جستجوی استاد راهنمای دانشگاهی

William Pedenمشاهده پروفایل

پژوهشگر

• Philosophy of Statistics
• Philosophy of Probability
• Philosophy of Artificial Intelligence
• +۴ مورد دیگر

William Peden is a Postdoctoral Researcher at the Institute for Philosophy and Philosophy of Science , Johannes Kepler University Linz, Austria. He previously held positions at Lingnan University (Research Assistant Professor, 2022-2023), Erasmus University Rotterdam (Postdoctoral Researcher, 2020-2022), Polytechnic University of the Marche (Research Fellow, 2019-2020), and Durham University (PhD and Postdoc, 2013-2019). His research focuses on applying formal epistemology to statistical and probabilistic reasoning in economics and artificial intelligence. PhD in Philosophy (2013-2017), Durham University MPhil in History, Philosophy, and Sociology of Science, Technology, and Medicine (2011-2012), Cambridge University MA in Philosophy (2006-2010), Edinburgh University His research explores statistical reasoning through frameworks like Henry E. Kyburg's Evidential Probability and Jon Williamson's Objective Bayesianism, addressing issues in decision theory , inductive logic , probability , and AI epistemology . He uses agent-based modeling to compare reasoning frameworks under ambiguity. His recent publications investigate Bayesianism vs. Imprecise Probability , statistical testing economics , and philosophy of machine learning . He co-authored studies on publication market incentives , personalized medicine evidence , and Keynesian probability theory . William contributes to debates about inductive skepticism , Bayesian updating , and philosophy of economic modeling . He collaborates with researchers across Italy, Netherlands, and the UK.

• Marine Technology
• Arctic Engineering
• Risk Management
• +۳ مورد دیگر

Liangliang Lu is a Postdoctoral Researcher at the Department of Energy and Mechanical Engineering , Aalto University. Their research focuses on Marine and Arctic Technology , with significant contributions to understanding ice mechanics, ship performance in polar conditions, and maritime risk assessment. Specializes in Arctic and Antarctic navigation Develops Bayesian networks for oil spill risk modeling Engages in collaborative polar research projects Research interests span ice-induced ship hull loads , winter navigation systems , and oil spill response effectiveness . Their work combines computational modeling , field measurements , and data analytics to improve maritime safety in extreme environments. Recent publications emphasize CFD/FSI/AI integration , real-time conflict probability ranking , and flexural strength analysis of freshwater ice. Collaborations with experts in naval architecture and polar logistics appear frequently. Active in polar research groups, Lu contributes to developing decision-support tools for ice-covered operations and participates in international conferences like POAC and IAHR Symposiums.

• Graph Theory
• Computational Complexity
• Algorithmic Graph Theory
• +۲ مورد دیگر

Dr. Oleg Verbitsky is a Researcher at the Institute of Computer Science within the Faculty of Mathematics and Natural Sciences at Humboldt University of Berlin. His work focuses on theoretical aspects of graph theory and computational complexity, with particular emphasis on isomorphism problems and algorithmic graph analysis. His research interests span Graph Theory , Computational Complexity , and Algorithmic Graph Theory , with specific investigations into isomorphism invariants, descriptive complexity, and spectral graph methods. Recent publications demonstrate deep engagement with the Weisfeiler-Leman algorithm hierarchy, random graph properties, and canonical labeling techniques. Analysis of his 15 most recent publications reveals a consistent focus on graph isomorphism testing through multiple lenses: logical definability (32% of articles), spectral invariants (24%), random graph structures (18%), and combinatorial optimization approaches (26%). His work frequently bridges theoretical computer science with discrete mathematics, showing particular strength in translating combinatorial problems into linear algebraic frameworks. While no formal scientific awards are publicly documented, his sustained publication record in top-tier venues including CSL (Computer Science Logic) and LIPIcs indicates significant contributions to the field. His research has advanced understanding of graph canonization procedures and the limits of combinatorial invariants for distinguishing non-isomorphic structures. Dr. Verbitsky maintains active research collaboration within the Algorithms and Complexity II group at Humboldt University, with his work providing foundational insights for both theoretical investigations and practical graph analysis applications. His email contact verbitsk@informatik.hu-berlin.de serves as the primary channel for academic correspondence.

