Find Academic Supervisors

• Linguistic Theories
• Philosophical Semantics
• Multimodal Communication
• +7 more

Dr. Andy Lücking is a postdoctoral researcher at Goethe University Frankfurt, specializing in multimodal communication and cognitive semantics. He serves as Principal Investigator for the GeMDiS project within the ViCom SPP initiative, and previously held research fellowships at Université Paris Cité's Laboratoire de Linguistique Formelle and Frankfurt's Text Technology Lab. Current research focuses on neurocognitive semantics Developed iconic gesture theory with TTR/RTT frameworks Created multimodal corpora (FraGA, DoTT, TGVCorp) Active in computational educational linguistics Contributed to annotation tools (TextAnnotator, DependencyAnnotator) His work combines theoretical modeling with experimental methods, spanning over a decade of contributions to dialogue semantics, gesture-speech integration, and semantic role labeling. Recent projects explore VR-based multimodal research (Va.Si.Li-Lab) and diachronic dependency parsing. He has co-authored 20+ publications including proceedings in SemDial, LREC, and Springer HCI volumes. Collaboration network includes: Jonathan Ginzburg (dialogue theory), Alexander Mehler (computational linguistics), Alexander Henlein (VR research), and Max Planck Institute researchers. Key methodologies involve corpus creation, machine learning, and cognitive modeling of referential phenomena.

Henricus VerhagenView profile

Professor

• Artificial Intelligence
• Social Simulation
• Agent-based Modeling
• +5 more

Henricus Verhagen is a Professor and Head of the Interaction Design and Learning Unit at the Department of Computer and Systems Sciences, Stockholm University. His research spans multiple domains including computer games and gaming , computational social simulation , agent theories inspired by social science , and ethics in AI . He serves as president of the European Social Simulation Association (ESSA) and contributes to SU's digital human sciences working group and national infrastructure HumInfra. Contact: verhagen@dsv.su.se Full name usage: Uses 'Harko' in publications Research focus: AI ethics, social simulation, agent-based modeling Research Interests encompass a unique blend of technical and social aspects: agent-based simulations for collective action problems, ethical frameworks for hybrid online systems, and player retention analysis in digital games. His work bridges computational models with real-world applications in public sector AI implementation and educational technology. Research Projects include both ongoing and completed initiatives like Mixed Reality Shared Engagement in Cultural Events (SECE) and Legal & Ethical AI Framework in Healthcare under the SPARC partnership.

• Applied Data Science
• Human-centered Artificial Intelligence
• Privacy in Collaborative Systems
• +4 more

Dr. Onuralp Ulusoy is a Researcher at Utrecht University's Faculty of Science, specifically within the Software Technology for Learning and Teaching department. Based at the Buys Ballot Building in Utrecht, he focuses on the intersection of privacy, artificial intelligence, and collaborative systems. His research spans Applied Data Science and Human-centered Artificial Intelligence, with particular emphasis on privacy mechanisms in online environments. Ulusoy's work explores how privacy norms emerge and can be managed in collaborative settings, especially within social networks. His publication record shows a clear trajectory in privacy research, evolving from foundational work on privacy auctioning mechanisms to more recent applications in learning analytics. His most cited work, 'PANOLA: A Personal Assistant for Supporting Users in Preserving Privacy' (2022), demonstrates practical applications of his theoretical frameworks. Recent publications indicate an expansion into educational technology with tools like 'mAIchart' for primary school educators. As a researcher at Utrecht University, Ulusoy has established himself as a specialist in privacy-preserving collaborative systems, with publications spanning top conferences in multi-agent systems, access control, and social network analysis.

