Find Academic Supervisors

• Logic Programming
• Knowledge Representation
• Artificial Intelligence
• +6 more

Bart Bogaerts is an Associate Professor in the Department of Computer Science at KU Leuven's Faculty of Engineering Science. He is affiliated with the Declarative Languages and Artificial Intelligence (DTAI) research unit and is a member of Leuven.AI - KU Leuven Institute for Artificial Intelligence. Bogaerts serves on the Council of the Faculty of Engineering Science as senior academic staff and participates in the Programme Committee for Artificial Intelligence curriculum development. His research focuses on foundational aspects of logic programming and knowledge representation, with particular expertise in approximation fixpoint theory, higher-order logic programming, and non-monotonic reasoning. Bogaerts investigates the theoretical underpinnings of stable model semantics, justification frameworks, and executable query languages. His work bridges theoretical computer science with practical applications in artificial intelligence and knowledge-based systems. Bogaerts' publication record demonstrates consistent contributions to top venues in logic programming and artificial intelligence. His recent work shows increasing focus on category-theoretic approaches to approximation theory, distributed web traversal specifications, and certified model expansion techniques. The publications reveal a strong emphasis on formal methods with applications spanning from theoretical mathematics to practical AI systems. As a promotor for multiple significant research projects, Bogaerts leads investigations into certified answer set programming (CertifASP), first-order model expansion (CertiFOX), proof generation for combinatorial optimization, distributed configuration problems, and knowledge integration paradigms. These projects, funded through 2028-2029, demonstrate his leadership in advancing the theoretical foundations of AI and logic programming. Bogaerts is actively involved in teaching courses on knowledge representation and reasoning, contributing to the development of next-generation AI researchers. His work within the DTAI research unit positions him at the forefront of declarative AI approaches in Belgium's leading research university.

Stephen ChongView profile

Professor

• Programming Languages
• Information Security
• Language-based Security
• +3 more

Stephen Chong is a Gordon McKay Professor in the Harvard John A. Paulson School of Engineering and Applied Sciences , where he co-directs the Undergraduate Studies in Computer Science program. His research intersects programming languages and information security , focusing on language-based security frameworks. Education : PhD in Computer Science from Cornell University (2008), B.Sc.(Hons) and B.A. from Victoria University of Wellington (New Zealand). Research : Develops tools like Formulog (Datalog + SMT for static analysis) and Accrue (Java interprocedural analysis), emphasizing security guarantees proportional to programmer effort. Grants : Funded by NSF , DARPA , AFOSR , and Google Faculty Research Award . Recent publications focus on neurosymbolic approaches (e.g., Guess & Sketch ), Datalog synthesis (e.g., Making Formulog Fast ), and quantitative robustness in cyber-physical systems. His group has pioneered formal methods for secure assembly transpilation and sensor attack modeling. Awards : NSF CAREER Award AFOSR Young Investigator Award Sloan Research Fellowship Advising : Supervised numerous PhD and senior thesis students, including Aaron Bembenek , Anitha Gollamudi , and Lucas Waye . Mentored projects like AbcDatalog (multi-threaded Datalog engine) and Shill (secure shell scripting). Labs/Teams : Leads the Programming Languages at Harvard group, collaborating with institutions globally. Organized workshops (e.g., NSF Workshop on Formal Methods for Security ) and chaired committees at conferences like CSF , POPL , and PLDI .