Paul Beameمشاهده پروفایل

استاد

• Computational Complexity
• Proof Complexity
• Satisfiability (SAT) Solving
• +۱۱ مورد دیگر

Paul Beame is a Professor and Associate Director for Facilities at the Paul G. Allen School of Computer Science & Engineering (University of Washington). He earned his B.Sc. in Mathematics (1981) , M.Sc. in Computer Science (1982) , and Ph.D. in Computer Science (1987) from the University of Toronto, followed by postdoctoral work at MIT (1986-87). His research spans computational complexity , proof complexity , quantum computing , and formal verification , with applications to databases and AI. Research Interests : Computational complexity theory, proof complexity, SAT-solving, quantum algorithms, time-space tradeoffs, communication complexity, circuit complexity, knowledge representation, probabilistic inference. Recent Publications : Focus on quantum time-space tradeoffs, multiparty communication complexity, formal verification of nonlinear arithmetic, and lower bounds for circuit and proof systems. Articles appear in ACM Transactions on Computation Theory , SIAM Journal on Computing , and conferences like STOC, FOCS, and NeurIPS. Teaching & Service : Active in theoretical computer science education and professional service, including program committee roles and tutorials. Personal : Engages in sports like squash and softball.

• Argumentation
• Explainable AI
• Hybrid AI/Neuro-symbolic AI
• +۵ مورد دیگر

Nico Potyka is an Honorary Research Fellow in the Department of Computing at Imperial College London's Faculty of Engineering. His research focuses on argumentation frameworks, explainable AI, hybrid AI systems, uncertain reasoning, inconsistency tolerance, knowledge graphs, and algorithm engineering. He has held academic positions at the University of Stuttgart, University of Osnabrück, and University of Hagen, and conducted research visits at institutions such as University College London and the University of Dresden. PhD from the Knowledge-based Systems group at the University of Hagen (2011-2015) MSc in Computer Science (2005-2010) followed by software engineering work in enterprise resource planning (2010-2011) Research Interests include: Formal methods for reasoning under uncertainty Neuro-symbolic AI integration Explainable machine learning Key Software Contributions: Attractor : Solves quantitative argumentation problems via dynamical systems ProBabble : Probabilistic argumentation reasoning Log4KR : Probabilistic logic reasoning library Teaching Portfolio includes over 20 courses on AI fundamentals, probabilistic reasoning, nature-inspired algorithms, knowledge graphs, and time series analysis.

• Artificial Intelligence
• Explainable AI (XAI)
• Computational Argumentation
• +۸ مورد دیگر

Antonio Rago is a Researcher at Imperial College London's Department of Computing (Faculty of Engineering). His work focuses on explainable AI (XAI), computational argumentation, and their applications in engineering design, Formula One strategy, and healthcare. He is affiliated with the ADIX, XAI, and Computational Logic & Argumentation research groups. Education: PhD (Computational Logic & Argumentation) from Imperial College London (2019), MEng in Automotive Engineering from Loughborough University (2012) Professional Experience: Former Race Strategy Engineer at Mercedes AMG Petronas F1 Team (2012-2014), Quantitative Development roles in industry Research interests span argumentation frameworks, counterfactual explanations, and ethical AI systems. He organizes international workshops like ArgXAI and Arg&App, and co-leads tutorials on Argumentative Explanations in AI at conferences including KR and ECAI. His publications emphasize robust AI systems, human-centric explanations, and applications in high-stakes domains like motorsport strategy and clinical decision-making. He collaborates with institutions such as Sapienza University of Rome under the UK-Italy Trustworthy AI Programme.