Paulus AditjandraView profile

Assistant Professor

• Sustainable Transport
• Freight Logistics
• Cold Chain
• +6 more

Paulus Aditjandra is an Assistant Professor at the Edinburgh Business School, Heriot-Watt University, focusing on sustainable transport , cold chain logistics , food value chains , and urban freight policy . He has worked on numerous UK Research Council and EU Horizon 2020 projects, including roles at Newcastle University, University of Aberdeen, and Heriot-Watt University. Education : BEng (Civil Engineering, double degree), MSc (Environmental Project Management), PhD (Transport Planning). Research Interests : Sustainable road freight, cold chain decarbonization, urban form impact on freight systems, green logistics, and food supply chain resilience. His recent work on cold chain infrastructure and zero-emission urban freight aligns with UN Sustainable Development Goals 11 (Sustainable Cities) and 12 (Responsible Consumption). He has secured £835k in grants (2022-2025) and led projects like Co-Designed Zero-Carbon Freight and VALUMICS (food systems sustainability). Awards include the Best Environmental Initiative (2015) and Bill Ogden Memorial Prize (2007). He teaches modules in Business Analytics , Green Logistics , and Quantitative Methods .

• multi-agent systems
• mathematical modeling of economic processes
• numerical methods
• +3 more

Sergey Borisovich Vasiliev is a Senior Lecturer at the Faculty of Economic Sciences, National Research University Higher School of Economics (HSE), with dual appointments in the Department of Applied Economics and Department of Project Work Support where he serves as Deputy Head of Department. He began working at HSE in 2013 and has accumulated 5 years of scientific and teaching experience. His office is located at Pokrovsky Boulevard, 11, office T607, Moscow. He holds a Master's degree in Applied Mathematics and Computer Science from HSE (2017). His language proficiency includes English, Greek, and Serbian. Vasiliev's research focuses on multi-agent systems, mathematical modeling of economic processes, and numerical methods. His work bridges economics and computational mathematics, with particular emphasis on dynamic optimization, general equilibrium models, and agent-based modeling of economic systems. He has developed models for the Russian economy, US banking system, and interbank lending networks, applying advanced mathematical techniques to complex economic problems. His teaching portfolio prominently features "Dynamic Optimization in Economics and Finance" for bachelor's and master's programs across multiple academic years, as well as "Optimization and agent models of economic processes." He teaches students in Economics and Applied Mathematics and Computer Science programs at various course levels. Gratitude from the Department of Applied Economics of the National Research University Higher School of Economics (January 2024) Vasiliev maintains an active research profile with publications spanning economics, mathematical modeling, and computational methods. His work demonstrates a strong interdisciplinary approach combining economic theory with advanced computational techniques. He is also affiliated with the Laboratory of Mathematical Modeling of Complex Systems at the Lebedev Physical Institute of the Russian Academy of Sciences since 2018, indicating his broader scientific engagement beyond HSE.

• Distributed Computing
• Cloud Computing
• Federated Learning
• +3 more

Associate Professor Bing Zhou is a Theme Leader in Distributed Computing Applications at the School of Computer Science, University of Sydney. He teaches courses such as Operating Systems Internals and Parallel and Distributed Computing , and leads research on distributed systems, cloud computing, and machine learning applications in bioinformatics. Current Research Students: Sichang DING (Spatial Multi-Omics), Quan LA (Adversarial Quantum Machine Learning) Contact: bing.zhou@sydney.edu.au | J12, Sydney University Research Interests: His work spans distributed computing, cloud optimization, bioinformatics data management, and machine learning techniques. Notable projects include DCDedupe (distributed storage optimization), FRANK (network analysis), and DomNet (protein prediction systems). Recent Publications (2022-2025): Focus on online caching algorithms, edge video processing, federated learning frameworks, and adaptive scheduling. Keywords include distributed systems, reinforcement learning, blockchain analytics, and GPU optimization. Key Collaborations: Co-authorships with researchers like D. Yuan, W. Bao, and A. Zomaya across 30+ journals and conferences.

Gaurav PatilView profile

Research Fellow

• Deep Learning
• Reinforcement Learning
• Artificial Intelligence
• +7 more

Dr Gaurav Patil is a Research Fellow at Macquarie University's School of Psychological Sciences. He specializes in computational, dynamical, and deep reinforcement learning methods to model human-agent interactions, focusing on cooperative/competitive multiagent systems and complex movement behaviors. Education: PhD in Mechanical Engineering from University of Cincinnati (2019) His research bridges psychology and AI through: Developing human-like artificial agents Analyzing navigation and decision dynamics Using VR for studying interpersonal coordination Exploring dynamical biomarkers in teams Recent work emphasizes: Deep reinforcement learning applications Human-AI behavioral congruence Swarm system control strategies Perceptual-motor primitive scaffolding He actively contributes to: Conference presentations (4 in 2023 alone) Interdisciplinary collaborations Open-access publications (10+ in 2023)

