Find Academic Supervisors

Irene McMullinView profile

Professor

• Existentialism and Phenomenology
• Ethics
• Moral Psychology

Irene McMullin is a Professor at the University of Essex within the School of Philosophical, Historical, and Interdisciplinary Studies, affiliated with the Department of Philosophy. She joined the university in 2013 after postdoctoral work at Bergische Universität Wuppertal and six years teaching at the University of Arkansas. Her academic background includes a PhD from Rice University, an MA from the University of Toronto, and a BA Hons from St. Francis Xavier University. Her research examines questions of personhood, agency, and self-becoming, particularly emphasizing the role of others in these processes. Drawing from both Continental and Analytic traditions, McMullin explores: Existentialism and Phenomenology Virtue ethics and Kantian ethics Moral psychology and social relations Current investigations focus on the phenomenology of ideality and how encounters with 'the good' shape practical agency. Her publications demonstrate sustained engagement with themes of moral deliberation, trust, and rationality across philosophers including Heidegger, Kant, and Løgstrup. Analysis reveals consistent interdisciplinary bridges between ethics, phenomenology, and social theory, with recent work increasingly addressing normative foundations of shared human experience.

Elham KazemiView profile

Professor

• Mathematics Education
• Teacher Education
• Educational Equity
• +6 more

Elham Kazemi is a Professor of Mathematics Education at the University of Washington’s College of Education, holding the Geda and Phil Condit Endowed Chair. She specializes in elementary teacher education, instructional leadership, and equity-focused mathematics pedagogy. Her research emphasizes professional learning communities, student-centered classroom practices, and disrupting inequities in education. Education: PhD in Mathematics Education, UCLA (1999) MA in Educational Psychology, UCLA (1997) BS in Psychology (Elementary Teaching Certificate), Duke University (1992) Research Interests: Kazemi’s work focuses on equitable mathematics instruction, teacher learning, and leadership development. She designs school-wide professional development models (e.g., Math Labs) and studies classroom discourse, student disciplinary identities, and organizational learning. Key projects include the Labs Project (funded by JSMF) and RMLL (NSF-funded leader learning). Publications & Grants: Over 40 peer-reviewed articles, including work in American Educational Research Journal and Journal of Teacher Education . Co-authored influential books like Choral Counting and Counting Collections and Intentional Talk . Recipient of $5.4M+ in grants from NSF, McDonnell Foundation, and others for projects on teacher leadership and equitable instruction. Awards: 2022 AERA Open Article of the Year 2019 Outstanding Faculty Award for Educational Equity 2015 Geda & Phil Condit Professorship Advising & Leadership: Kazemi co-leads initiatives like the Leading Towards Racially Just Mathematics Instruction partnership. She has supervised numerous graduate students and collaborates with schools to implement equity-driven practices. Labs & Teams: Her work includes the Labs Project (designing Learning Labs for mathematics/literacy discussions) and the Mathematics Education Project (MEP), fostering statewide collaboration among educators.

Jari MurtoView profile

Associate Professor

• Labour Law
• Social Law
• Employment Policy
• +5 more

Jari Murto serves as Associate Professor at the Faculty of Law, University of Helsinki, where he specializes in Labour and Social Law. With over two decades of academic and practical experience, he contributes significantly to Finnish and European labour law discourse through publications, policy analysis, and academic leadership. His educational qualifications include a Doctor of Laws (LL.D), Master of Science in Economics and Business Administration, and Master of Laws (LL.M). Murto's doctoral dissertation Ryhmänormit yrityksessä (Group Norms in Companies, 2015) established foundational research on workplace norm systems. Murto's research examines labour law doctrines, norm systems, working conditions determination, and transition-phase labour market issues. He analyzes EU policy impacts on national frameworks, lifelong learning integration into labour law, and psychosocial workplace safety. Recent work addresses digital workplace challenges, parental employment policies, and just transitions in green/digital economies. His scholarship bridges theoretical legal frameworks with practical industrial relations through frequent commentary on Supreme Court decisions. As Doctoral Programme Supervisor, Murto mentors emerging legal scholars while maintaining active peer review roles. He serves on Finland's Board for Strengthening General Applicability of Collective Agreements and participates in European labour law networks including the Labour Law Research Network and Nordic Network of Labour Law Scholars. His conference activities span topics from social packages in income policy agreements to lifelong learning's role in modern labour law. Murto maintains strong engagement with practical legal applications through Supreme Court commentary series ( KKO:n ratkaisut kommentein ) and regular contributions to Lakimies journal. His research methodology combines doctrinal analysis with empirical studies of workplace practices and policy implementation.

