Find Academic Supervisors

• Computational Social Science
• Artificial Intelligence
• Robotics
• +5 more

Dr. Yara Khaluf is an Assistant Professor in the Information Technology Group at Wageningen University & Research, Department of Social Sciences. She holds a PhD (2014, Paderborn University, cum laude) on robot swarm task allocation, followed by postdoctoral research at Paderborn University (2014–2015) and Ghent University’s IDLab (2015–2021). Her work focuses on computational social science, hybrid human-agent societies, and distributed artificial cognition, leveraging agent-based modeling and systems dynamics for behavior prediction/modulation. She leads European-funded projects like ChronoPilot (EU Horizon2020 FET) and DELICIOS (FWO, 2019–2022). Her research explores interactions between artificial agents and humans, developing cognitive capacities for seamless interaction via social feedback networks. Notable contributions include collective foraging algorithms, time perception modeling, and agent-based simulations for public health interventions. Awards include competitive IGS and DFG fellowships. She collaborates with leading experts in swarm intelligence (Dorigo, Stuetzle), collective decision-making (Hamann, Marshall), and experimental psychology (Johansson, Vatakis). Current projects investigate modulating human time perception and delegation of conflict-of-interest decisions to AI agents. Teaching includes courses on model thinking, agent-based modeling of complex systems, and data science applications in food/consumer science. Her work bridges computational methods with societal challenges, emphasizing scalable solutions for hybrid systems.

David CookeView profile

Researcher

• Computational Solid State Chemistry
• Biomineralization
• Surface Science
• +3 more

Dr David Cooke is a Subject Area Leader in Chemistry & Chemical Engineering at the Department of Physical and Life Sciences, School of Applied Sciences, University of Huddersfield. He is a member of the Structural, Molecular and Dynamic Modelling Centre and Associate Member of multiple research centers including the Centre for Functional Materials and Catalysis Research Centre. Background: PhD in Computational Solid State Chemistry (Prof SC Parker, University of Bath) Postdoctoral Research: University of Bath and Materials Science department at the University of Cambridge Research Interests: Computational Solid State Chemistry, mineral surface modeling, biomineralization processes, crystal growth, and surface defect analysis. His work aligns with UN Sustainable Development Goals for environmental and health applications. Publications: 15 recent works focus on cerium oxide interfaces, plutonium hydration, oxide-polymer composites, and defect dynamics using Density Functional Theory and Molecular Dynamics. Key collaborations include M. Molinari, L. Gillie, and S. Parker. Scientific Activities: Active in research output since 2001 (50+ publications) 5 supervised works 35+ research activities including oral presentations

Kazem KazerounianView profile

Professor

• Nano-Mechanical Systems
• Robotics
• Gear Systems Dynamics
• +4 more

Dr. Kazem Kazerounian is a Professor of Mechanical Engineering at the University of Connecticut, affiliated with the School of Mechanical, Aerospace, and Manufacturing Engineering. He holds B.S., M.S., and Ph.D. degrees in Mechanical Engineering from the University of Illinois at Chicago (1980–1984). His expertise spans analytical and computational kinematics/dynamics applied to bio-nano machines, robotics, gear systems, and product design with health/ergonomics focus. He is a Fellow of ASME and recipient of the ASME Lifetime Achievement Award (2006) and George Wood Award (1997). Research interests include protein-based nano-scale devices, gear system dynamics, robotic manipulation, and creativity in engineering education. He consults for OSIM International (Singapore), Pratt & Whitney, and the Singapore Productivity & Standards Board. Editorial roles include ASME Applied Mechanics Review, Journal of Medical Devices, and Journal of Mechanisms and Machine Theory. Awards: ASME Lifetime Achievement Award (2006), George Wood Award (1997), ABB Outstanding Faculty Award (1997) Consulting: OSIM International, Pratt & Whitney, Singapore Productivity & Standards Board His work bridges mechanical engineering with bio-nano systems, emphasizing interdisciplinary applications in medicine and robotics. Over 150 publications span topics like nanorobotics, orthosis design, and computational protein folding models.

