Find Academic Supervisors

• Midwifery
• Maternal Health
• Mindfulness in Healthcare
• +7 more

Louise Hunter is an Associate Lecturer at the Oxford School of Nursing and Midwifery, Oxford Brookes University, where she contributes to both undergraduate and postgraduate teaching in midwifery. She is actively involved in research, supervision, and professional development, with a strong focus on improving maternity care and the experiences of women and midwives. Education: PhD MA (Oxon) RM (Registered Midwife) Her research interests revolve around enhancing midwifery care through innovative models such as mindfulness training and group antenatal care. She has investigated mindfulness as a tool to improve workplace culture and support women during labor and early parenthood. Her work on the NIHR-funded REACH project explored group antenatal care, and she continues to research water birth feasibility, anemia in pregnancy, and equity in midwifery education. Her recent publications demonstrate a consistent focus on maternal and newborn health, midwifery education, and service user empowerment. Themes across her work include health equity, particularly for Black, Asian, and Minority Ethnic (BAME) students and birthing people, evidence-based practice, and the integration of psychological and social support into maternity care. Scientific Awards and Recognition: Fellow of the Higher Education Academy Louise Hunter is also a member of the Royal College of Midwives (RCM) and actively supervises research students, including Claire Litchfield, whose work examines water immersion in labor for obese women. She is involved in the Maternity Care (OxMater) research group and contributes to developing initiatives that involve service users in midwifery recruitment and training. Her work bridges clinical practice, education, and research, aiming to create more inclusive, effective, and compassionate maternity services.

Bernd KlauerView profile

Professor

• Water resources economics
• Ecological economics
• Environmental and resource economics
• +7 more

Prof. Dr. Bernd Klauer serves as Deputy Head of the Department of Economics at the Helmholtz Centre for Environmental Research (UFZ) since 2017 and holds an Honorary Professorship for Sustainability and Water Resources Management at the University of Leipzig since 2015. He leads the Working Group on Social Science Water Research and contributes to interdisciplinary projects spanning Germany, EU, Jordan, and India. Doctorate in Economics (1997), University of Heidelberg Diplom-Mathematiker (1992), University of Heidelberg His research integrates water economics with ecological economics and governance frameworks, focusing on hydro-economic modeling, water resource governance, decision support systems, and multi-criteria evaluation. Key application areas include Food-Water-Energy Nexus, Integrated Water Resource Management, and EU Water Framework Directive implementation. The 15 most recent publications reveal a strong emphasis on coupled human-natural systems modeling, climate change adaptation in agriculture, water scarcity governance, and socioeconomic analysis of informal water markets. His work consistently bridges technical hydrological models with economic decision-making frameworks across diverse geographic contexts. Current projects include FUSE (Food-Water-Energy Nexus) and NexusFootprints, while completed initiatives like the Jordan Water Project demonstrate his commitment to transboundary water challenges. He collaborates extensively with hydrologists, ecologists, and policy experts.

Jean-François GodboutView profile

Professor

• Data Science
• AI Safety
• Generative AI
• +6 more

Jean-François Godbout is a Professor in the Department of Political Science at the Université de Montréal and an Associate Academic Member of Mila - the Quebec AI Institute. He directs the undergraduate program in Big Data Analytics in Social Sciences and Humanities at UdeM and conducts interdisciplinary research through the Complex Data Lab. Affiliated with IVADO (AI Consortium) Member of CÉRIUM (International Research Centre) and CECD (Democratic Citizenship Centre) His research focuses on: Data Science applications in political institutions AI Safety and generative AI's impact on political attitudes Misinformation Mitigation through large language models Comparative Political Development in Canadian and Lower Canada contexts Legislative Institutions and voting records analysis Political Polarization in online societies Recent publications analyze social media disinformation, AI persuasion on harmful topics, and education-focused text simplification. His articles frequently combine graph mining , machine learning , and political science methodologies. Scientific collaborations include: Mila researchers (Andreea Musulan, Maximilian Puelma Touzel) IVADO data science initiatives McGill University interdisciplinary projects He supervises students in: Political science (Julien Robin, Matthew Taylor) Artificial Intelligence (Kellin Pelrine, Camille Thibault) Computational social science applications

Pierre MarquisView profile

Professor

• Artificial Intelligence
• Knowledge Representation
• Automated Reasoning
• +6 more

