Find Academic Supervisors

Joel David HamkinsView profile

Professor

• Set Theory
• Computability Theory
• Philosophy of Mathematics
• +7 more

Joel David Hamkins is the O’Hara Professor of Logic at the University of Notre Dame, with significant affiliations to logic and philosophy research communities in China and Japan. His work bridges set theory, computability, and philosophy of mathematics, focusing on foundational questions about infinity, truth, and mathematical existence. Key Research Areas : Set theory, potentialism, continuum hypothesis, surreal numbers, forcing, large cardinals, definability, halting problem history Recent Talks : Kobe University (2025), Notre Dame HPS Colloquium (2025), Fudan University seminars (2025), Peking University conference (2025) Scientific Contributions : 2024 arXiv paper on halting problem attribution, ongoing work on bi-interpretation of surreal arithmetic with ZFC, analysis of transitive submodel principles Awards & Recognitions : William Reinhardt Memorial Lecture (2025), former JSPS Fellowship at Kobe University Hamkins’ work reveals deep connections between technical set theory and philosophical inquiry, particularly through his modal logic approach to potentialism and analysis of truth nonabsoluteness. His 2024 paper with Theodor Nenu re-examines Turing’s legacy, while his technical collaborations with researchers from Fudan University and Oxford advance foundational mathematics.

Nir OrenView profile

Professor

• Multi-Agent Systems
• Formal Argumentation
• Computational Trust Theory
• +1 more

Professor Nir Oren is a faculty member at the School of Natural and Computing Sciences , University of Aberdeen. His research focuses on multi-agent systems , formal argumentation , computational trust theory , and norm-based reasoning . He currently supervises PhD students in Computing Science and serves as Dean for Research Performance. Research Specialisms: Artificial Intelligence, Operational Research Contact: n.oren@abdn.ac.uk Research Trends (2022–2025): Nir Oren's publications span argumentation theory , BDI agent modeling , resilience in autonomous systems , and human-machine collaboration . His recent work addresses responsibility-aware AI , medical explainability , and environmental sensor networks . Key methods include probabilistic reasoning , game theory , and logical formalisms .

Jose Israel RodriguezView profile

Assistant Professor

• Applied Algebraic Geometry
• Algebraic Statistics
• Nonlinear Algebra
• +5 more

Jose Israel Rodriguez is an Assistant Professor in the Department of Mathematics at the University of Wisconsin-Madison, with additional affiliations in the Department of Electrical & Computer Engineering and the Institute for Foundations of Data Science. He joined UW Madison in Fall 2020 after completing postdoctoral positions at the University of Chicago (with Lek-Heng Lim) and Notre Dame (with Jonathan Hauenstein). Rodriguez earned his PhD in 2014 from UC Berkeley under the supervision of Bernd Sturmfels. His research focuses on applied algebraic geometry and algebraic methods for statistics, with particular interests in nonlinear algebra and nonlinear eigenvalue problems, algebraic statistics and nearest point problems, and applications of monodromy and Galois groups. Rodriguez has made significant contributions to numerical algebraic geometry, particularly in solving polynomial systems, maximum likelihood estimation, and Euclidean distance degree calculations. His work bridges theoretical mathematics with practical computational methods. Rodriguez's recent publications demonstrate a strong trend toward developing numerical methods for solving complex algebraic problems with applications in statistics, optimization, and engineering. His research shows increasing sophistication in handling decomposable systems, multiparameter eigenvalue problems, and braid group computations, often implementing these methods in software tools like Macaulay2. His work connects abstract algebraic geometry with concrete computational approaches. NSF Postdoctoral Fellow Provost's Postdoctoral Scholar Rodriguez currently advises PhD students Julia Lindberg (expected graduation May 2022, joint with B. Lesieutre) and Zinan Wang. He has organized numerous seminars and conferences including SIAM_SAGA, Algebra in Statistics and Computation Seminar, and Applied Algebra Seminar. His research has been supported by various grants that enable his work in numerical algebraic geometry and its applications. Rodriguez is actively involved in the algebraic geometry and statistics communities, organizing several seminars and minisymposia at major conferences. He has developed several software tools including implementations for decomposable sparse polynomial systems, multiregeneration, algebraic optimization, Galois groups, and maximum likelihood obstruction functions. His work connects theoretical mathematics with practical computational applications across various domains.