• Artificial Intelligence
• Cybersecurity
• Machine Learning
• +7 more

Vahid Behzadan is an Assistant Professor in Data Science and Computer Science at the University of New Haven's Tagliatela College of Engineering. He leads the SAIL Lab, focusing on AI safety and security, particularly in autonomous systems like driverless cars and smart cities. His work addresses adversarial attacks on machine learning and reinforcement learning, with applications in cybersecurity and healthcare. Behzadan has held prior positions at Kansas State University, University of Nevada Reno, and University of Birmingham, UK. He holds a Ph.D. in Computer Science and an M.S. from the University of Nevada Reno, and a B.Eng. from the University of Birmingham. His research spans AI ethics, cybersecurity, and complex systems. Behzadan advises the UNH hacking team and actively participates in policy initiatives, including Connecticut's AI Working Group and the Connecticut AI Alliance. He has contributed to over 30 peer-reviewed articles and frequently engages in media discussions on topics like AI safety, facial recognition, and cybersecurity threats. Key research areas include adversarial machine learning, AI forensics, and ethical AI design. His work bridges theoretical advancements with real-world applications in transportation, healthcare, and national security. Behzadan collaborates with organizations such as the Transportation Research Laboratory (TRL) and Open Web Application Security Project (OWASP).

• Neuroscience
• Artificial Intelligence
• Neuronal Modeling
• +5 more

Eilif B. MULLER is a Professor in the Department of Neurosciences at Université de Montréal, Principal Investigator of the Architectures of Biological Learning Lab (ABL-Lab) at CHU Sainte-Justine Research Center, and Associate Faculty at Mila (Quebec AI Institute). His work bridges neuroscience and artificial intelligence, focusing on understanding how sensory perception is learned in the neocortex through biophysical simulations and deep learning models. He holds affiliations with IVADO (Institute for Data Valorization) and contributes to strategic initiatives like the UNIQUE Québec Center. His research integrates empirical neurophysiology with computational models, exploring dendritic processing and synaptic plasticity to inform both biological understanding and AI advancements. Teaches NSC-6044 and NSC-6045 (Neuroscience Colloquia) at Université de Montréal. Leads projects on neocortical learning mechanisms and their implications for neurodevelopmental disorders. Recipient of grants from CRSNG (Natural Sciences and Engineering Research Council), FRSQ (Health Research Fund), and institutional funding. Publications span topics in computational neuroscience, neural network modeling, and interdisciplinary AI-neuroscience research. Collaborates extensively across institutions to advance large-scale brain simulations and data-driven models.

• Complex Systems Modeling
• Computational Mathematics
• Applied Mathematics
• +7 more

Yannis Kevrekidis is a Professor at Princeton University with a distinguished career in computational mathematics and chemical engineering. He is currently a Hans Fischer Senior Fellow at the Technical University of Munich (TUM-IAS) and has held visiting positions at institutions like the Zuse Institute Berlin and Caltech. Education : National Technical University of Athens (Chemical Engineering) University of Minnesota (PhD in dynamical systems) Research Interests : Equation-Free and Variable-Free Modeling Complex Systems Dynamics Multiscale Computation Integration of Machine Learning with Scientific Computing Pattern Formation & Instability Analysis Key Article Trends : Advanced data-driven modeling of dynamical systems Manifold learning for reaction coordinates Projective integration methods Coarse-grained modeling across disciplines Applications in epidemiology, neuroscience, and fluid dynamics Scientific Awards : Guggenheim Fellowship Humboldt Research Award Computing in Chemical Engineering Award (AIChE) Bodossaki Academic Award Allan P. Colburn Award Collaborations : Extensive international collaborations with institutions in Germany, Austria, and the UK Key role in the Complex Systems Modeling and Computation focus group at TUM-IAS