Pierre Marquis is a distinguished Professor of Computer Science at Université d'Artois , affiliated with the Centre de Recherche en Informatique de Lens (CRIL-CNRS, UMR 8188) . Since December 2024, he has served as the vice-president for research and doctoral studies at Université d'Artois. His research focuses on Artificial Intelligence , particularly knowledge representation , automated reasoning , inconsistency handling , and knowledge compilation , with recent emphasis on Explainable AI (XAI) . Research Interests: Marquis's work spans foundational AI topics including abduction , induction , belief revision , and preference modeling . He has pioneered knowledge compilation techniques to optimize AI tasks and developed frameworks for reasoning under inconsistency through paraconsistent logics and argumentation. His EXPEKTATION chair (2020-2026) under France's national AI program drives his current focus on interpretable machine learning models. Scientific Awards: 2025: CNRS Silver Medal 2022: AAIA Fellow 2017: Senior Member of Institut Universitaire de France (IUF) 2009: EurAI (ECCAI) Fellow Doctoral Students: Mentoring Clément Lens (critical patient monitoring systems) and Mehdi Sabiri (data-knowledge integration for AI explanations). Collaborating with students like Louenas Bounia (formal XAI models) and Romain Wallon (pseudo-Boolean constraints). Grants & Projects: Leads the EXPEKTATION research chair (2020-2026) and participates in ANR PING/ACK (2019-2023), ANR THEMIS (2021-2025), CNRS IRP MAKC (2020-2024), and H2020 TAILOR (2020-2024). Previously led PIA4 MAIA (2023-2032) and Pint (2022-2023). Labs & Teams: Active in CRIL-CNRS, contributing to PyXAI (Python XAI library) and d4 (model counting), while mentoring teams on consensus belief merging and dynamic constraint processing .

Darrell RossView profile

Professor

• Forest entomology
• Ecology and management of forest insect pests
• Bark beetle ecology
• +7 more

Darrell Ross is a Professor in Entomology at the School of Natural Resource Sciences , North Dakota State University . Previously, he held professorial roles at Oregon State University in the Department of Forest Ecosystems and Society and served as Director of the Richardson Hall Quarantine Facility from 2006–2019. His academic journey began with a PhD in Entomology from the University of Georgia (1990), an MS in Forest Ecology from Oregon State University (1985), and a BS in Forest Science from Pennsylvania State University (1981). PhD , Entomology, University of Georgia, 1990 MS , Forest Ecology, Oregon State University, 1985 BS , Forest Science, Pennsylvania State University, 1981 Dr. Ross specializes in forest entomology, focusing on bark beetle ecology, pheromone-based management strategies, and biological control of invasive species like the hemlock woolly adelgid. His work integrates chemical ecology with forest health assessment and ecological restoration. His research emphasizes pheromone applications (e.g., MCH) for bark beetle control, predator-prey dynamics in biological control of adelgids, and habitat manipulation for pest management. Recent studies address biodegradable pheromone formulations, predator phenology for invasive species control, and post-outbreak ecological impacts on pollinators. At Oregon State University, he directed the Richardson Hall Quarantine Facility, contributing to large-scale forest protection strategies. Current work at NDSU continues his legacy in integrating chemical signaling with forest ecosystem management.

Atrisha SarkarView profile

Assistant Professor

• Human-centric multiagent systems
• Human-AI interaction
• Human-robot interaction
• +4 more

Atrisha Sarkar is an Assistant Professor in the Department of Electrical and Computer Engineering at Western University , Canada, and heads the Humans and Autonomous Agents Lab . She is also a faculty member of the Rotman Institute of Philosophy and a Faculty Affiliate at the Schwartz Reisman Institute for Technology and Society . Her research integrates empirical and behavioral game theory with software engineering to design human-centric AI systems that prioritize safety and societal well-being. Education: Atrisha holds a PhD and has previously served as a postdoctoral fellow at the Schwartz Reisman Institute for Technology and Society at the University of Toronto under the supervision of Prof. Gillian Hadfield. Research Focus: Her work centers on human-centric multiagent systems , combining methods from: Behavioral and empirical game theory Software engineering Human-AI and human-robot interaction AI safety and reliability She applies these to domains such as autonomous driving, cooperative AI, and social media dynamics, aiming to ensure AI systems align with human values and societal norms. Publications and Impact: Atrisha has published extensively in top-tier venues including AAAI , AAMAS , ICRA , NeurIPS , and EC . Her work spans from theoretical models of strategic behavior to practical frameworks for validating autonomous systems, with a strong emphasis on real-world applicability. Labs and Teams: She leads the Humans and Autonomous Agents Lab at Western University, where her team focuses on designing AI agents that can cooperate effectively with humans in complex, dynamic environments.

