Find Academic Supervisors

• Artificial Intelligence
• Computer Graphics
• Virtual Reality
• +3 more

Carlos Cglez-Morcillo is an Associate Professor at the Higher School of Computer Science, University of Castilla-La Mancha (Spain), with an active career in academia since 2002. He holds a European PhD in Computer Science (2007) and a degree in Computer Science (2002) with an Extraordinary End-of-Degree Award. Currently, he serves as Academic Director of the Vice-Rectorate of Digital University and Director of the G9 Shared Digital Campus, while also being a founding member of the AIR Research Group and Creative Director of the university spin-off Furious Koalas. PhD in Computer Science (2007) BSc in Computer Science (2002) Technical Engineer in Computer Systems (2000) Research interests include Artificial Intelligence, Computer Graphics, and their applications in rehabilitation technology and educational innovation. His work spans mixed reality systems for stroke recovery, gamification in learning environments, and 3D rendering optimization. He has led 9 research projects with over €550,000 in funding and contributed to over 30 technology transfer initiatives. Recent publications focus on VR/AR applications for neurological rehabilitation, e-commerce metaverse environments, and AI-driven educational tools. His 15 most recent articles reflect interdisciplinary work bridging computer science with healthcare and business innovation. Scientific recognition includes being the first Spaniard to obtain the Blender Foundation Certified Trainer (2009) and leading award-winning projects like ICEIS 2025 Best Student Paper. He actively participates in conferences and media outreach, demonstrating commitment to public engagement through platforms like Naukas and CMM Radio.

• Multiagent Systems
• Agent Architecture
• Agent-based Simulation
• +7 more

Julian Padget is a Reader (equivalent to Associate Professor) in the Department of Computer Science at the University of Bath, with extensive affiliations across multiple research centers including the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa), Water Innovation and Research Centre (WIRC), UKRI CDT in Accountable, Responsible and Transparent AI, Centre for Therapeutic Innovation, and Institute for Digital Security and Behaviour (IDSB). His work bridges computer science with energy systems, healthcare, and digital governance through interdisciplinary collaborations. Padget's research centers on multiagent systems , agent architecture , norm representation and reasoning , and fusing symbolic and statistical AI , with significant contributions to distributed ledgers, policy modeling, and narrative models. His fingerprint analysis reveals dominant connections to multi-agent systems (100%), web services (72%), and normative frameworks (48%), reflecting his focus on creating ethically aligned autonomous systems for complex socio-technical environments. Recent work demonstrates increasing integration of AI with energy infrastructure and biomedical applications. Analysis of his 15 most recent publications shows a clear trajectory toward operationalizing AI ethics, particularly in bias management and trust frameworks, while maintaining strong foundations in multiagent coordination. His energy sector research increasingly focuses on digital spine architectures for data sharing, and biomedical collaborations explore molecular imaging techniques for cancer research. The consistent thread across domains is the development of governance frameworks for autonomous systems. Padget actively supervises doctoral students with 23 supervised works documented and serves as Principal Investigator on major grants including EPSRC-funded energy network projects (2025-2026) and Innovate UK collaborations with the BBFC. His policy impact is evidenced by parliamentary testimony in March 2025 that generated coverage across 16 news outlets. Current projects emphasize AI for agile energy networks, value-aware agent architectures, and statutory compliance frameworks for online media. His laboratory ecosystem spans the IAAPS Innovation Bridge and Institute for Digital Security and Behaviour, focusing on translating theoretical agent frameworks into practical applications for energy systems, digital governance, and health interventions. The Water Innovation and Research Centre provides critical infrastructure for his energy-related simulations, while therapeutic innovation collaborations enable biomedical applications of his norm-representation frameworks.

Christof WittwerView profile

Academic

• Smart Grids
• Renewable Energy Systems
• Energy Management
• +3 more

Prof. Christof Wittwer is Director of the Business Area 'System Integration' at Fraunhofer Institute for Solar Energy Systems (ISE) in Freiburg. He holds an honorary professorship at the University of Freiburg's Faculty of Environmental and Natural Resources, contributing to master’s programs in Renewable Energy Engineering and Management. His career includes roles as a researcher, postdoc, and department head at Fraunhofer ISE, focusing on distributed energy systems, grid integration, and control engineering. Education: Diploma in Electrical Engineering (University of Kaiserslautern) Key Roles: Director of System Integration, Honorary Professor, and former Head of 'Smart Grids' Department Research: Smart Grids, Energy Management, and System Simulation His research emphasizes system integration of renewable energy, grid resilience, and decentralized energy systems. Notable projects include the Fraunhofer Cluster of Excellence for Integrated Energy Systems (CINES) and contributions to the C/sells initiative for future energy systems in Southern Germany. Publications span smart grid controls, stochastic optimization, and renewable energy policy, with a focus on practical implementation and system-level solutions.