Prashant DoshiView profile

Professor

• Artificial Intelligence
• Robotics
• Multiagent Systems
• +6 more

Prashant Doshi is a Professor of Computer Science at the University of Georgia's School of Computing. He leads the THINC Lab , focusing on AI and Robotics, particularly multiagent decision-making frameworks like the Interactive POMDP (I-POMDP) . His work bridges game theory and decision theory, addressing challenges in uncertain, multiagent environments. Notable contributions include applications of I-POMDPs in counter-terrorism, defense simulations, and human behavior modeling. Doshi has published over 150 papers and holds editorial roles at Springer's Journal of AAMAS . Research interests span inverse reinforcement learning (IRL) , robotic learning from observation, SLAM in occluded settings, and semantic Web technologies. Awards include UGA’s Creative Research Medal (2011) and NSF CAREER Award (2009). He has been recognized three times with the CS Department’s Outstanding Faculty Research Award (2009, 2012, 2018). Key Projects: Open Human-Robot Collaboration Systems, I-POMDP framework development, cybersecurity intent recognition. Grants: NSF CAREER Award, Collaborative Research grants on multiagent systems. Labs: THINC Lab (focusing on human-robot interaction and decision-making). Recent work explores open multiagent systems , where agents dynamically join/leave, and occluded IRL for robots learning from partial observations. His research has practical applications in disaster response robots, healthcare resource allocation, and autonomous vehicle decision-making.

• Transportation
• Logistics
• Supply Chains
• +6 more

Assoc Prof Kok Choon Tan is an Associate Professor in the Department of Analytics and Operations at the NUS Business School. He holds a Deputy Director role at the Centre for Maritime Studies (CMS), Singapore. His research focuses on container terminal operations optimization, maritime logistics, and simulation-based decision-making. He has been with NUS since 1984, starting as a Senior Tutor in Mathematics, and later earning a Post-Graduate Diploma in Teaching in Higher Education (PG DipTHE) to enhance his pedagogical skills. Research Interests: Transportation and logistics optimization, applied mathematics, operations research modeling, and maritime systems. He leads the Port Operations Modelling & Analysis track at CMS, focusing on container terminal efficiency through mathematical optimization and simulation. Teaching Philosophy: Emphasizes student-centered learning, active learning strategies (e.g., collaborative learning, case studies), and bridging theory to real-world applications. His teaching integrates problem-solving, critical thinking, and presentation skills development through group projects and industrial case studies. Recent Research Trends: His articles address AGV scheduling, container relocation under uncertainty, and multi-modal port operations. These contributions highlight innovations in automated systems, data-driven decision-making, and sustainability in port logistics. Labs/Teams: Active in the NUS Centre for Maritime Studies and collaborates with departments in Industrial Systems Engineering and Civil & Environmental Engineering. His work supports Singapore’s maritime and logistics industry through applied research and strategic planning.

Sean LukeView profile

Professor

• Evolutionary Computation
• Genetic Programming
• Multi-agent Systems
• +13 more