Yao LiView profile

Assistant Professor

• Programming Languages
• Formal Verification
• Dependent Types

Yao Li is an Assistant Professor of Computer Science at Portland State University, specializing in Programming Languages, Formal Verification, and Dependent Types. They earned a Ph.D. in Computer and Information Science from the University of Pennsylvania (2022), supervised by Stephanie Weirich, and hold a Master’s and Bachelor’s in Software Engineering from Shanghai Jiao Tong University (2016, 2013) under Zhengwei Qi. Ph.D., Computer and Information Science, University of Pennsylvania (2022) M.S., Software Engineering, Shanghai Jiao Tong University (2016) B.S., Software Engineering, Shanghai Jiao Tong University (2013) Their research focuses on formal verification of functional programming languages, particularly Haskell, and mechanized proofs using tools like Coq. They work on specifying and verifying networked servers, lazy program cost analysis, and embedded systems through program adverbs and Tlön embeddings. Recent publications (2018-2025) demonstrate expertise in Haskell verification, formal methods, and interaction trees. Key trends include bridging the gap between mechanized formalization and real-world code, advancing lazy evaluation semantics, and enhancing software verification through dependent types. Yao Li actively participates in academic service as a committee member and session chair in conferences like POPL, ICFP, and PLDI, contributing to artifact evaluation, program organization, and student research competitions.

Nate FosterView profile

Professor

• Programming Languages
• Networking
• Formal Verification
• +3 more

Nate Foster is a Professor of Computer Science at Cornell University and a Visiting Researcher at Jane Street . During the 2023-24 academic year, he served as a Visiting Professor at EPFL in the Data Center Systems Laboratory. His research bridges Programming Languages and Networking , focusing on formal verification, data plane programming, and language design for networked systems. His recent work includes developing symbolic automata for network verification (e.g., Active Learning of Symbolic NetKAT Automata , StacKAT ), creating efficient verifiers like KATch , and advancing type safety in data plane programming (e.g., SafeP4 ). These efforts span formal methods, algorithm optimization, and practical networked systems. Notable scientific awards include: NSF CAREER Award Sloan Research Fellowship ACM SIGCOMM Rising Star Award ACM SIGPLAN Robin Milner Award He actively contributes to PLDI, POPL, OOPSLA, and ICFP, serving as author, editor, and committee member. His GitHub repositories include tools for academic website templates and programming language research codebases.

• Optimization methods
• Metaheuristics
• Heuristics
• +12 more

Mina Mirhosseini is a Research Fellow at the Faculty of Logistics, Molde University College, Norway. She holds a PhD in Computer Science from Shahid Beheshti University of Tehran, Iran, and has prior academic experience as a faculty member and lecturer in Iran and as a remote teaching assistant at the University of Hertfordshire, UK. Her primary research interests include Optimization Methods, Metaheuristics, Heuristics, Linear Integer Programming, Parallel Processing, Machine Learning, Artificial Intelligence, and Logistics. She has made significant contributions to solving complex computational problems such as the n-similarity problem and Mixed Integer Linear Programming (MILP) models using hybrid and parallel algorithms, particularly in the context of high-level synthesis and wireless sensor networks. The analysis of her recent publications reveals a strong focus on developing and applying advanced optimization techniques, especially quantum-inspired gravitational search algorithms and parallel genetic algorithms, to real-world engineering and computational challenges. Her work consistently emphasizes performance improvement, scalability, and load balancing in distributed and heterogeneous computing environments. Mina Mirhosseini has an extensive publication record in high-impact journals such as IEEE Transactions on Parallel and Distributed Systems, Journal of Parallel and Distributed Computing, Journal of Supercomputing, and Computers and Electrical Engineering. Her research has been published across a range of venues, reflecting interdisciplinary work at the intersection of computer science, electrical engineering, and applied optimization. She has actively contributed to the academic community through roles such as program committee member and executive committee member for conferences on fuzzy systems, swarm intelligence, and evolutionary computation. Her academic journey includes teaching and research roles in Iran, demonstrating a sustained commitment to higher education and scientific inquiry. Mina Mirhosseini is part of the research group focused on Planning, Optimization and Decision Support at Molde University College. Her current work continues to advance the state-of-the-art in parallel and metaheuristic optimization methods, with applications in logistics, synthesis, and sensor network design.