Krzysztof BurdzyView profile

Professor

• Probability Theory
• Stochastic Processes
• Brownian Motion
• +7 more

Krzysztof Burdzy is a Professor of Mathematics and Adjunct Professor of Statistics at the University of Washington, where he is affiliated with the Department of Mathematics in the College of Arts and Sciences. He maintains an active research and teaching profile, currently offering undergraduate courses in probability. His research interests span Probability Theory , Stochastic Processes , Neumann Eigenfunctions , Hot Spots Problem , and the Philosophy of Probability . He is particularly known for his work on Brownian motion, eigenfunction behavior, and spectral theory in geometric domains. His recent work includes contributions to the resolution of the hot spots conjecture for Euclidean triangles and the discovery of interior hot spots in convex sets. The most recent articles reflect a deep engagement with both theoretical mathematics and foundational philosophy. Topics include spectral geometry, probabilistic methods in PDEs, critiques of philosophical theories of probability, and interdisciplinary reflections on epistemology. The publication trend shows sustained contributions from the 1990s through 2024, with a dual focus on rigorous mathematical proofs and meta-scientific analysis. Euclidean triangles have no hot spots (Annals of Mathematics, 2020) Convex sets can have interior hot spots (preprint, 2024) Hypocrisy++: On Philosophy of Probability and Sociology of Ideologies (2023) Burdzy has advised students in mathematics and probability, though specific names are not listed. He has received recognition through publications in top-tier journals such as Annals of Mathematics and Journal of Functional Analysis , though formal awards are not explicitly mentioned. He has delivered numerous talks on the philosophy of probability and its relationship to statistics. He is actively involved in public scholarship, maintaining a personal website with essays on quantum probability, real estate, philosophy, and AI. His work on the limitations of mathematics, suicide prevention, and critiques of post-modern thought reflect a broad intellectual engagement beyond technical mathematics. He does not appear to lead a formal lab or research team, but collaborates with scholars such as R. Bañuelos, W. Werner, and others in probability and analysis.

Kate OggView profile

Professor

• Refugee Law
• Human Rights Litigation
• Feminist Legal Theory
• +2 more

Kate Ogg is Professor and Associate Dean (Higher Degree Research) at ANU Law School. Her interdisciplinary research examines refugee law, human rights litigation, and feminist legal theory through works including the monograph 'Protection from Refuge: From Refugee Rights to Migration Management'. Ogg's scholarship investigates how courts shape refugee journeys globally. She holds a BA/LLB (First Class Honours, University Medal) from Griffith University, MSc (Distinction) from Oxford, and PhD from ANU. Ogg provides expert testimony to the Australian Federal Parliament and contributes to international media discourse on refugee policy. Research Focus: Current ARC-funded projects examine community sponsorship for refugees and movement litigation. Key research streams include: COVID-19 border restrictions' impact on citizenship conceptualizations Feminist engagements with international refugee law Deliberative democratic approaches to human rights adjudication Constitutional struggles in displacement contexts Recent publications analyze pandemic border controls as internal displacement events and refugee law's response to democratic backsliding. Collaborative work advances methodological innovation through refugee-centered legal scholarship. Leadership: As Director of the Rewriting Jurisprudence project, Ogg collaborates with scholars and lawyers with displacement experiences to reimagine legal precedents. She co-leads the Law, Governance & Institutions cluster at ANU's Institute for Climate, Energy & Disaster Solutions.