• Information Retrieval
• Crowdsourcing
• Human-in-the-loop AI
• +5 more

Dr. Gianluca Demartini is a leading researcher in Human-in-the-loop AI Systems with significant contributions to Crowdsourcing , Information Retrieval , and Generative AI applications. His work bridges Machine Learning and Human-Computer Interaction , focusing on Bias Management , Fact-Checking , and Ethical AI . Major Affiliations : L3S Research Center, ScienceWISE platform, and collaborations with institutions like University of Queensland and University of Padua Over 15 years, his research has explored Crowdsourcing Quality Control (Mechanical Cheat 2012), Entity Ranking (2008-2013), and Semantic Search . Recent work (2024-2026) focuses on Generative AI Impacts in domains like Media Literacy , Data Curation , and Visual Analytics . Scientific Recognition : Best Paper Award (Top 1.4%) at ICTIR 2023 Best Short Paper Award (Top 0.6%) at ECIR 2020 Honorable Mention (Top 2%) at CSCW 2020 Best Demo Award at ISWC 2011 3rd Best Paper at LA-WEB 2008 His 15 most recent publications (2024-2026) demonstrate expertise in LLM-based Content Moderation , Immersive Data Visualization , and Trustworthy AI Systems . He has pioneered methods for Bias Detection in Wikipedia (2013), Entity Ranking (2008-2013), and Human-AI Collaboration frameworks. His work consistently addresses ethical challenges in AI for Social Good and Responsible Data Science .

• Agent-Based Computational Economics
• Economic Networks
• Macroeconomics
• +3 more

Giorgio Fagiolo is a Full Professor of Economics at Sant'Anna School of Advanced Studies. His work spans agent-based computational economics, economic networks, and macroeconomic policy analysis. University: Sant'Anna School of Advanced Studies (Scuola Superiore Sant'Anna) Department: Economics Email: giorgio.fagiolo@sssup.it Research interests focus on agent-based modeling , macroeconomic instability , and climate-economy interactions . He develops computational models to study industrial dynamics, financial integration, and policy design in complex systems. Key themes: Endogenous growth cycles, R&D network stability, and green transition policies. Methodological emphasis: Empirical validation of agent-based models and nonlinear economic dynamics. Scientific awards include collaboration with leading institutions like ETH Zurich, Columbia University, and OFCE Sciences Po. His publications appear in journals such as Journal of Economic Dynamics and Control and Ecological Economics .

Walter Timo de VriesView profile

Professor

• Intelligent Land Management
• Responsible Land Administration
• Urban and Rural Development
• +8 more

Professor Walter Timo de Vries is a faculty member at the Technical University of Munich (TUM) , holding the Chair of Land Management and Land Development within the Department of Aerospace and Geodesy, TUM School of Engineering and Design . His research focuses on intelligent and responsible land management , urban and rural development , spatial justice , and the development of a Human Geodesy framework. A graduate of TU Delft (1988) and Rotterdam (PhD), he has led international projects across Asia, Africa, and South America. At TUM, he directs the Master's and PhD Programs in Land Management , serves as Dean of Geodesy , and leads TUM.Africa . Member of the German Geodetic Commission Member of the Bavarian Academy for Rural Development Academic Coordinator of TUM SEED Center Research Interests span responsible land governance , land tenure security , land consolidation , and geospatial methods for sustainable development. His recent work examines the Water-Energy-Food Nexus and digital twins in collaborative planning. He has supervised over 20 PhD and Master’s students on topics like spatial justice , nomic pastoral tenure , and smart land use . Publications address blockchain in land administration , spatial inequalities , and land policy reforms across global contexts.