• Climate Change
• Risk Finance
• Disaster Resilience
• +3 more

Swenja Surminski is a Professor in Practice at the Grantham Research Institute on Climate Change and the Environment, LSE. She also serves as Managing Director for Climate and Sustainability at Marsh McLennan and chairs the Munich Climate Insurance Initiative. Her expertise spans climate adaptation, risk finance, disaster resilience, and Loss and Damage policy. She advises the UK Committee on Climate Change and leads projects like the EU Naturance initiative and the Climate Resilience Alliance. Surminski holds a PhD in Political Science from Hamburg University and has published extensively on climate risk, insurance mechanisms, and resilience dividends. Her work bridges academia, policy, and industry, focusing on transformative climate adaptation strategies. Education: PhD in Political Science, Hamburg University (2002), Fulbright Scholar at University of New Hampshire. Affiliations: Grantham Research Institute, Marsh McLennan, Munich Climate Insurance Initiative (Chair). Research Interests: Climate risk finance, adaptation co-benefits (Triple Resilience Dividend), nature-based solutions, private sector adaptation, and UNFCCC policy. Her research emphasizes integrating risk reduction with sustainable development, particularly through insurance and policy frameworks. Recent work explores flood resilience in urban areas and environmental justice in housing vulnerability. Policy Contributions: Co-author of UK Climate Change Risk Assessments, advisor to Bank of England, and contributor to IPCC reports. Her policy briefs inform flood risk management in mature economies (e.g., UK, Germany, US) and advocate for equitable climate adaptation strategies.

Miguel Molina SolanaView profile

Associate Professor

• Artificial Intelligence
• Data Science
• Energy Management
• +7 more

Dr. Miguel Molina-Solana is an Associate Professor (Prof. Titular) at the Department of Computer Science and AI, Universidad de Granada (Spain) and Honorary Research Fellow at Imperial College London's Data Science Institute. He holds a PhD in Computer Science and AI from Universidad de Granada (2008-2012) and an MSc in Computer Science from the same institution (2002-2007). His academic journey includes roles as Marie Curie Research Fellow (2017-2019 at Imperial College), Research Associate at the Data Science Institute (2015-2017), and postdoctoral researcher at UGR (2012-2015). Research focuses on Artificial Intelligence , Data Science , Energy Management , and Disinformation Analysis . Notable projects include SINERGY (deep learning for energy simulation), IBERIFIER (EU-funded disinformation observatory), and IA4TES (AI applications for sustainable energy transition). He co-leads the SAIL Lab at UGR and has led research groups in visualization and energy systems. Publications span Angewandte Chemie , Energy and Buildings , and Applied Soft Computing , covering topics like physics-informed neural networks, HVAC control optimization, and Telegram-based disinformation analysis. His work bridges machine learning with domain-specific challenges in energy, music informatics, and smart built environments. Outreach activities include science communication projects (e.g., 'The Sound of Mars' art installation) and education initiatives through Native Scientist. Current roles involve advising PhD students on energy and AI projects, with active grants from Spanish and EU programs. Labs/Teams: SAIL Lab (Universidad de Granada), Data Science Institute (Imperial College London collaborations), and interdisciplinary teams in energy and disinformation research.

• Multiagent Systems
• Artificial Intelligence
• Game Theory
• +4 more

Julian Garcia is an Associate Professor in the Department of AI and Data Science at Monash University's Faculty of Information Technology. His research focuses on understanding how self-interested agents (human and machine) coordinate actions without central planners, leveraging game theory and simulations. Key areas include multiagent systems, AI, social behavior dynamics, and human-technology intersections. Teaching responsibilities include computer science, algorithms, and computational modeling. He contributes to the Optimization group within his department. No scientific awards or grants are explicitly listed in the provided text. Research emphasizes evolutionary dynamics and agent-based modeling, evidenced by GitHub repositories like pyevodyn and game_theory , though these are not formal articles. No advising or lab affiliations beyond the Optimization group are detailed.

Sz-Ting TzengView profile

Academic

• Artificial Intelligence
• Multiagent Systems
• Human-Centric AI
• +4 more

Sz-Ting Tzeng is a Postdoctoral Fellow at the Department of Computer Science , Umeå University , Sweden. Her research focuses on socially aware AI , multiagent systems , human-centric AI , and AI ethics . Research Trends: Her recent publications (2024-2025) analyze value-based decision-making frameworks in multiagent systems, ethical AI, and social experience modeling through simulations. These works intersect AI ethics , human-AI collaboration , and value-sensitive design . Collaborations: The department participates in major programs like WASP (Wallenberg AI, Autonomous Systems and Software Program) and TAIGA (Transdisciplinary AI Centre).