Mattia AndreolettiView profile

Lecturer

• Philosophy of Medicine
• Bioethics
• Clinical Ethics
• +5 more

Dr. Mattia Andreoletti is a Lecturer at the Department of Health Sciences and Technology at ETH Zurich, working within the Professorship for Bioethics. His research spans philosophy of medicine and bioethics, with a focus on the ethical dimensions of AI in healthcare, dementia policy, drug regulation, and clinical reasoning. PhD from the European School of Molecular Medicine (SEMM), affiliated with the European Institute of Oncology (IEO, Milan) ORCID: 0000-0003-1880-0770 His work intersects with clinical ethics, particularly examining replicability in scientific research, evidential pluralism in drug regulation, and the ethical landscape of digital biomarkers. He contributes to courses such as Ethics in Drug Development and Ethics Workshop: The Impact of Digital Life on Society . The 15 most recent articles (2025-2023) highlight his engagement with AI ethics, dementia prevention, regulatory science, and clinical reasoning. Topics include ethical frameworks for digital biomarkers, evidential pluralism in drug approval, and philosophical foundations of rehabilitation sciences.

Christian ListView profile

Professor

• Decision-making
• Individual and collective choice
• Preference and judgment aggregation
• +9 more

Christian List is Professor of Philosophy and Decision Theory at Ludwig Maximilian University of Munich, where he serves as Co-Director of the Munich Center for Mathematical Philosophy (MCMP). Previously, he was Professor of Philosophy and Political Science at the London School of Economics until 2020. His work bridges philosophy, economics, and political science with a particular focus on individual and collective decision-making and the nature of intentional agency. Professor List's research spans multiple interconnected domains: theories of individual and collective choice (particularly social choice theory and judgment aggregation), free will and consciousness, the philosophy of mind and action, and the foundations of the social sciences. His work on group agency, developed in his influential book Group Agency with Philip Pettit, has reshaped debates about corporate entities and collective intentionality. His more recent work on free will, culminating in his book Why Free Will is Real , presents a scientifically grounded defense of free will against reductionist skepticism. His recent publications reveal a sophisticated integration of formal methods with deep philosophical questions, particularly regarding consciousness, probability aggregation, and the relationship between different levels of explanation. List's work consistently demonstrates how mathematical precision can illuminate fundamental philosophical problems while maintaining relevance to broader social and scientific contexts. Scientific Awards and Recognition: Elected Fellow of the British Academy (2014) Member of Academia Europaea (2023) Member of the Bavarian Academy of Sciences and Humanities (2022) Joseph B. Gittler Award from the American Philosophical Association (2020) Philip Leverhulme Prize in Philosophy (2007) 5th Social Choice and Welfare Prize (2010) List has supervised numerous PhD students and early-career researchers, many of whom have gone on to prominent positions in philosophy and related fields. His collaborative work with Franz Dietrich on judgment aggregation has been particularly influential. As Co-Director of the Munich Center for Mathematical Philosophy, he has secured substantial research funding and established MCMP as a leading international hub for formal and mathematical approaches to philosophical problems. Through the Munich Center for Mathematical Philosophy, List leads a vibrant research community that brings together philosophers, economists, political scientists, and mathematicians to tackle foundational questions using rigorous formal methods. The center hosts regular workshops, seminars, and visiting scholars, creating a dynamic intellectual environment that bridges disciplinary boundaries.

Lance RipsView profile

Professor

• cognitive psychology
• reasoning
• concepts and categorization
• +9 more

Lance Rips is a Professor in the Psychology Department at Northwestern University , Evanston, IL. His research focuses on cognitive psychology, particularly concepts, reasoning, and autobiographical memory. Academic Rank: Professor Institution: Northwestern University Department: Psychology Department Contact: ripslab@gmail.com , rips@northwestern.edu Research interests include: Deductive and inductive reasoning Concepts of objects/events over time Causal cognition Mathematical thinking (numbers, non-Euclidean geometry) Informal argumentation and survey methodology His lab investigates foundational questions in cognition, with recent work on conditional reasoning, object individuation, and developmental understanding of substances. Publications span journals like Cognitive Science , Psychological Science , and Cognition .