James BrotherstonView profile

Professor

• Logic
• Computation
• Separation Logic
• +5 more

James Brotherston is Professor of Logic and Computation in the Programming Principles, Logic and Verification Group (PPLV) at University College London's Department of Computer Science. His research spans logic, computation, and verification, with a focus on separation logic, cyclic proofs, and automated reasoning for program correctness. Research interests include: Foundations of program verification using separation logic Automated reasoning via cyclic proof systems Concurrency and deadlock detection Formal methods for security and resource management Applications of substructural logics in computer science His publications demonstrate consistent focus on logical foundations of verification, with recent work expanding into concurrency testing and atomic operations compatibility. Trends include theoretical advances in proof systems alongside practical verification tools. Scientific awards and grants: Facebook Testing and Verification Research Award (2019) £6M EPSRC Programme Grant for IRIS project (2018-2024) Facebook Faculty Grant (2015) Multiple EPSRC fellowships and grants totaling over £1.2M (2008-2017) He has supervised 12+ PhD students and research fellows, with current students working on verification of concurrent systems. Leads research in the PPLV group and collaborates internationally on logical frameworks.

• Management
• Organizational Behavior
• Leadership Development
• +5 more

Dr. Monika Kwiecińska is a Professor at the Department of Economics and Enterprise Organization at Wrocław University of Economics (UEW). Her expertise spans management, nonprofit organizations, human resources, leadership development, and generational studies. She holds certifications as a business coach, MindSonar consultant, and systemic therapist, emphasizing her multidisciplinary approach. Her research focuses on organizational integration, psychological contracts in workplaces, and the role of corporate foundations in social responsibility. Research Interests: Professor Kwiecińska explores how generational differences (e.g., Gen Z) impact workplace dynamics, leadership models informed by integral theory, and the strategic use of corporate foundations. She analyzes organizational culture in nonprofit sectors and evaluates the effectiveness of corporate community involvement (CCI) initiatives. Her work bridges theoretical frameworks (e.g., action logic, spiral dynamics) with practical applications in leadership and HR. Publications: Her recent work examines generational value systems, corporate philanthropy, and leadership selection during mergers. Key themes include the psychological contract between employers and modern employees, and the role of AHP modeling in managerial decision-making. Earlier research explored nonprofit organizational culture and strategic alliances between for-profit and non-profit entities. Awards: No scientific awards explicitly listed in the provided materials. Grants & Advising: No specific grants or advisee students are documented here. However, her extensive publications suggest active involvement in research projects and likely advisory roles in organizational development initiatives. Labs/Teams: Affiliated with the Department of Economics and Enterprise Organization at UEW, though no specific lab or research team names are mentioned.

• Synthetic Biology
• CRISPR-Based Gene Circuits
• Molecular Engineering
• +3 more

Yasu Xu is a Postdoctoral Researcher at the McGovern Institute for Brain Research, part of MIT's renowned Brain and Cognitive Sciences program. Their research focuses on synthetic biology, particularly leveraging CRISPR-Cas systems to engineer programmable gene circuits in Escherichia coli. Xu's work emphasizes the design of bistable genetic toggle switches and plasmid systems with tunable copy numbers, integrating principles from physics and systems biology to improve CRISPR-based circuit performance. Research interests span synthetic biology, gene regulation mechanisms, and microbial engineering with applications in biotechnology and biomedical research. Xu's contributions address challenges in programmable genetic systems, including circuit stability, thermodynamic determinants of CRISPR-Cas interactions, and high-throughput assay development.