Sean Luke is a Professor in the Department of Computer Science at George Mason University (GMU) and serves as Associate Director of the Center for Social Complexity at the Krasnow Institute. He leads the GMU Evolutionary Computation Laboratory (ECLab) and is actively engaged in research at the intersection of artificial intelligence, evolutionary computation, and multi-agent systems. His work spans robotics, music technology, simulation, and knowledge representation. Position: Professor, Department of Computer Science, GMU Leadership: Associate Director, Center for Social Complexity Laboratory: ECLab – GMU’s Evolutionary Computation Laboratory Research Focus: Multi-agent systems, evolutionary algorithms, swarm robotics, computational creativity in music, agent-based modeling Sean Luke's research interests center on evolutionary computation, genetic programming, and multi-agent simulation. He has made foundational contributions to the development of MASON, a widely used Java-based multi-agent simulation toolkit, and ECJ, a general-purpose evolutionary computation framework. His work in computational creativity explores how AI can assist in music synthesis and patch design, culminating in the open-access textbook Computational Music Synthesis . He also investigates swarm robotics, human-agent collaboration, and optimization in complex systems such as supply chains. His most recent publications (2020–2024) reflect a strong trend toward interdisciplinary applications of AI and simulation. These include co-creative music systems, planner-guided robot swarms, and agent-based modeling for supply chain resilience. His work frequently appears in top venues such as GECCO, AAMAS, and IJCAI, and emphasizes open science through freely available software and textbooks. Sean Luke has mentored numerous students and researchers, including William Squires, Drew Wicke, Ermo Wei, and Matteo D'Auria, who have co-authored significant works in multi-agent learning, swarm robotics, and model calibration. He has also been involved in the RoboPatriots RoboCup team, demonstrating practical applications of AI in robotics competitions. Key Projects: MASON, ECJ, RoboPatriots, Computational Music Synthesis Open Resources: Essentials of Metaheuristics , Computational Music Synthesis Luke’s work is supported by a strong track record of publications and technical reports, with recent efforts focusing on improving fairness, scalability, and usability in AI systems. He continues to advance the state of the art in evolutionary algorithms and multi-agent learning, with a growing emphasis on real-world applications and human-AI collaboration.

Alina HawkinView profile

Researcher

• Robotics
• Artificial Intelligence
• Virtual Reality
• +3 more

Alina Hawkin is a researcher at the Department of Computer Science, University of Bremen. Her work focuses on teaching robots new manipulation tasks through human demonstrations in Virtual Reality (VR) and leveraging their prior experiences for autonomous execution. Key Projects: EASE, Knowledge 4 Retail, BMWi SMILE, go4IT Robotic Platforms: PR2 (Willow Garage), HSR (Toyota), Pepper (Softbank), TIAGo (PAL Robotics) Research Interests: Combines robotics, AI, and VR to develop knowledge-based systems for tasks like retail assistance and meal preparation. Emphasizes semantic digital twins, dynamic query generation, and transient state modeling. Publications: Recent works include cloud-integrated robotic solutions for retail (2024), motion parameterization from human VR demonstrations (2020), and semantic digital twin-based shopping assistants (2023).

Scott DeLoachView profile

Professor

• Multiagent Systems
• Distributed Systems
• Software Engineering
• +5 more

Scott DeLoach is a Professor and Department Head in the Department of Computer Science at Kansas State University's College of Engineering. He holds a B.S. in Computer Engineering from Iowa State University (1982), and M.S. (1987) and Ph.D. (1996) degrees in Computer Engineering from the Air Force Institute of Technology. Before joining K-State in 2001, he served 20 years in the U.S. Air Force, working at the Aeronautical Systems Division, 544th Strategic Intelligence Wing, Air Force Research Laboratory, and Air Force Institute of Technology. He became interim department head in 2014 and permanent head in 2016, serving until his scheduled retirement in June 2025. His research applies software engineering methodologies to intelligent, adaptive multiagent and distributed systems, with current focus areas including: Runtime/design-time models for smart grid and power distribution systems Adaptive network security using runtime models Formal specification of agent-oriented systems Self-tuning autonomous systems through organizational policies DeLoach's publications (20+ journal articles, 75+ conference papers) predominantly explore multiagent systems, adaptive security, and formal verification methods, demonstrating consistent focus on theoretical foundations with practical applications in critical infrastructure. Awards & Honors: National Science Foundation CAREER Award (2004) K-State College of Engineering Frankenhoff Outstanding Research Award (2011) K-State Outstanding Department Head Award (2021) He has advised over 30 graduate students, including 7 Ph.D. graduates, primarily through the Multi-Agent & Cooperative Robotics (MACR) Laboratory . His leadership includes editorial duties for the International Journal of Agent-Oriented Software Engineering (since 2005) and participation in numerous program committees.