James R. WrightView profile

Associate Professor

• Machine Learning
• Game Theory
• Artificial Intelligence
• +3 more

James R. Wright is an Associate Professor in the Department of Computing Science at the University of Alberta and a Fellow & Canada CIFAR AI Chair at the Alberta Machine Intelligence Institute (Amii). He holds a Ph.D. from the University of British Columbia (2016) under Kevin Leyton-Brown, with prior postdoctoral work at Microsoft Research (2016–2018). His research focuses on modeling human strategic behavior using machine learning, emphasizing interactions where participants' rewards depend on others' actions. Key areas include algorithm design for bounded rational agents, multiagent systems, and game theory applications. Education: Ph.D. (Computer Science, UBC, 2016), M.Sc. (Computer Science, UBC, 2010), B.Sc. (Computing Science, Simon Fraser University, 2000). Research interests include data-driven models for predicting human strategic decisions, algorithmic fairness, and reinforcement learning. Recent work addresses self-play guarantees in multiplayer games, peer prediction mechanisms, and software vulnerability detection via static analyzers. His work has been published in top venues like AAAI, NeurIPS, and ICML. Awards include the ACM SIGecom Doctoral Dissertation Award (Honorable Mention), NSERC grants, and the Canada CIFAR AI Chair. He advises multiple graduate students and has served on numerous editorial and conference committees. Teaching includes courses on artificial intelligence, modeling human strategic behavior, and intelligent systems. He leads the Algorithmic and Behavioral Game Theory (ABGT) reading group at UAlberta.

• Air Traffic Management
• Algorithms Design
• GIS (Geographic Information Systems)
• +4 more

Valentin Polishchuk is a Senior Associate Professor at Linköping University's Department of Science and Technology (ITN), within the Communications and Transport Systems division. His research focuses on Air Traffic Management (including UTM for drones), algorithm design, robotics, GIS, and optimization. He holds a PhD and has contributed to over 110 publications, emphasizing theoretical and applied computational geometry. His work integrates interdisciplinary approaches to solve challenges in transportation systems and logistics. Educations: PhD in Computer Science (university unspecified) Research Interests: Algorithmic foundations for Air Traffic Management and UTM systems Geometric algorithms for path planning and visibility problems Optimization of transportation networks and logistics Applications of computational geometry in robotics and GIS Articles Trends: Recent work emphasizes multi-agent path coordination, pandemic modeling via graphical inference, and geometric approaches to social distancing. Earlier contributions focused on minimum-link paths, visibility algorithms, and relay networks optimization. Grants/Advising: Contributed to EU-funded projects on UTM and air traffic optimization Collaborations with industry partners on airspace capacity modeling Labs/Teams: Leads the Air Traffic and Transportation Planning research group, part of Linköping's Communications and Transport Systems division. Active in the FL (Flight Logistics Unit) and works with LiU's robotics and GIS initiatives.

Trifon Anchev TrifonovView profile

Associate Professor

• Computer Science
• Mathematical Logic
• Artificial Intelligence
• +3 more

Trifon Anchev Trifonov is an Associate Professor in the Department of Computer Informatics at the Faculty of Mathematics and Informatics, Sofia University 'St. Kliment Ohridski'. His academic work focuses on mathematical logic, computational mathematics, and generalized net modeling. Current affiliation: Sofia University Research areas: Proof theory, fuzzy logic, neural networks Email: triffon@fmi.uni-sofia.bg Trifonov's research explores the intersection of mathematical logic and computational systems through Dialectica interpretations and generalized net frameworks. He contributes to formal verification, intuitionistic fuzzy logic, and adaptive neural architectures. His publications demonstrate expertise in algorithmic analysis, proof mining, and computational modeling. Key collaborations include work with K. Atanassov, K. Georgiev, and G. Mengov in generalized net systems and neural signal processing. Trifonov's work spans multiple subfields including: Proof theory and constructive mathematics Intuitionistic fuzzy logic Adaptive resonance neural networks Generalized net modeling Computational complexity Formal verification techniques

Yilun DuView profile

Assistant Professor

• Generative Models
• Robot Learning
• Decision Making
• +5 more

Yilun Du is an Assistant Professor at Harvard University in the Kempner Institute and Department of Computer Science, and a senior research scientist at Google DeepMind. He holds a PhD and bachelor's degree from MIT EECS, advised by prominent figures like Leslie Kaelbling. His research focuses on generative models, decision-making, and embodied agents, emphasizing compositional architectures and energy-based models. Notable contributions include foundational work on diffusion models and the development of frameworks like COMET and Diffusion Forcing. He has received awards such as the Outstanding Paper Award at ICLR 2024 and a gold medal at the International Biology Olympiad. Education: PhD (MIT EECS, 2024), Bachelor's (MIT, 201X). Research spans generative AI applications in robotics, vision, and scientific domains. Key projects include compositional scene understanding, video generation, and multiagent self-improvement systems. His work bridges generative modeling with real-world decision-making, emphasizing generalization and scalability. Publications highlight advancements in energy-based models, video diffusion, and embodied intelligence. He organizes workshops on compositional learning and safe AI at top conferences like NeurIPS. Current interests include decentralized generative architectures for decision-making societies of models and integrating systematic reasoning with deep learning.