• Computational Psychopathology
• Learning Theory
• Cognitive Neuroscience
• +3 more

Robin A. Murphy is a Professor of Experimental Psychology at the University of Oxford and a Fellow and Tutor for Admissions at Corpus Christi College. He holds a PhD from McGill University (Canada) and has contributed over 50 scientific publications on associative learning mechanisms, their role in mental disorders like depression and psychopathy, and translational neuroscientific applications. His research bridges animal and human learning, with a focus on computational psychopathology and neurochemical modulation (e.g., serotonin). Education: Undergraduate degree, Queen's University MA and PhD in Psychology, McGill University Research Interests: Dr. Murphy investigates how associative learning processes underpin mental disorders, particularly through neurochemical systems like serotonin. His work explores causal reasoning biases in depression, psychopathy's learning deficits, and translational models linking animal studies to human cognition. Key themes include agency perception, contingency judgment, and the neural substrates of prejudice. Recent projects involve peptide research in aging and computational modeling of multi-agent systems in depression. Grants and Funding: Supported by MRC, BBSRC, Wellcome Trust, and Japan Society for the Promotion of Science. He has advised UK Research Councils and NSERC (Canada). Labs and Teams: Leads a lab focusing on associative learning mechanisms, collaborating with institutions globally on computational psychopathology and translational neuroscience.

Cesla AmarelleView profile

Professor

• Migration Law
• Human Rights
• Constitutional Law
• +5 more

Cesla Amarelle serves as Full Professor and Chairholder of Public Law and Migration Law at the University of Neuchâtel's Faculty of Law. Her academic leadership extends to co-directing the Swiss Center for Migration Law (CDM) and contributing to national research initiatives including the National Center of Competence in Research (NCCR) 'On the Move'. She concurrently holds significant public appointments as Chair of the Institute of European Law at the University of Fribourg and Federal Commissioner for Women's Issues, with recent expert designation to the Federal Round Table on signature collection integrity for 2024. Her academic foundation includes a law degree from the University of Lausanne (1996), LL.M. in European and International Economic Law from the University of Fribourg, and doctoral thesis from the University of Lausanne (2004). Her career progression at the University of Neuchâtel spans assistant professor (2009-2014), extraordinary professor (2015-2016), and full professor positions since 2016, complemented by earlier research roles at Swiss National Science Foundation and University of Fribourg. Professor Amarelle's research centers on migration law frameworks, human rights protections in asylum systems, and constitutional dimensions of European integration. Her work critically examines the intersection of migration governance with digital technologies, climate change impacts, and gender equality. Current projects analyze temporary protection regimes, non-refoulement principles in technological contexts, and the evolving relationship between Swiss migration law and European legal frameworks. Her scholarship consistently bridges theoretical legal analysis with practical policy implementation challenges. Her extensive publication record demonstrates evolving focus from foundational migration law codification toward contemporary challenges including digital discrimination, child rights in emergency contexts, and sustainable finance frameworks. Recent scholarship reflects increasing engagement with technological impacts on migration governance and the humanitarian dimensions of temporary protection systems, while maintaining rigorous analysis of constitutional and European law interfaces. Professor Amarelle actively contributes to academic and public discourse through leadership in the Swiss Center for Migration Law and participation in the NCCR 'On the Move' consortium. Her public service includes significant political roles as Vaud State Councilor for Education (2017-2022) and National Councilor (2011-2017), where she chaired key committees on political institutions and finance while representing Swiss higher education interests nationally. She maintains active engagement with professional associations including the Swiss Conference of Higher Education Institutions and Conference of Directors of Public Education.