Jakub MacinaView profile

Research Fellow

• Natural Language Processing
• Learning Sciences
• Dialogue Systems
• +6 more

Jakub Macina is a Doctoral Fellow at the ETH AI Center and a PhD Candidate at ETH Zürich . He works in the intersection of Natural Language Processing and Learning Sciences as part of the Language, Reasoning and Education Lab (led by Prof. Mrinmaya Sachan) and the Professorship for Learning Sciences and Higher Education (led by Prof. Manu Kapur). Forbes 30 Under 30 in Science & Education 2023 Recipient of ETH AI Center Fellowship ( Co-founder of a health-tech startup with seed investment Research Interests : Focus on generative large language models (LLMs), dialogue tutoring systems , pedagogical alignment of AI models, and mathematical reasoning . His work explores: Reinforcement learning for pedagogical steering LLM evaluation frameworks Socratic question generation Stepwise error detection and remediation Student-teacher interaction modeling Publications span top conferences like EMNLP , ACL , NeurIPS , and RecSys , with particular emphasis on educational applications of LLMs and dialogue-based learning systems . Scientific Awards : Forbes 30 Under 30 in Science and Education (2023) 2nd Place in ACM IT SPY Computer Science Master's Thesis Competition (2017) ETH AI Center Fellowship (2021) Leadership & Teaching includes: Managing team of 6 data scientists Teaching Assistant for Machine Learning and NLP courses at ETH Zurich Developing large-scale ML pipelines for recommender systems Open-source contributions to Discourse and Google Summer of Code projects

Brian DzwonkowskiView profile

Associate Professor

• Coastal Circulation
• Estuarine Dynamics
• Ocean Observing Systems
• +6 more

Dr. Brian Dzwonkowski is an Associate Professor at the University of South Alabama's Stokes School of Marine & Environmental Sciences and a Senior Marine Scientist at the Dauphin Island Sea Lab. He holds a Ph.D. (2009) and M.S. (2003) in Marine Studies from the University of Delaware, and a B.A. in Mathematics (1999) from The College of New Jersey. Education: Ph.D., Marine Studies (Physical Oceanography), University of Delaware M.S., Marine Studies (Oceanographic Remote Sensing), University of Delaware B.A., Mathematics, The College of New Jersey His research focuses on coastal physical oceanography, examining how tides, winds, and river discharge drive water movement and layering in coastal systems. He investigates interactions between physical processes and biogeochemical cycling, with emphasis on hypoxia, harmful algal blooms, and ecosystem vulnerability to climate change. His work integrates in situ data, satellite observations, and numerical models across spatiotemporal scales. Recent publications highlight his expertise in hurricane-ocean interactions (e.g., J. Phys. Oceanogr. , 2022), shelf hypoxia dynamics (e.g., J. Geophys. Res. Oceans , 2021), and estuarine-shelf exchange processes. Collaborative projects span topics like Vibrio ecology (2024), compound fluvial-marine flooding (2021), and coastal climate resilience. Dr. Dzwonkowski mentors graduate and undergraduate students, including former Ph.D. advisees Steve Dykstra and Jeff Coogan. He contributes to coastal monitoring initiatives via the MyMobileBay.com platform and leads interdisciplinary studies on estuarine restoration (e.g., West Fowl River project).

• Machine Learning
• Bioinformatics
• Medical Imaging
• +5 more

Paul J. Kennedy is a Professor at the University of Technology Sydney's Centre for Artificial Intelligence. He holds a PhD from the same institution (1999). His research focuses on machine learning applications in healthcare, bioinformatics, medical imaging, and data mining. Key areas include developing algorithms for genomic data analysis, healthcare pathway modeling, and edge-cloud frameworks for omics data. Education: PhD in Artificial Intelligence (1999, UTS). Research interests span machine learning, health informatics, and data compression. Notable work includes studies on administrative health records, lung nodule detection, and virtual reality-based cancer cohort analysis. He has co-authored over 100 publications across journals like BMC Bioinformatics, IEEE Transactions, and Artificial Intelligence in Medicine. Advising: Collaborates extensively with students/researchers but no explicit student list provided. Grants and labs: Active in interdisciplinary projects involving medical and computational teams, though specific grants are not detailed here.