Jon WarrenView profile

Academic

• Probability Theory
• Stochastic Flows
• Random Matrices
• +2 more

Dr Jon Warren is a Reader in Statistics at the University of Warwick, specializing in probability theory. His research spans stochastic flows, random matrices, and properties of Brownian motion, with significant contributions to understanding complex stochastic systems. Research Interests: Dr Warren's work is centered on probability theory, particularly in the areas of stochastic flows, random matrices, and Brownian motion. His research delves into the intricate behaviors of these systems, exploring their properties and applications in various mathematical contexts. Publications: His recent publications cover a wide range of topics within probability theory, including stochastic heat equations, Dyson Brownian motion, and random matrix theory. These works highlight his expertise in both theoretical developments and practical applications of stochastic processes. Teaching: He teaches ST910 Introduction to graduate probability, demonstrating his commitment to educating the next generation of statisticians and probabilists. Contact: Dr Warren can be reached at J.Warren@warwick.ac.uk for academic inquiries or collaboration opportunities.

Dominique DevrieseView profile

Professor

• Functional Programming
• Object Capabilities
• Secure Compilation
• +5 more

Dominique Devriese is a professor at the Department of Computer Science, KU Leuven, and a member of the DistriNet research group. His work bridges computer security, programming languages, and formal verification. Research interests: Functional Programming, Object Capabilities, Secure Compilation, Dependently-typed Programming, Modal Type Theory Teaching: Formal Systems, Object-Oriented Programming, CyberSecurity, Secure Software His research focuses on rigorous software systems security through capability machines and secure compilation techniques. He actively contributes to formal verification using Agda and Haskell, with recent work on multimode type theory and effect parametricity. Key publication trends include: multimode/presheaf type theory, capability-based security models, formal verification of hardware/software abstractions, and parametricity applications in programming languages. Contact: Email: dominique.devriese@kuleuven.be ORCID: 0000-0002-3862-6856

• Programming Language Design
• Program Verification
• Type Theory
• +3 more

Neelakantan R. Krishnaswami is a Professor of Computer Science at the University of Cambridge's Computer Laboratory , and a Fellow of Trinity College . His research focuses on the intersection of program verification, programming language design, and foundational topics like type theory and semantics. His work spans areas such as refinement types, parser design, separation logic for systems software, and the semantics of reactive programming. Notable contributions include the Datafun language for higher-order Datalog and the λert type theory for explicit refinement types. He has also developed foundational frameworks for verifying imperative programs using advanced type systems and logical relations. Key publications include 'Explicit Refinement Types' (ICFP 2023), 'flap: A Deterministic Parser with Fused Lexing' (PLDI 2023), and 'CN: Verifying Systems C Code' (POPL 2023). His work frequently addresses challenges in efficiency, correctness, and modularity for both functional and imperative systems. His awards include Distinguished Paper Awards at PLDI 2019 and POPL 2020. His research integrates theoretical rigor with practical tooling, exemplified by contributions to languages like Coq, Lean, and Haskell.

Benjamin J. DelawareView profile

Assistant Professor

• Programming Languages
• Software Engineering
• Formal Verification
• +3 more

Benjamin J. Delaware is an Assistant Professor of Computer Science at Purdue University. His research focuses on programming languages, formal verification, and tools for ensuring software correctness using mechanized theorem provers. He holds a Ph.D. from The University of Texas at Austin (2013), an MSc from Washington University in St. Louis (2007), and a B.S. from Truman State University (2005). His work emphasizes practical formal methods, including static enforcement of privacy policies, compiler design for oblivious computation, and automated verification techniques. Key contributions include tools like Taypsi, KestRel, and HACCLE. His research bridges theory and practice, addressing challenges in software security, correctness, and efficiency. Publications span top venues like POPL, PLDI, and OOPSLA, reflecting a strong focus on foundational programming language concepts. Collaborations with researchers like Suresh Jagannathan and Qianchuan Ye drive advancements in automated reasoning and secure computation.