Richard HoltonView profile

Professor

• Moral Philosophy
• Philosophy of Mind
• Free Will
• +3 more

Professor Richard Holton is a Fellow and Director of Studies in Philosophy at the University of Cambridge. His work spans moral philosophy, philosophy of mind, and epistemology, with a focus on agency, responsibility, and trust. His recent research examines mental effort, akrasia (weakness of will), and ethical decision-making in pandemic contexts. Publications highlight interdisciplinary connections between philosophy, psychology, and medical ethics. While his articles address causation, self-deception, and linguistic frameworks, no explicit scientific awards or student advisement records are documented in the provided materials.

Martin MüllerView profile

Professor

• Artificial Intelligence
• Game Theory
• Monte Carlo Tree Search
• +7 more

Martin Müller is a Professor in the Department of Computing Science at the University of Alberta, where he conducts research in artificial intelligence, game theory, and heuristic search. He holds the Canada CIFAR AI Chair at Amii and is an Amii Fellow, underscoring his leadership in AI. His research group focuses on Monte Carlo tree search, reinforcement learning, combinatorial game theory, and automated planning, with applications in games such as Go, Hex, and NoGo. His research interests span Monte Carlo and exact methods in game-tree search , exploration in heuristic search and machine learning , and algorithms in combinatorial game theory . He has developed open-source software like MCGS (Minimax-based Combinatorial Game Solver) and contributes to game-playing systems such as Fuego for Go. His work bridges theoretical foundations with practical implementations in AI-driven game solvers. Recent publications show a strong trend in reinforcement learning , particularly in deep Q-learning, policy gradient methods, and anomaly detection in deep RL. His team also explores combinatorial game solving , sparse reward environments , and imperfect information games . The research integrates machine learning with classical AI techniques, emphasizing empirical validation and algorithmic innovation. Canada CIFAR AI Chair Amii Fellow Best student paper award at IEEE Conference on Games 2024 Best paper award at IEEE COG 2021 Outstanding paper award at AAAI-18 Faculty of Science Dissertation Award (2016) Dissertation Award from the Canadian Artificial Intelligence Association (2013) Müller has supervised numerous PhD and MSc students, including Hongming Zhang, Henry Du, and Timo Bertram, many of whose theses focus on game AI, reinforcement learning, and combinatorial optimization. He is funded by NSERC, Mitacs, and Compute Canada. His group collaborates on projects involving neural networks for game playing, SAT solving, and planning algorithms. He is currently on sabbatical but remains academically active, teaching a graduate course on combinatorial games in 2025 and hosting visiting researchers. His lab is involved in the development of MCGS, a solver for sum games, and contributes to open-source AI software. The team publishes regularly in top venues such as NeurIPS, ICML, AAAI, and IEEE Transactions on Games. Future work includes advancing combinatorial game solvers, improving deep RL robustness, and exploring generalization in game representations.

• Computer Vision
• Natural Language Processing
• 3D Human Motion Synthesis
• +3 more

Gül Varol is a permanent researcher at École des Ponts ParisTech's IMAGINE group, an ELLIS Scholar, and Guest Scientist at Max Planck Institute. She holds a PhD from Inria Paris/ENS with awards from ELLIS and AFRIF. Her academic service includes Program Chair at ECCV'24 and Area Chair roles at major conferences. Current affiliations: IMAGINE group (École des Ponts ParisTech), Max Planck Institute Previous roles: Postdoctoral researcher at University of Oxford Her research focuses on vision-language applications, particularly in 3D human motion synthesis, sign language technology, and audio description generation. Key techniques include text-conditioned diffusion models, temporal context modeling, and synthetic data utilization. Scientific contributions recognized through: Google Research Scholar award (2023) ELLIS PhD Award (2020) AFRIF PhD thesis award (2020) Best application paper at ACCV'20 Recent publications demonstrate expertise in: Text-driven 3D motion editing (MotionFix, 2024) Cross-dataset generalization studies (TMR++, 2024) Temporal action composition frameworks (TEACH, 2022) Sign language dense annotation methods (BOBSL, 2022) Zero-shot audio description generation (AutoAD-Zero, 2024) She actively contributes to dataset development including BOBSL (British Sign Language corpus) and SURREACT synthetic action dataset, while pioneering new evaluation metrics for audio description quality and motion retrieval benchmarks.