Swati ChandnaView profile

Senior Lecturer

• Statistics
• Data Science
• Network Theory
• +3 more

Dr. Swati Chandna is a Senior Lecturer at the School of Computing and Mathematical Sciences, Birkbeck, University of London. She holds an honorary position as an Honorary Lecturer in Statistics at University College London (UCL) from January 2023 to January 2026. She earned her PhD in Statistics from Imperial College London in 2013. Her research focuses on statistical modeling, network analysis, and bioinformatics, with notable contributions to stochastic networks, single-cell genomic data analysis, and complex-valued signal processing. Teaching responsibilities include modules such as Bayesian Methods, Analysing Data, Statistical Analysis, and Project Applied Statistics. She serves as Admissions Tutor for Graduate Certificate and Diploma in Statistics for Data Science and as School Ethics Lead at Birkbeck. Her work bridges theoretical statistics with practical applications in genomics, environmental modeling, and biomedical research. Dr. Chandna’s recent research explores topics like covariate-driven network estimation, stochastic modeling of genomic data, and bootstrap techniques in source separation. Her publications reflect interdisciplinary collaboration across statistics, computer science, and life sciences.

Daniel R ObaidView profile

Associate Clinical Professor

• Interventional Cardiology
• Cardiac Computed Tomography
• Intravascular Imaging
• +5 more

Dr. Daniel R Obaid is a Clinical Associate Professor and Consultant Cardiologist at Swansea University Medical School , specializing in Biomedical Sciences . His clinical academic work at the Morriston Regional Cardiac Centre and ILS 2 Clinical Imaging Facility focuses on advanced cardiovascular imaging and interventional cardiology. Expertise in Interventional Cardiology , Cardiac CT , and Atherosclerotic Plaque Imaging Significant contributions to patient safety and human factors in cardiovascular procedures Recipient of the Young Investigator Prize from the Society of Cardiovascular CT, USA His research integrates invasive and non-invasive imaging techniques to identify vulnerable plaques, with publications spanning atherosclerosis , clot microstructure , and AI applications in cardiology . Current studies include virtual TAVR simulations and biomechanical analysis of plaque stress . Recent collaborative work explores low-dose radiation protocols , LDL transport modeling , and anti-inflammatory effects of GLP-1 agonists , reflecting interdisciplinary approaches to cardiovascular risk mitigation. Available for postgraduate supervision , Dr. Obaid has contributed to undergraduate medical professionalism and cardiovascular physiology modules (PM-241F, PM-266).

• Biostatistics
• Epidemiology
• Survival Analysis
• +4 more

Gomez Melis, Guadalupe is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the GRBIO research group (Bioestadística i Bioinformàtica) and the Department of Statistics and Operations Research. She collaborates with the Institut de Recerca i Innovació en Salut (Health Research Institute) and the Faculty of Mathematics and Statistics (FME). Her work focuses on biostatistics, survival analysis, multistate models, and clinical trial design, with significant contributions to understanding disease progression and outcomes, particularly in pandemic-related studies. She has supervised doctoral theses and leads various research projects funded by EU and national grants. Her research spans statistical methodologies for healthcare data, including censored data analysis and adaptive clinical trial designs. Key activities include leading over 450 research outputs, including articles in high-impact journals like Biostatistics and BMC Medical Research Methodology , and collaborations on projects like the EU-funded Siemens Energy AI Chair initiative. Her work often integrates statistical modeling with real-world health data, addressing challenges in infectious disease dynamics, elderly patient care, and genomic analysis. Notable contributions include developing the GofCens package for goodness-of-fit methods and the MSMpred interactive tool for predicting patient trajectories via multistate models. She actively participates in international conferences and serves on scientific committees, demonstrating her role in advancing biostatistical methodologies globally.