Stuart KurtzView profile

Professor

• Theoretical Computer Science
• Computational Complexity Theory
• Type Theory
• +4 more

Stuart Kurtz is a Professor in Computer Science and the College at the University of Chicago, and serves as Master of the Physical Sciences Collegiate Division. He holds the endowed position of George and Elizabeth Yovovich Professor. His research focuses on theoretical computer science, including computational complexity theory, randomness in computation, type theory, and formal logic. He has contributed to foundational areas such as the Berman-Hartmanis Isomorphism Conjecture and the computational properties of random sets. Kurtz is affiliated with the Theoretical Computer Science and Programming Languages Groups at the University of Chicago. He has been recognized with the 2009 Quantrell Award for teaching excellence. His service roles include Director of Undergraduate Studies and Department Chair in Computer Science. He actively mentors Ph.D. students and has advised multiple graduates in complexity theory and related fields. His academic background includes a Mathematics Ph.D. from the University of Illinois, supervised by Carl Jockusch. He approaches type theory as an intersection of formal logic and functional programming. Research interests span measure-theoretic randomness, computational logic, and complexity class separations. His recent work explores connections between theoretical computer science and interdisciplinary fields like physics and statistics. In teaching, Kurtz has instructed courses such as Formal Language Theory, Discrete Mathematics, and Honors Intro Programming. His service contributions include roles in the Computation Institute and Toyota Technological Institute at Chicago. His lab affiliations and collaborative work reflect a strong commitment to advancing theoretical foundations in computer science.

George EvansView profile

Professor

• Macroeconomics
• Econometrics
• Adaptive Learning
• +9 more

George Evans is the John B. Hamacher Professor of Economics at the University of Oregon, affiliated with the Department of Economics in the College of Arts and Sciences. He holds a Ph.D. from the University of California, Berkeley (1980), with expertise in macroeconomics and econometrics. His research centers on adaptive learning in macroeconomic models, exploring how expectations influence monetary and fiscal policy, economic stability, and sunspot equilibria. His work integrates theoretical modeling with experimental and behavioral insights, contributing significantly to the understanding of bounded rationality and learning dynamics in economic systems. The recent articles highlight a consistent focus on expectations, learning, and macroeconomic policy . Themes include the stability of economic equilibria under learning, the role of bounded rationality in unemployment and market dynamics, and the nonlinear effects of fiscal policy. His research often employs advanced dynamic modeling and has been published in leading journals such as the American Economic Journal: Macroeconomics and Journal of Economic Theory . Evans has received research funding, including from the NSF (Grant No. SES-1559209), and is a co-author of the influential book Learning and Expectations in Macroeconomics . He has delivered numerous invited lectures at international conferences and institutions, solidifying his role as a leading scholar in behavioral and learning-based macroeconomics. He advises and collaborates extensively, particularly with Seppo Honkapohja, Bruce McGough, and William Branch. His work continues to shape the discourse on how agents form expectations and how such behavior affects macroeconomic outcomes.

Dmitriy TraytelView profile

Associate Professor

• Logic
• Automata Theory
• Runtime Verification
• +7 more

Dmitriy Traytel is an Associate Professor at the University of Copenhagen's Department of Computer Science since August 2020, where he currently heads the Software, Data, People & Society (SDPS) section. Prior to this position, he worked as a senior researcher (Oberassistent) in the Information Security Group led by David Basin at ETH Zürich. He completed his PhD at TU München under Tobias Nipkow's supervision in 2015. His research focuses on formal methods, particularly logic, automata theory, runtime verification and monitoring, decision procedures, (co)induction and (co)recursion, and interactive theorem proving. Traytel develops formally verified tools for runtime monitoring including VeriMon, TimelyMon, and WhyMon, emphasizing correctness and efficiency in monitoring complex temporal properties. His recent publications (2021-2025) demonstrate a strong focus on first-order temporal logic monitoring, with particular attention to explainable verdicts, scalable parallel implementations, and formal verification of monitoring algorithms. The work spans theoretical foundations in logic and category theory while maintaining practical applications in runtime verification systems. Distinguished Paper Award at POPL 2025 for 'Barendregt Convenes with Knaster and Tarski' Best Student Paper Award at FSCD 2016 Distinguished Paper Award at ATVA 2018 Traytel has supervised numerous PhD, Master's, and Bachelor's students in areas spanning formal verification, runtime monitoring, and theorem proving. His research has been supported through collaborations with major institutions including ETH Zürich and TU München. He actively contributes to the academic community by serving on program committees for major conferences including ITP 2025 and RV 2025. He leads the Software, Data, People & Society section at the University of Copenhagen, focusing on developing formally verified tools for runtime verification that bridge theoretical computer science with practical applications in security and system monitoring.