Marty AllenView profile

Academic

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

Marty Allen is an Associate Teaching Professor and Director of Online Programs in the Department of Computer Science at Tufts University's School of Engineering. He holds a PhD in Computer Science from the University of Massachusetts Amherst (2009), with earlier degrees in Philosophy from Simon Fraser University (1996 B.A.) and the University of Pittsburgh (2001 M.A.). His research focuses on multiagent reinforcement learning and applications of AI to biological systems, including influenza phenotype prediction and complex ecological modeling. He has authored or co-authored over 40 publications across journals like Emerging Microbes and Infections and conferences such as AAAI and NIPS. Allen has led multiple grants including a $1.2M REU program and a Disc Seed Grant for AI-driven viral research. He teaches courses in discrete mathematics, algorithms, and capstone projects, and has held leadership roles in curriculum development including the Strategic Planning Transformational Education Action Group at University of Wisconsin–La Crosse (2016–2019). Professional activities include service on Tufts' Computer Science External Advisory Board and equity initiatives as Department Equity Liaison. His work bridges theoretical computing with interdisciplinary applications in both natural and social sciences.

Lars Ailo BongoView profile

Professor

• Operating Systems
• Concurrent Programming
• Data-intensive Computing
• +5 more

Lars Ailo Bongo is a Professor at the Department of Computer Science, UiT The Arctic University of Norway. His research interests span operating systems, concurrent programming, data-intensive computing, and applications of machine learning in healthcare and bioinformatics. He has been actively involved in teaching courses such as Operating Systems, Concurrent Programming, and Algorithms, emphasizing open-access educational materials. Notably, three of his master’s students received awards for their theses: Nina Angelvik (2018), Bjørn Fjukstad (2014), and Martin Ernstsen (2013). He also advises students like Johan Ravn, whose master’s project led to a startup. Bongo’s work includes developing scalable bioinformatics pipelines (e.g., NeLS infrastructure), optimizing genomics workflows, and advancing tools for medical image analysis. He pioneered open-access course repositories on GitHub and contributed to visualization frameworks like GeneNet VR. His research bridges computer science with healthcare, focusing on tumor infiltration lymphocyte analysis, AI-driven diagnostics, and ethical AI applications in mental health. He has held roles as a postdoc at Princeton and TA at the University of Tromsø. His scientific contributions span over 50 peer-reviewed articles, covering topics from parallel computing to synthetic health data interoperability. He emphasizes reproducibility and transparency in data management, exemplified by projects like Occode for historical data transcription and MORTAL language for cross-paradigm computing. In education, Bongo advocates for accessible teaching materials and has designed courses like INF-2202 Concurrent Programming, which utilize modern tools (e.g., Go language) and GitHub repositories. His teaching philosophy integrates practical coding with theoretical foundations, fostering student innovation and open-source collaboration.

Boris GroismanView profile

Lecturer

• Foundations of Quantum Mechanics
• Quantum Information Theory
• Quantum Entang
• +5 more

Dr. Boris Groisman is a Lecturer and Governing Body Fellow at the University of Cambridge , affiliated with the Department of Applied Mathematics and Theoretical Physics (DAMTP) . He serves as a College Lecturer at Sidney Sussex College and acts as Director of Studies for Applied Mathematics. His research focuses on the Foundations of Quantum Mechanics and Quantum Information Theory , particularly quantum states, entanglement, and its philosophical implications like the Sleeping Beauty Problem. He contributes to topics such as quantum nonlocality, classical irreversible computation analogies, and magnetoresistance in granular films. He is actively involved with the Centre for Quantum Information and Foundations and has published extensively in journals like Physical Review A , IEEE Journal on Selected Areas in Information Theory , and Analysis . Contact: praelector@sid.cam.ac.uk | bg268@cam.ac.uk | Room B2.01 | Personal Homepage

Kalin Georgiev NikolovView profile

Associate Professor

• Computer Science
• Artificial Intelligence
• Neural Networks
• +4 more

Kalin Georgiev Nikolov is an Associate Professor at the Faculty of Mathematics and Informatics, University of Sofia, specializing in computational methods, neural networks, and generalized nets. His work bridges mathematics and computer science through innovative modeling techniques. Fields of Interest: Computer Science, Neural Networks, Generalized Nets, Fuzzy Logic, Computational Mathematics Key Collaborations: Trifon Trifonov, Georgi Mengov, S. Hadjitodorov Recent Research: 2005 publications on neutrosophic sets, adaptive resonance networks, and geometric computing applications