• Artistic Education
• Ecological Art
• Green Aesthetics
• +4 more

Montserrat Calbó i Angrill is a Professor in the Department of Specific Didactics at the University of Girona , affiliated with the Faculty of Education and Psychology . She coordinates visual arts education programs and has served as Vice-Dean of Teachers (2008-09). As a researcher in the Education, Heritage and Intermediate Arts (GREPAI) group under the Institute of Educational Research , her work spans artistic education, ecological art, and interdisciplinary learning. Education : PhD in Fine Arts (2001) from the University of Barcelona with a thesis on environmental interpretations in artistic education. Research Focus : Integrating art into broader educational contexts, emphasizing sustainability, teacher training, and creative learning. Her recent publications highlight interdisciplinary art education trends, including ecological art projects (2022), structured logical materials for early childhood mathematics (2022), and digital education initiatives like UdiGitalEdu (2020). She explores multisensory and multicultural approaches, such as visual poetry analysis (2011-2012) and heritage education (2005-2011). Contact : montserrat.calbo@udg.edu

Tullio Ceccherini SilbersteinView profile

Associate Professor

• Mathematical Analysis
• Group Theory
• Cellular Automata
• +5 more

Tullio Ceccherini Silberstein is an Associate Professor of Mathematical Analysis in the Department of Engineering at the University of Sannio, Italy. He also maintains an affiliation with the Istituto Nazionale di Alta Matematica 'Francesco Severi' in Rome. His teaching responsibilities include Mathematics courses for Civil Engineering and Energy Engineering programs. His primary research interests span Mathematical Analysis, Group Theory, Cellular Automata, Harmonic Analysis, Representation Theory, and Symbolic Dynamics. His work has significantly contributed to the understanding of the Garden of Eden theorem for cellular automata, finite Gelfand pairs, and ergodic properties of dynamical systems. His research demonstrates strong connections between algebraic structures, combinatorial methods, and dynamical systems. Analysis of his recent publications reveals a continued focus on the intersection of algebraic structures and dynamical systems, with particular emphasis on sofic groups, surjunctivity, and the Garden of Eden theorem across various mathematical contexts. His work shows evolution from foundational studies in cellular automata to increasingly sophisticated applications in group theory and algebraic dynamics. Throughout his career, Ceccherini Silberstein has maintained an active presence in the mathematical community through numerous conference presentations and collaborations, particularly with Michel Coornaert. His work bridges theoretical mathematics with applications in symbolic dynamics and computational group theory.

• Metaphysics/Ontology
• Meta-philosophy
• Philosophy of Science
• +7 more

Laurenţiu Staicu is a Professor at the Department of Theoretical Philosophy, Faculty of Philosophy, University of Bucharest, where he has held progressive academic positions since 1997, currently serving as University Professor (2017-present). He also functions as a philosophical counselor at Bellanima Medical Center (2012-present) and maintains active involvement in multiple philosophical institutions. His academic formation includes: Postdoctoral Research Program at University of Bucharest (2010-2012) PhD in Philosophy from University of Bucharest (1997-2002) with thesis on metaphysics of natural genres Undergraduate studies in Philosophy at University of Bucharest (1990-1995) Staicu's scholarly work demonstrates remarkable breadth across philosophical disciplines with particular emphasis on metaphysics/ontology, philosophy of science, and applied ethics. His research consistently bridges traditional philosophical inquiry with scientific practice, especially in biology and evolutionary theory. He has developed significant expertise in knowledge management, ethics of science, and philosophical counseling, with notable contributions to understanding Darwinism, rationality, and evolution from philosophical perspectives. His teaching portfolio includes Philosophy of Biology, Metaphysics, Ethics of Science, and Models of Evolution for undergraduate and graduate students. Analysis of his recent publications reveals a clear trajectory toward increasingly interdisciplinary work connecting philosophical foundations with contemporary ethical challenges. His scholarship shows growing engagement with bioethics, particularly regarding informed consent in Romanian psychiatry, the philosophical implications of biomedical technologies, and the ethical dimensions of cultural evolution. There's also notable attention to how classical philosophical frameworks like Aristotle's categories remain relevant to modern problems, alongside examination of digital culture phenomena like trolling through philosophical lenses. Staicu has coordinated multiple significant research projects: "Teorii ale complexității" (1998-2000), World Bank-funded interdisciplinary project "Fundamente teoretice și metodologice în dinamica sistemelor naturale complexe" (2006-2008), CNCSIS-funded research "Consimțământul informat în psihiatria din România" (2012-2016), CNCSIS-funded collaboration with University of Medicine and Pharmacy of Bucharest As an institutional builder, Staicu serves as: Founding member and president of the Romanian Association for Practical Philosophy Founding member of Romanian Society for Analytic Philosophy and Romanian Society of Philosophy Founding member and former director of Center for Logic, Philosophy and History of Science Editorial board member for Logos & Episteme, Philosophy Study, and Analele Universității din Craiova Evaluator for European Science Foundation and ARACIS His international engagement includes Erasmus teaching appointments at Autonomous University of Barcelona (2007) and University of Oxford (2017), plus research visits to institutions like University of Tulsa.

