preserved in GitHub's Arctic Code Vault. He maintains an active GitHub profile (https://github.com/cpgoncalves) with repositories like Analytics-Engine and Quantum-Cybersecurity.

• Big Data Analytics
• Computational Social Science
• Political Economy
• +۱ مورد دیگر

Nicholas Seltzer is an Associate Professor in the Department of Political Science at the University of Nevada, Reno. He holds a Ph.D. in Political Science from Stony Brook University (2014), an M.A. in National Security Policy from George Washington University (2007), and a B.A. in Philosophy and Political Science from University of California, Davis (2003). Prior to academia, Seltzer worked in the defense industry on projects including early warning systems for political instability. Seltzer's research employs computational approaches to social science, including multiagent simulation, geographic information systems, and big data analytics. Key research areas include the evolution of cooperation and conflict, collective action problems, emergence of social complexity, social media networks, and biopolitics. His work examines climate change responses, tribal conflict dynamics, and political attitude formation through interdisciplinary frameworks combining political science, economics, and evolutionary biology. Seltzer's publications demonstrate consistent focus on social dynamics in environmental and political contexts. Recent work examines climate justice, cooperation in social networks, and pastoralist conflicts in East Africa. Methodologies include behavioral experiments, computational modeling, and cross-cultural comparisons. At UNR, Seltzer teaches courses on world politics and mass media in American politics. His research bridges political theory with computational methods, analyzing complex social systems through agent-based modeling and network analysis.

Enric Plaza Cerveraمشاهده پروفایل

استاد پژوهشی

• Case-Based Reasoning
• Multiagent Learning
• Conceptual Blending
• +۴ مورد دیگر

Enric Plaza Cervera is a Research Professor at the Learning Systems Department of the Artificial Intelligence Research Institute (IIIA-CSIC) in Catalonia, Spain. His work focuses on foundational aspects of artificial intelligence, particularly in conceptual blending, case-based reasoning (CBR), and multiagent systems. He explores how cognitive principles like image schemas and conceptual blending can be applied to computational models of creativity, semantic understanding, and diagrammatic reasoning. His research also addresses ethical challenges in AI governance and value alignment through agent-based simulations and formal models. Key research areas include: Formalizing cognitive processes in AI for diagram interpretation and creativity Developing ethical frameworks for autonomous systems using AGV (Autonomy-Governance-Value) models Advancing CBR theory through amalgamation techniques for integrating multiple solutions Modeling embodied cognition in understanding abstract concepts through spatial metaphors Recent publications (2020-2024) emphasize interdisciplinary approaches combining cognitive science, formal logic, and multiagent systems to tackle challenges in AI transparency, value alignment, and creative problem-solving. No scientific awards are explicitly mentioned in the provided materials. His work contributes to both theoretical advancements and applied AI systems through the IIIA's research initiatives.

Peter Stoneمشاهده پروفایل

استاد

• Reinforcement Learning
• Multiagent Systems
• Robotics
• +۷ مورد دیگر

Peter Stone is a Professor of Computer Science at The University of Texas at Austin, holding the Truchard Foundation Chair. He leads the Learning Agents Research Group (LARG) within the Artificial Intelligence Laboratory and serves as Director of Texas Robotics and Associate Department Chair. His research focuses on reinforcement learning, multiagent systems, and robotics, emphasizing adaptive and interactive intelligent agents. Stone earned his Ph.D. from Carnegie Mellon University and has held roles at Sony AI as Chief Scientist and Cogitai, Inc. as co-founder. Education: Ph.D. in Computer Science (Carnegie Mellon University, 1998), B.S. in Mathematics with Computer Science (University of Chicago, 1993). Research Interests: Reinforcement Learning, Multiagent Systems, Robotics, AI Planning, and Ethical AI. His work addresses challenges in autonomous agents, including robot soccer, autonomous vehicles, and Gran Turismo racing, often leveraging real-world applications. Recent Articles: Focus on reinforcement learning advancements, multiagent coordination, and real-world robotics deployments. Notable works include champion-level autonomous driving agents and proto successor measure theory. Awards: ACM/SIGAI Industry Award, multiple Sony Technology Awards, ACM and IEEE Fellowships, and teaching accolades like the Minnie Stevens Piper Professorship. Advising: Supervised over 50 Ph.D., master’s, and undergraduate students, contributing widely to AI and robotics research. Current projects include the UT Austin Villa robot soccer team and Sony AI collaborations. Labs/Teams: LARG, Texas Robotics, and Sony AI. Active in RoboCup competitions and AI policy initiatives like the One Hundred Year Study on Artificial Intelligence.