Morteza Haghir ChehreghaniView profile

Professor

• Machine Learning
• Decision Making
• Reinforcement Learning
• +17 more

Morteza Haghir Chehreghani is a Professor of Artificial Intelligence and Machine Learning at the Data Science and AI Division of Chalmers University of Technology , Sweden. He leads the Machine Learning and Decision Making Lab and is affiliated with WASP , CHAIR , and ELLIS . Education : PhD in Computer Science (2014) from ETH Zurich under Prof. Dr. Joachim M. Buhmann Prior Roles : Staff Research Scientist at Naver Labs Europe (2014-2018) Research spans Interactive Machine Learning , Sequential Decision Making , Federated Learning , Efficient Deep Learning , and Graph-Based Learning . Key application areas include Transport , Autonomous Systems , Energy , Drug Discovery , and Computational Biology . Selected Publications (2020-2025) demonstrate expertise in Reinforcement Learning for drug design, Minimax Distance Measures for clustering, and Graph Neural Networks for trajectory analysis. Current work focuses on Combinatorial Bandits and Human-in-the-loop AI . Teaching includes graduate courses like Advanced Topics in Machine Learning (DAT441/DIT41), Algorithms for Machine Learning (TDA233/DIT382), and PhD-level Advanced Reinforcement Learning . He has also taught Statistical Methods for Data Science and Theoretical Foundations of ML . Patents include systems for Autonomous Vehicle Motion Control , K-NN Search via Minimax Distances , and Trip Prediction Algorithms . Collaborative projects involve Nature Communications (2022) and multiple ICML / CVPR publications.

Rasha Abdel RahmanView profile

Professor

• Language production
• Neurocognitive psychology
• Visual perception
• +5 more

Prof. Dr. rer. nat. Rasha Abdel Rahman is a leading figure in Neurocognitive Psychology at the Institute of Psychology, Humboldt-Universität zu Berlin . Her research bridges the domains of language production , visual perception , and semantic memory organization , with particular emphasis on electrophysiological mechanisms (EEG) and emotional influences on cognitive processing. Habilitation in Psychology (2008), Ph.D. in Psychology (summa cum laude, 2001), and M.S. in Psychology (1997) from Humboldt-Universität Since 2010: Heisenberg Professor of Neurocognitive Psychology 2009: Heisenberg Fellow Her research interests focus on: Language production mechanisms Interface between vision, semantics, and language Functional organization of semantic memory Attentional and emotional modulation of perception Face and object perception dynamics Mental imagery processes The laboratory employs behavioral and electrophysiological (EEG) methods to investigate how knowledge shapes perception and language processing. Recent studies examine: Emotional content's impact on social judgment AI-generated face perception Art perception influenced by artist morality Trustworthiness effects in visual consciousness Selected scientific awards include: Heisenberg-Fellowship (DFG, 2008) Heinz Heckhausen Junior Scientist Award (DGPs, 2002)

Sean B. AnderssonView profile

Professor

• Optimal Estimation
• System Identification
• Single Particle Tracking
• +4 more

Sean B. Andersson is a Professor in the Department of Mechanical Engineering at Boston University's College of Engineering. His research focuses on optimal estimation, system identification, single particle tracking, robotics, and control theory. He earned his Ph.D. from the University of Maryland, College Park. Education : Ph.D. in Mechanical Engineering (University of Maryland, College Park) His work integrates control algorithms with applications in microscopy, nanofabrication, and multi-agent systems. Recent research trends highlight persistent monitoring, trajectory optimization, MRI reconstruction, and dip-pen nanolithography. He has mentored numerous graduate and undergraduate students, many of whom now hold positions at institutions like MIT Lincoln Labs, University of Pennsylvania, and Juniper Networks. Scientific Contributions : Developed robust multi-agent control policies for data harvesting Advanced single particle tracking with real-time feedback Innovated in non-raster scanning probe microscopy Optimized sensor scheduling via minimax and semidefinite programming His lab team combines theoretical and applied research in robotics and control systems, with alumni contributing to academia, industry, and research labs globally.