Akshat KUMARView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Multiagent Systems
• +4 more

Akshat Kumar is an Associate Professor (Research Track) in the School of Information Systems at Singapore Management University (SMU). He holds a PhD in Computer Science from the University of Massachusetts Amherst (2013) and was previously a Research Scientist at IBM Research India. Research Focus : His work lies at the intersection of AI, Machine Learning, and Multiagent Systems, with applications in urban mobility optimization (e.g., autonomous vehicles, maritime traffic management), decision-making under uncertainty, and computational sustainability. He leads the Representation, Learning, and Reasoning (RLR) Lab, which develops algorithms for large-scale multiagent coordination using reinforcement learning and probabilistic inference. Awards & Grants : Recipient of the Lee Kong Chian Fellowship (2020-22), Best Paper Awards at AAAI (2017) and ICAPS (2014), and featured in IEEE’s 'AI’s Ten to Watch' (2018). Principal Investigator (PI) of Singapore MOE Tier-2 grants totaling S$1.1M for projects like 'Data Driven Collective Decision Making For Urban System Optimization' (2019–2021). Education & Teaching : Taught courses on computational thinking, artificial intelligence, and spreadsheet modeling. Advises PhD students and research engineers on topics like reinforcement learning, maritime traffic simulation, and cloud security policy design. Impact : His research addresses challenges in urban systems, such as optimizing autonomous taxi fleets, reducing maritime congestion, and improving smart grid management. Collaborations include Fujitsu-SMU Urban Computing Lab and Singapore port authorities.

Jerome Bernard DarbonView profile

Associate Professor

• Hamilton-Jacobi Equations
• Imaging Sciences
• Optimal Control
• +7 more

Jerome Darbon is an Associate Professor of Applied Mathematics at Brown University, specializing in Hamilton-Jacobi equations, imaging sciences, optimal control, and optimization. His research emphasizes developing efficient algorithms for variational estimations, combinatorial optimization, and stochastic sampling, with applications in remote sensing, geomorphology, and medical imaging. He holds a Ph.D. from École Nationale Supérieure des Télécommunications (Paris, 2005) and has been recognized with awards including the CNRS Prime d’Excellence Scientifique (2010-2014) and the UCLA Chancellor’s Award for Postdoctoral Research (2009). His work bridges theoretical mathematics with practical computational methods, addressing high-dimensional problems through innovative approaches like neural network architectures and algorithm-architecture co-design. Research Interests: Hamilton-Jacobi PDEs and their applications in control theory Imaging sciences, including denoising and image restoration Optimization techniques for compressive sensing and inverse problems Algorithm development for parallel architectures Key Contributions: Developed methods to overcome the curse of dimensionality in Hamilton-Jacobi equations Advanced landscape evolution models using PDE-based simulations Contributed to SAR image regularization and InSAR phase reconstruction Awards and Grants: NSF Grant DMS 1820821 (2018-2021) for work on variational decomposition models ONR Grant N00014-11-1-0749 (2011-2014) for combinatorial scientific computing Teaching: Courses include Applied PDEs, Numerical Optimization, and Computational Linear Algebra.

Michael BarlowView profile

Professor

• Serious Games & Games Technology
• AI & Multi-Agent Systems
• Simulation & Virtual Environments
• +4 more

Professor Michael Barlow is a distinguished academic at The University of New South Wales , specifically affiliated with UNSW Canberra and the School of Systems & Computing . His work spans multiple disciplines, including Artificial Intelligence , Multi-Agent Systems , Simulation & Virtual Environments , and Trusted Autonomy . Barlow’s research delves into Machine Learning and Human-Computer Interaction , with a particular focus on Speech Science and Technology in earlier stages of his career. University: The University of New South Wales School: School of Systems & Computing Role: Professor and Head of School His research interests include Serious Games , AI & Multi-Agent Systems , Trusted Autonomy , and Human-Computer Interaction . He has pioneered work in Swarm Intelligence and Simulation Technologies , applying these to domains such as military training , unmanned vehicle coordination , and game design . Barlow’s publications reveal a consistent trend in interdisciplinary work, blending Artificial Intelligence with Human Factors . His recent studies focus on Human-Swarm Interaction and Behavioral Metrics in multi-agent systems, while earlier works explore evolutionary game theory , speech processing , and virtual environments . He has contributed extensively to teaching in Core Computer Science for undergraduates and postgraduates, with specialized courses in Games & Serious Games , Simulation Graphics , and Algorithms . His consulting interests align with his research, emphasizing Simulation , Virtual Environments , and AI/Agent Systems .