Benjamin EysenbachView profile

Assistant Professor

• Reinforcement Learning
• Machine Learning
• Probabilistic Inference
• +3 more

Benjamin Eysenbach is an Assistant Professor in the Department of Computer Science at Princeton University's School of Engineering and Applied Science since 2023. His research focuses on developing principled reinforcement learning (RL) algorithms that improve simplicity, scalability, and robustness in state-of-the-art systems, particularly through probabilistic inference techniques. Ph.D., Machine Learning, Carnegie Mellon University (2023) B.S., Mathematics, Massachusetts Institute of Technology Research interests center on reinforcement learning with emphasis on long-horizon reasoning, exploration strategies, and robustness. He explores intersections with probabilistic inference and self-supervised learning to enhance RL capabilities. Recent publications highlight trends in contrastive learning for goal-conditioned RL, temporal distance modeling , and hierarchical control . Key themes include reward-free learning, scalable architectures, and uncertainty quantification in decision-making systems. 2025: Junior Faculty Award for Excellence in Research and Teaching, Princeton School of Engineering and Applied Science Eysenbach's work bridges theoretical foundations with practical implementations in AI training frameworks, emphasizing performance optimization and safety mechanisms.

• Computer Vision
• Machine Learning
• Deep Learning
• +5 more

Abhinav Shrivastava is an Associate Professor in the Department of Computer Science at University of Maryland, College Park, with a joint appointment in the Institute of Advanced Computer Studies (UMIACS). Previously, he served as an Assistant Professor at the same institution from August 2018 to June 2024, and spent one year as a Visiting Research Scientist at Google Research from September 2017 to August 2018. His educational background includes: PhD in Robotics and Artificial Intelligence from Carnegie Mellon University (2017), advised by Abhinav Gupta, with thesis titled 'Discovering and Leveraging Visual Structure for Large-scale Recognition' MS in Artificial Intelligence from Carnegie Mellon University (2011), supervised by Alyosha Efros and Martial Hebert BTech in Computer Science and Engineering from Jaypee Institute of Information Technology (2010) Professor Shrivastava's research focuses on computer vision and machine learning, with particular expertise in object detection, image recognition, and neural representations. His work bridges theoretical advances with practical applications, exploring how visual systems can discover and leverage structure in large-scale recognition problems. He has made significant contributions to understanding the role of supervision in vision transformers, developing novel approaches for object-state composition recognition, and creating efficient neural representations for videos and 3D scenes. His research often addresses fundamental challenges in visual recognition, including handling novelty in open-world environments and improving the efficiency of visual systems. An analysis of his recent publications reveals a strong emphasis on neural representations, particularly for dynamic content like videos and 3D scenes. His work demonstrates increasing sophistication in handling open-world vision problems, with research spanning object discovery, localization, and representation learning. The publications show a clear progression toward more efficient and scalable models, with recent work focusing on model compression, sparse representations, and addressing the challenges of working with limited annotations. His scientific contributions have been recognized with several prestigious awards: Best Paper Award (Applications) at IEEE Winter Conference on Applications of Computer Vision (2020) Microsoft Research PhD Fellowship (2014-2016) Best Student Paper Award at IEEE Winter Conference on Applications of Computer Vision (2014) Outstanding Reviewer Award at IEEE CVPR (2015) Professor Shrivastava has successfully mentored numerous graduate students, many of whom have become prominent researchers in computer vision. His Amazon Research Awards (2020 and 2023) have supported innovative projects including 'The pursuit of knowledge: discovering and localizing new concepts using dual memory' and 'Audio-conditioned Diffusion Models for Generating Lip-synchronized Videos.' He has served as Area Chair for major conferences including ICCV, CVPR, and AAAI, demonstrating his leadership in the computer vision community. His research has attracted significant funding from both academic and industry sources, supporting his exploration of fundamental questions in visual recognition and representation learning.