• Computational Linguistics
• Psycholinguistics
• Language Processing
• +4 more

Richard Futrell is an Associate Professor at the University of California, Irvine (UCI), affiliated with the Department of Language Science. He leads the Language Processing Group, focusing on computational models of human and machine language processing. His work bridges information theory, Bayesian cognitive modeling, and natural language processing (NLP) interpretability. University of California, Irvine Department of Language Science Language Processing Group leader His research examines how linguistic structures emerge from cognitive and communicative pressures. Key areas include dependency locality, surprisal theory in sentence processing, and efficiency-driven language evolution. He investigates how memory constraints, predictability, and information density shape syntactic and morphological patterns across languages. Recent publications analyze code-switching efficiency, syntactic priming, ERP component modeling, and agent-based language contact simulations. His work frequently employs Bayesian modeling, neural network analysis, and cross-linguistic corpora to uncover universal principles in language processing. ACL Best Paper Award (2024) Best Paper Award for Computational Modeling of Language (2023) Marr Prize for Best Student Paper (2017) He has developed datasets like SPACER for error repair analysis and contributed to phonotactic learning frameworks. His collaborations span cognitive scientists, computational linguists, and neuroscientists, advancing understanding of language production, comprehension, and structural optimization.

Keith LeGrandView profile

Assistant Professor

• Multi-sensor Multi-object Tracking
• Spacecraft Navigation
• Space Domain Awareness
• +5 more

Keith LeGrand is an Assistant Professor in the School of Aeronautics and Astronautics at Purdue University, part of the Cislunar Space Initiative. He holds a Ph.D. in Aerospace Engineering from Cornell University (2022), an M.S. (2015), and a B.S. (2014) in Aerospace Engineering from Missouri University of Science and Technology. His research focuses on multi-object tracking, spacecraft navigation, space domain awareness, and intelligent sensor control. Key projects include developing probabilistic filters for cislunar space object tracking and information-driven autonomy systems. LeGrand leads the Sensing, Controls, and Probabilistic Estimation (SCOPE) Group, which advances space surveillance and autonomous systems. Notable awards include the 2025 AFOSR and ISIF Young Investigator Awards, 2023 AMOS Best Paper Award, and the E.F. Bruhn Teaching Award for excellence in undergraduate instruction. LeGrand advises a diverse group of graduate and undergraduate students in astrodynamics and space applications. His work is supported by grants from AFOSR, ISIF, and partnerships with institutions like Sandia National Laboratories and Draper Labs. The SCOPE lab collaborates on projects such as lunar landing navigation, satellite proximity operations, and multi-sensor fusion for space surveillance.