John ConlonView profile

Assistant Professor

• Behavioral Economics
• Experimental Economics
• Cognitive Science
• +5 more

John Conlon is an Assistant Professor at Carnegie Mellon University's Dietrich College of Humanities and Social Sciences within the Department of Social and Decision Sciences . As a behavioral economist, his work bridges economics and psychology through experimental methods to analyze how attention, memory, and cognitive biases influence economic decision-making. Ph.D. in Business Economics from Harvard University B.A. in Economics and Philosophy from The Ohio State University Postdoctoral researcher at Stanford University His research investigates belief formation under cognitive constraints, focusing on how selective memory recall, attention allocation, and social learning distort economic choices. Key applications include education decisions (major selection, salary expectations) and labor markets (teacher recruitment, job search behavior). Article trends reveal systematic exploration of non-Bayesian belief updating , social learning asymmetries , and cue-driven economic biases . These studies employ dual-task experiments , nationally representative surveys , and household fieldwork to challenge rational choice frameworks. Dr. Conlon's interdisciplinary work aligns with Dietrich College's focus on cross-disciplinary collaboration between economists and psychologists. His methodological approach integrates structural modeling with behavioral interventions to address policy-relevant questions.

Rodrigo ZamithView profile

Associate Professor

• News innovation
• Emerging media technologies
• Data-driven news work
• +6 more

Rodrigo Zamith is an Associate Professor and Chair of the Journalism Department at the University of Massachusetts Amherst. He is also a Faculty Associate of UMass' Computational Social Science Institute and a Faculty Affiliate of its Department of Communication. His work bridges journalism and technology, focusing on the evolving media landscape and digital research methods for social scientists. Dr. Zamith received his academic training from: Ph.D. in Mass Communication from the University of Minnesota M.S. in Mass Communication from Florida International University B.A. in Journalism from the University of Minnesota Rodrigo Zamith's research interests focus on the intersection of journalism and technology, examining how digital platforms and algorithms reshape news production and consumption. His work explores news innovation, emerging media technologies, data-driven news work, algorithms in journalism, and computational social science. He investigates how journalistic practices are reconfigured in digital environments and develops innovative digital research methods for studying media phenomena. His scholarship draws on theoretical frameworks from sociology, psychology, science & technology studies, and economics, employing both quantitative and qualitative methodologies. His recent publications demonstrate a clear trajectory examining the role of algorithms, data, and digital platforms in journalism. His work spans computational analyses of news recommendation systems, examinations of open-source infrastructure in newsrooms, studies of visual climate change communication on social media, and investigations into how journalists navigate audience metrics. His research reveals both the challenges and opportunities presented by technological change in journalism, with particular attention to issues of transparency, trust, and democratic implications. Dr. Zamith has received significant recognition for his scholarly contributions: Nafziger-White-Salwen Dissertation Award (best dissertation in mass communication) Finalist for the Gene Burd Dissertation Award Finalist for Digital Journalism's Article of the Year award Lilly Teaching Fellow FlexLearning Fellow Recipient of UMass' College Outstanding Teaching Award Finalist for the University's Distinguished Teaching Award As an educator, Dr. Zamith teaches both conceptually-oriented and skills-oriented courses including Data-Driven Storytelling, Introduction to Journalism, International Journalism, Content Analysis, and Introduction to Visual Storytelling. His teaching excellence has been recognized through multiple awards. While specific grant information isn't detailed in the provided text, his research output suggests active engagement with funding opportunities in computational social science and digital journalism. Dr. Zamith is affiliated with UMass' Computational Social Science Institute, where he contributes to interdisciplinary research on digital methods. His work with GitHub repositories suggests engagement with open-source communities, and his research on newsroom technology indicates connections with media organizations exploring digital innovation.