Reza SamaviView profile

Associate Professor

• Information Security
• Machine Learning
• Trustworthy AI
• +5 more

Dr. Reza Samavi is an Associate Professor at Toronto Metropolitan University's Department of Electrical, Computer, and Biomedical Engineering, Faculty of Engineering & Architectural Science. He is also a Faculty Affiliate with the Vector Institute for Artificial Intelligence and directs the Trustworthy AI Research Lab (TAILab). Previously, he served as Assistant Professor and eHealth Graduate Program Coordinator at McMaster University's Department of Computing and Software (2014-2020). Holding a PhD in Computer Science (University of Toronto, 2013), his academic journey bridges industry experience with rigorous scholarly contributions. His research lies at the critical intersection of Trustworthy AI , Machine Learning Security , and Medical Informatics . He investigates Safety & Security of ML Algorithms Privacy-Preserving AI Systems Transparency Frameworks for Medical AI Blockchain-enabled Privacy Auditing Game Theory for Model Robustness Optimization-based Anonymization Techniques The TAILab research group under his leadership has produced groundbreaking work in Uncertainty Quantification for Neural Networks Robustness Against Adversarial Attacks Medical Image Analysis Clinical Decision Support Systems Emergency Medicine Predictive Modeling His recent projects focus on enhancing migrant youth mental health through LLM-based conversation agents and developing certified robustness guarantees for ensemble networks. Dr. Samavi's scholarly excellence is recognized through Privacy Technologies Research Award (IBM) Privacy By Design Research Award (Ontario IPC) Bridging Divides Emerging Research Grant (TMU) NSERC PGS-D Recipient (Co-supervised student) SOSCIP Accelerator Grant He has secured major funding from NSERC , SOSCIP , MITACS , HHS , and IDEaS programs. As a dedicated educator, Dr. Samavi teaches graduate courses in Secure Machine Learning and Software Testing while mentoring 15+ graduate students across PhD , MASc , and MEng programs. His lab has presented at premier venues including AAAI , IJCAI , and IEEE Transactions while maintaining active collaborations with institutions like Harvard, ETH Zurich, and the University of Waterloo.

Guoquan HuangView profile

Assistant Professor

• Robotics
• Computer Vision
• Robot Learning
• +5 more

Guoquan Huang is an Assistant Professor in the Department of Mechanical Engineering at the University of Delaware. He holds a B.Eng. in Automation from the University of Science and Technology, Beijing (2002), and M.Sc. and Ph.D. degrees in Robotics from the University of Minnesota (2009 and 2012). Prior to his current role, he was a Postdoctoral Associate at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on robotics, computer vision, and autonomous systems, emphasizing probabilistic perception, estimation, and control for ground, aerial, and underwater vehicles. He leads the development of the OpenVINS platform for visual-inertial estimation and has contributed to advancements in SLAM (Simultaneous Localization and Mapping), sensor fusion, and multi-robot coordination. Education: B.Eng in Automation (Electrical Engineering), University of Science and Technology, Beijing, 2002 M.Sc. in Robotics, University of Minnesota, Twin Cities, 2009 Ph.D. in Robotics, University of Minnesota, Twin Cities, 2012 His research interests span robotics, computer vision, and autonomous systems , with a focus on: Visual-inertial navigation and SLAM Sensor fusion (LiDAR, IMU, camera) Autonomous vehicle control and safety Multi-robot cooperative localization His recent publications (2023–2025) emphasize robust algorithms for navigation in GPS-denied environments, real-time sensor calibration, and dataset development for aerial visual localization. He has pioneered techniques like decoupled error-state estimation and consistent parallel frameworks for SLAM. Labs/Teams: Leads the development of the OpenVINS research platform, focusing on visual-inertial state estimation. Collaborates on projects involving human-swarm interactions and resilient ground vehicle navigation.

Stefan KlusView profile

Lecturer

• Data-driven model reduction
• Transfer operator approximation
• Machine learning
• +8 more

Dr. Stefan Klus is a Lecturer at the School of Mathematics and Physics, University of Surrey. His research focuses on data-driven model reduction, transfer operator approximation, and kernel-based machine learning applied to dynamical systems. He specializes in interdisciplinary applications across quantum physics, fluid dynamics, and computational biology. Education: PhD in Industrial Mathematics (2011, Paderborn University) and Habilitation (2020, Freie Universität Berlin). Research Interests : Data-driven modeling and reduced-order methods Koopman operator theory and transfer operators Machine learning for dynamical systems (e.g., Deeptime library) Tensor decompositions and quantum systems analysis Graph-based analysis (e.g., microbiome dynamics) Publications : Klus has contributed to over 50 peer-reviewed articles, with recent work emphasizing: Kernel methods for quantum chemistry and physics Tensor-based approaches for high-dimensional systems Applications in climate science (e.g., Pacific SST modeling) Agent-based modeling and social systems Technical Contributions : Co-developer of the Deeptime Python library for dynamical modeling Pioneer in Koopman operator-based model reduction Advanced graph kernel methods for microbiome analysis