• Robotics
• Autonomous Systems
• Unmanned Aerial Vehicles (UAVs)
• +9 more

Nabil Aouf is a Professor of Robotics and Autonomous Systems in the Department of Electrical and Electronic Engineering at City, University of London, a position he has held since January 2019. Previously, from 2006 to 2018, he was Professor of Autonomous Systems at Cranfield University’s Defence and Security campus, where he also served as Head of the System and Autonomy Group and Research Lead of the Centre of Electronic Warfare, Information and Cyber. He earned his PhD in Electrical Engineering from McGill University Faculty of Engineering between 1999 and 2002. His research focuses on Robotics, Autonomous Systems, UAV Navigation, Computer Vision, and Fault-Tolerant Control . Key areas include visual odometry, sensor fusion (vision/IMU, RGBD, thermal-visible), robust control for UAVs, fault diagnosis in inertial systems, 3D perception, and autonomous landing. His work integrates theoretical control methods with real-time implementation in aerospace and defense contexts. His recent publications reflect a strong emphasis on robust optimization, multispectral vision, and real-time autonomous navigation. Trends indicate a focus on enhancing autonomy under uncertainty—through illumination-invariant stereo matching, L∞ optimization, and robust feature matching—particularly for UAVs operating in challenging environments. Nabil Aouf has collaborated extensively with researchers such as M. Richardson, O. Araar, T. Mouats, and M. Boulekchour across numerous projects in UAV control, sensor fusion, and autonomy. While no scientific awards are listed in the provided text, his leadership roles and sustained publication record in high-impact journals and conferences underscore his academic contributions. He has supervised or collaborated with several advisees including S.H. Almutairi, L. Chermak, I. Vitanov, and D. Nam, contributing to both theoretical developments and practical implementations in autonomous systems. His work has applications in aerospace, defense, planetary exploration, and critical infrastructure inspection.

John C HeatonView profile

Professor

• Asset pricing
• Portfolio allocation
• Time series econometrics
• +3 more

John C. Heaton is the Myron S. Scholes Distinguished Service Professor of Finance at the University of Chicago Booth School of Business and Director of the Anthony Pritzker Family Foundation - Family Office Initiative. He joined Chicago Booth in 2000 after serving as the Nathan S. and Mary P. Sharp Distinguished Professor of Finance at Northwestern University's Kellogg School of Management, with additional positions at MIT's Sloan School of Management and the Hoover Institution. Heaton maintains an active research affiliation as a research associate of the National Bureau of Economic Research. His educational background includes: Bachelor's degree in commerce from the University of Windsor (1982) Master's degree in economics from the University of Western Ontario (1984) PhD in economics from the University of Chicago (1989) Heaton's research program centers on asset pricing, portfolio allocation, and time-series econometrics , with particular emphasis on understanding how macroeconomic fluctuations affect financial markets. His work investigates the long-run risk-return tradeoff in asset valuation and how background risks from labor and entrepreneurial income influence investment decisions. He approaches these questions through rigorous econometric analysis combined with economic theory, seeking to bridge the gap between academic research and practical investment challenges. Analysis of Heaton's publications reveals a consistent focus on market frictions and their implications for asset pricing and portfolio choice. His research demonstrates how transaction costs, borrowing constraints, and incomplete markets affect investor behavior and market outcomes. A distinctive contribution is his work on long-run risk components that influence asset valuations despite being realized far into the future. Heaton's scholarly achievements have been recognized through: Alfred P. Sloan Research Fellowship (1993-1995) National Science Foundation Fellowship (1993-1998) Ongoing research affiliation with the National Bureau of Economic Research As an educator, Heaton teaches advanced courses in asset pricing, financial instruments, fixed income, and investments, with a focus on connecting theoretical frameworks to real-world investment challenges. His directorship of the Family Office Initiative reflects his expertise in wealth management across generations. His research continues to influence both academic discourse and practical approaches to understanding risk in financial markets, with current teaching commitments extending through 2026.

Bernhard von StengelView profile

Professor

• Game Theory
• Algorithmic Game Theory
• Computational Complexity
• +2 more

Bernhard von Stengel is a Professor of Mathematics at the Department of Mathematics, London School of Economics and Political Science . His work bridges game theory, computational complexity , and mathematical economics , with a focus on equilibrium computation and algorithmic aspects. Developed Game Theory Explorer , open-source software for analyzing strategic and extensive-form games. Organized major workshops like What is Strategic Information? (2024) and Game Theory and Machine Learning (2023). Authored the textbook Game Theory Basics (Cambridge University Press, 2021). His research spans zero-sum games , correlated equilibrium , inspection games , and communication over noisy channels . Recent work includes characterizing the Condorcet dimension of metric spaces (2024) and stable-set bounds for Nash equilibria in bimatrix games. He has collaborated with institutions like the Game Theory Society and contributed to public discourse via talks on algorithms' societal impact (2021) and game theory in politics (2020).