John H. ReifView profile

Professor

• DNA Computing
• Molecular Assembly
• Robot Motion Planning
• +4 more

John H. Reif is a Professor of Computer Science at Duke University, with secondary appointments in the Thomas Lord Department of Mechanical Engineering and Materials Science (since 2024) and the Department of Electrical and Computer Engineering (since 2016). His research spans DNA computing , molecular assembly , robot motion planning , and quantum computation , focusing on programmable biomolecular systems and parallel algorithms. Education: Ph.D. in Applied Mathematics, Harvard University (1977) M.S. in Applied Mathematics, Harvard University (1975) B.S. in Applied Mathematics and Computer Science, Tufts University (1973) His recent publications emphasize DNA strand displacement , molecular-scale learning systems , and 3D DNA nanostructures , with applications in diagnostics, data storage, and nanofabrication. Articles highlight innovations in error-resilient DNA circuits, programmable self-assembly, and algorithmic modeling of molecular processes. Scientific Awards: Fellow of the American Association for the Advancement of Science (AAAS) Fellow of the Association for Computing Machinery (ACM) Fellow of the Institute of Electrical and Electronics Engineers (IEEE) He has supervised numerous Ph.D. students and postdoctoral researchers , including Rajiv Nagipogu (adaptive molecular systems) and Xin Song ( Daniel Fu , DNA computation on cell membranes). His work is funded by grants from the Defense Advanced Research Projects Agency (DARPA) and the National Science Foundation (NSF) , with recent focus on molecular-scale AI and DNA polymerase reaction networks. Reif co-founded Domus Diagnostics , developing affordable infectious disease testing solutions. He served as General CoChairman of FNANO24 and contributes to teaching courses like Computational Complexity and Molecular Assembly and Computation .

Noortje VenhuizenView profile

Assistant Professor

• Computational Semantics
• Discourse Processing
• Language Comprehension
• +3 more

Noortje Venhuizen is an Assistant Professor in the Department of Cognitive Science and Artificial Intelligence at the Tilburg School of Humanities and Digital Sciences, Tilburg University. She serves as Academic Director for the BSc Cognitive Science and Artificial Intelligence program since 2024, and has held academic positions at Saarland University (2015-2022) including roles as Scientific Staff member and Principal Investigator in SFB 1102 projects. PhD in Computational Semantics (University of Groningen, 2015) MSc in Logic (ILLC, University of Amsterdam, 2011) BSc in Artificial Intelligence (Utrecht University, 2009) Her research focuses on expectation-based language comprehension, neurocomputational modeling of semantic processing, distributional formal semantics, and pragmatic reasoning in discourse. Key contributions include PDRT-SANDBOX (Haskell NLP library) and DFS Tools (Prolog implementation of distributional formal semantics). Recent publications (2023-2025) explore multimodal word meaning, informativity in reference production, and neurocognitive models of surprisal processing. Her work combines formal semantics with cognitive neuroscience and computational modeling. LOT Grotevragenprijs essay contest - Second Prize She has presented research at major conferences including CogSci, AMLaP, and Sinn und Bedeutung. Current teaching includes courses on artificial intelligence, statistics, and semantic theory.