• Hydrogeology
• Groundwater Management
• Environmental Geochemistry
• +3 more

Dr. Teresa Melo is an Assistant Professor in the Department of Mineral and Energy Resources Engineering at the Instituto Superior Técnico (University of Lisbon). Her research focuses on hydrogeology, groundwater management, and environmental geochemistry, with a particular emphasis on climate change impacts and ecosystem sustainability. She is affiliated with the CERIS research unit, specializing in sustainable civil engineering innovations. Her teaching portfolio includes courses such as 'Hydrogeology,' 'Groundwater Pollution and Protection,' and 'Advanced Topics in Water Resources and Environment.' She actively contributes to the AQUADAPT project, addressing climate-resilient riverine ecosystems and groundwater-dependent vegetation mapping. Key research themes include groundwater-surface water interactions, natural background level assessments, and the socio-economic valuation of groundwater protection. She collaborates internationally on projects such as the FREEZE initiative, investigating submarine groundwater discharge and coastal aquifer dynamics. Her publications span over three decades, with recent work emphasizing wildfire impacts on groundwater recharge, microbial diversity in aquifers, and ethical dimensions of contaminated groundwater management. She has advised numerous interdisciplinary studies on environmental risk assessment and policy frameworks.

• Risk Management
• Crisis Management
• Patient Safety
• +7 more

Denis Fischbacher-Smith is a Professor and Research Chair in Risk and Resilience at the University of Glasgow's Adam Smith Business School, within the College of Social Sciences. Previously, he held roles at the University of Liverpool, including founding director of its Management School, and held academic positions at Sheffield, Durham, and John Moores Universities. He also served as a visiting professor at Kobe University (Japan), San Diego State University (USA), and Innsbruck University (Austria). His academic journey includes degrees from Manchester, Glasgow, St Andrews, and others, culminating in a DLitt in Crisis Management. He holds over a dozen professional certifications, including Fellowships from the Academy of Social Sciences and Higher Education Academy, and Chartered statuses in Geography, Security, and Management. Research focuses on risk management, crisis response, and organizational resilience, with 112+ publications spanning three decades. Key areas include evacuation strategies, crisis team performance, emergency planning limitations, and organizational vulnerability. He advises governments (e.g., UK Department of Health, Lesotho), corporations, and regulatory bodies, and has led projects on healthcare safety and terrorism preparedness. Publications emphasize interdisciplinary approaches to risk, such as using comics in education and analyzing post-EU expansion crises. Awards recognize his contributions to public health policy, emergency planning, and security practices. He chairs HARM Consulting and serves on boards of NHS trusts and sports organizations.

Richard SilberglittView profile

Professor

• Emerging Technologies
• Science, Technology, and Innovation Policy
• Energy Security
• +17 more

Richard Silberglitt is a Senior Physical Scientist at RAND and Professor of Policy Analysis at the RAND School of Public Policy, where he conducts interdisciplinary research at the nexus of science, technology, and public policy. With over 50 years of experience across academia, government, and industry, he is a leading expert in technology foresight, energy systems, and R&D portfolio management. His research focuses on emerging technologies , science and innovation policy , energy security , and nanotechnology . He has developed influential methodologies such as an energy scenario analysis framework and the PortMan portfolio management system, both widely applied in U.S. and international contexts. His work supports strategic planning in defense, public safety, and economic development. His recent publications reflect a strong trend toward technology foresight , critical materials supply chains , quantum technology assessment , and public sector innovation . These works often employ scenario planning, Delphi methods, and data-driven analytics to inform high-stakes policy decisions. Member, American Physical Society Member, Materials Research Society Member, American Ceramic Society As a subject matter expert, Silberglitt has advised the United Nations, U.S. Department of Defense, National Security Agency, and multiple federal agencies. He has chaired the International Advisory Board of the APEC Center for Technology Foresight and delivered testimony to U.S. Congressional committees on critical materials and technology policy. His research has been supported by grants and contracts from the U.S. Army, Navy, CDC, and National Institute of Justice. He has led major initiatives on law enforcement technology, transportation safety ( The Road to Zero ), and international technology foresight. His work often involves collaborative teams and cross-sector partnerships to address complex technological and policy challenges.