Thomas Baarمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Formal Verification
• Model-Driven Engineering
• +۳ مورد دیگر

Prof. Dr. Thomas Baar is a Professor at HTW Berlin, specializing in cyber-physical systems, formal verification, and model-driven engineering. His research focuses on hybrid systems, automated driving platforms like CeCar, and improving usability of verification tools such as KeYmaera. He contributes to software engineering education and legacy system modernization through domain-specific languages (DSLs) and graphical editors. Baar's work spans academia and industry, with collaborations in aerospace safety, multiagent systems, and cybersecurity for control systems. His research interests include formal methods for hybrid systems, software reliability, and educational platforms for autonomous systems. He has published extensively on topics like verification frameworks, syntax improvements for formal tools, and safety analysis methodologies. His interdisciplinary approach bridges theoretical computer science with practical applications in aerospace, automotive, and industrial automation. Key contributions include the CeCar platform for autonomous driving research, modularization enhancements for KeYmaera, and DSL-based solutions for legacy software maintenance. Baar collaborates with institutions like the IFAF Berlin and participates in EU-funded projects focusing on smart cities and sustainable technologies. His publications reflect a strong emphasis on verification techniques, with over 15 peer-reviewed articles since 2015. He is affiliated with the HTW Berlin's Wilhelminenhof Campus and actively engages in knowledge transfer initiatives to bridge research and industry needs.

Marc Zimmermannمشاهده پروفایل

مدرس

• Mathematics Education
• Chemistry Education
• Didactics
• +۳ مورد دیگر

Marc Zimmermann is a Lecturer and Campus Manager at Ludwigsburg University of Education. He holds a Master's degree in subject didactics (mathematics, physics) and has extensive experience in education and academic administration. His roles include serving as a Senate Elected Member and coordinating the introduction of HISinOne university management software. Zimmermann has held positions as a Research Associate and Lecturer at the Institute of Mathematics and Computer Science, with additional academic staff roles at the University of Economics and the Environment Nürtingen-Geislingen. Educational background includes a first state examination for teaching secondary schools (history, mathematics, physics) and advanced studies in mathematics and physics didactics. His research focuses on mathematics education innovation, including intelligent assessment tools, active learning strategies, and didactic frameworks for STEM subjects. Notable projects include the SAiL-M project addressing teaching methodologies and the development of the 'open math room' concept for active learning environments. Zimmermann’s work emphasizes bridging theory and practice in education through technology integration, such as e-learning tools and lecture recordings. His recent publications explore chemical reaction mechanisms, self-efficacy in mathematics learners, and conceptual understanding in STEM fields. He has contributed to curriculum development across multiple institutions and remains active in improving teaching quality through collaborative academic initiatives.

• Applied Mathematics
• Differential Equations
• Impulsive Systems
• +۷ مورد دیگر

Jianhua Shen is a Professor at Nanjing University of Posts and Telecommunications (NJUPT), School of Computer Science and Engineering, with a distinguished research career spanning over 30 years. His academic journey shows a natural progression from theoretical mathematics to applied computer science and educational technology. His research interests encompass Applied Mathematics , Differential Equations , Impulsive Systems , Stability Analysis , Computer Networks , Wireless Communication , Educational Technology , and Machine Learning . Shen's work demonstrates remarkable adaptability while maintaining mathematical rigor, evolving from foundational theoretical work to practical applications in modern computing and education. Shen's recent publications (2020-2025) reveal a strong focus on educational technology and federated learning , with significant contributions to virtual simulation experiments, MOOC platforms, and personalized learning systems. His work bridges theoretical computer science with practical educational applications, reflecting NJUPT's emphasis on technology-enhanced education. As an advisor, Shen has mentored numerous students including Meijuan Chen, Cong Yu, and Xiaoling Liu, who frequently appear as co-authors on his publications. His collaborative network extends across multiple departments at NJUPT and includes researchers from various Chinese institutions.

Paul Wiegandمشاهده پروفایل

دانشیار

• Machine Learning
• Optimization
• Natural Computation
• +۳ مورد دیگر

R. Paul Wiegand is an Associate Professor in the Department of Computing & Information Sciences at Winthrop University's College of Business Administration. He holds a Ph.D. in Computer Science from George Mason University (2004), an M.S. from the University of North Carolina-Charlotte (1999), and a B.S. from Winthrop University (1996). His research focuses on machine learning, optimization, natural computation, multiagent systems, and probabilistic reasoning, with recent work exploring novelty search algorithms and coevolutionary methods. He has held roles at the University of Central Florida and the Navy Center for Applied Research in Artificial Intelligence. Dr. Wiegand's pedagogical approach emphasizes contextual learning and student engagement. He actively organizes academic events like the Winthrop SMACS Programming Competition and co-leads the interdisciplinary Mathematics & Computer Science student seminar. His research projects include NSF-funded work on coevolutionary peer-instruction systems and DoD-funded smart network routing algorithms. He also explores foundational theory for swarm-based task allocation and decentralized systems. Key research contributions include studies on robust path tracking, evolutionary programming for Parsons puzzles, and multiagent learning dynamics. His work bridges theoretical computer science with practical applications in education, robotics, and network optimization. Beyond academia, he plays in the bands Read-Only Time Travel and PhyNight , contributing to local music scenes in South Carolina.

Kathleen Keoghمشاهده پروفایل

مدرس

• Artificial Intelligence
• Multiagent Systems
• Human Behavior Modeling
• +۳ مورد دیگر

Dr. Kathleen Keogh is a Lecturer in Information Technology at Federation University Australia, specializing in intelligent software agents and multiagent systems. She coordinates the Bachelor of IT (Professional Practice) program, integrating industry internships with IBM and Kyndryl. Her research focuses on modeling human behavior through agent-based systems, particularly in dynamic environments requiring improvisation. She holds a PhD from the University of Melbourne (2019), with prior qualifications including a Master of Science (2002) and Bachelor of Science (Honours) (1988). Education: PhD (Computer Science), University of Melbourne (2019) MSc (Cognitive Science), University of Melbourne (2002) BSc(Hons) (Computer Science), James Cook University (1988) DipEd (Adult Education), Australian Catholic University Research Interests: Her work emphasizes agent coordination in complex scenarios, such as emergency management simulations. She explores organizational constructs enabling autonomous agents to adapt dynamically, contributing to sociotechnical systems analysis. Recent studies include familiarity-based team recognition in academic networks and runtime flexibility in multiagent systems. Teaching & Industry Collaboration: Dr. Keogh teaches programming, software engineering, and capstone projects using Scrum methodologies. She manages industry partnerships for work-integrated learning programs, ensuring students gain practical experience while studying. Labs & Collaborations: Involved in interdisciplinary projects with IBM and Kyndryl, focusing on cloud and enterprise computing. Her research integrates computational models of human expertise, such as disturbance management in healthcare.

• Agent-Based Modeling
• Insurance Markets
• Catastrophe Risk Management
• +۳ مورد دیگر

Teresa Bi is a Researcher and Postdoctoral Research Associate affiliated with the Informatics Overview Network. Her work focuses on agent-based modeling and simulation, particularly in analyzing ambiguity within catastrophe insurance markets and multi-agent systems. Her research interests include the intersection of computational models, risk management, and economic decision-making under uncertainty. She has contributed to advancing methodologies for understanding complex insurance market dynamics through agent-based approaches. Bi’s recent work, accepted to the 2025 AAMAS Conference, explores ambiguity’s impact on catastrophe insurance markets, highlighting interdisciplinary applications of computer science and actuarial science.

Chun Wangمشاهده پروفایل

استاد

• Sustainable Mobility Systems
• Eco-friendly Transportation Networks
• Computational Social Simulation
• +۴ مورد دیگر

Dr. Chun Wang is a Professor and Director of the Concordia Institute for Information Systems Engineering at Concordia University. His research focuses on Sustainable, Smart, and Socially-Oriented Mobility Systems, emphasizing eco-friendly solutions that enhance community well-being and reduce environmental impact. His work integrates computational social simulation, game theory, and multiagent systems to address challenges in electrification, decarbonization, and supply chain optimization. Key research areas include mobility systems design, scheduling algorithms, two-sided matching mechanisms, and e-supply chain management. His interdisciplinary team develops frameworks for ride-hailing systems, crowd-sourced delivery, and electric vehicle charging networks, with an emphasis on privacy preservation and uncertainty management. Recent publications (2021–2023) highlight advancements in auction-based scheduling, data-driven optimization for car-sharing, and privacy-preserving matching mechanisms. The lab’s work bridges theoretical models with practical applications in smart cities and sustainable infrastructure. Dr. Wang leads the Sustainable, Smart, and Socially-Oriented Mobility Systems Lab, fostering collaborations across engineering, computer science, and urban planning disciplines. His contributions span transportation networks, energy systems, and healthcare operations, with a focus on scalable and socially responsible solutions.

Jamie Matthewsمشاهده پروفایل

مدرس ارشد

• Interactive Storytelling
• Narrative Generation
• Mise-en-scène
• +۳ مورد دیگر

Dr. Jamie Matthews is a Senior Lecturer in Games Development at the Department of Computing & Games, Teesside University, affiliated with the Centre for Digital Innovation. His research focuses on interactive storytelling, narrative generation, and virtual student behavior modeling. He holds a Doctoral Thesis in Crowd Simulation for Interactive Entertainment Applications (2021). Education: PhD in Computer Science (2021) from Teesside University, supervised by Prof. John Porteous and Dr. Christopher Jayne. Research interests include Mise-en-scène techniques for narrative actions, benchmarking frameworks for virtual agents, and semantic representation in storyworlds. His work bridges computer science and digital arts, emphasizing procedural storytelling and multiagent systems. Publications span conference contributions on virtual student behavior benchmarks and narrative staging systems. His MISER framework has been highlighted in multiagent systems research. Awards: No specific honors listed. Active in grant-funded projects related to interactive entertainment applications. Labs/Teams: Involved with the Centre for Digital Innovation, focusing on digital innovation in games and interactive technologies.