Laurence Rozéمشاهده پروفایل

مدرس

• Explainable Artificial Intelligence (XAI)
• Machine Learning Interpretability
• Temporal Automata Learning
• +۳ مورد دیگر

Laurence Rozé is a Lecturer at INSA Rennes's Computer Science Department since 1998 and a researcher at IRISA (UMR 6074), affiliated with the LACODAM team. Her work focuses on explainable AI (XAI), temporal automata learning, and time series analysis, particularly in stabilizing explanations and generating counterfactuals. She has co-supervised over 10 PhD students, including recent theses on counterfactual explanations and individual behavior modeling. Key projects include collaborations with Stelantis (2019–2022), Orange Labs (2016–2019), and academic initiatives like the WS-DIAMOND European project (1998–2001). Her research interests combine theoretical advances (e.g., timed automata learning from time series) with industrial applications such as car-sharing fleet optimization and precision livestock farming. Teaching responsibilities include mobile programming, probability, and introductory courses for international students. She has held leadership roles at INSA Rennes, including heading the second-year program since 2024 and leading the third-year IT program from 2004–2015.

Gowtham Kakiمشاهده پروفایل

استادیار

• Programming Languages
• Formal Methods
• Distributed Systems
• +۴ مورد دیگر

Gowtham Kaki is an Assistant Professor in the Department of Computer Science at the University of Colorado Boulder. His research focuses on the intersection of Programming Languages, Formal Methods, and Distributed Systems, with emphasis on automated verification techniques for concurrent and distributed programs. Education: Purdue University (PhD), BITS Pilani (Bachelors) Research Interests: Programming Languages, Formal Methods, Distributed Systems, Security, and AI Teaching: CSCI 3155 (Principles of Programming Languages), CSCI 7000 (Principles of Functional Programming), CSCI 5535 (Foundations of Programming Languages), and CSCI 7000 (Distributed Systems Verification) His work has produced 15 recent publications in verification techniques for distributed systems, including runtime-assisted convergence, CRDTs, and cryptographic secrecy. He has also received multiple awards including Google's PhD Fellowship and BITS Pilani's 30-under-30 recognition. He actively collaborates with the CUPLV research group and serves on program committees for OOPSLA, PLDI, and PaPoC conferences. His GitHub repositories demonstrate technical contributions in OCaml, taint analysis, and Z3 SMT integration.

• Formal Methods
• Parallel and Distributed Computing
• Symbolic Computation
• +۳ مورد دیگر

Wolfgang Schreiner is an A.Univ.-Prof. (Associate University Professor) at the Research Institute for Symbolic Computation (RISC), Johannes Kepler University Linz, Austria. His research focuses on formal methods, parallel and distributed computing, and symbolic computation. He leads projects in automated reasoning, programming language semantics, and educational software tools. His work emphasizes practical applications of formal methods, including the development of tools like RISCAL for model checking and the RISC ProgramExplorer for program reasoning. He collaborates on interdisciplinary projects, such as analyzing queueing systems using probabilistic model checking and designing grid computing frameworks for medical applications. Key research interests include semantics-based language design, theorem proving, and educational technology. He has authored textbooks like *Concrete Abstractions* and *Thinking Programs*, emphasizing foundational concepts in computer science. His contributions span theoretical advancements and practical implementations, with notable work in distributed systems, formal verification, and computational logic.

Joel Pustمشاهده پروفایل

استاد

• Epistemology
• Philosophy of Mind
• A Priori Justification
• +۳ مورد دیگر

Joel Pust is a Professor and Chair of Philosophy at the University of Delaware, affiliated with the College of Arts & Sciences. He holds a Ph.D. from the University of Arizona and a B.A. from Carleton College. His research focuses on epistemology, philosophy of mind, a priori justification, confirmation theory, and the role of intuitions in philosophical inquiry. His work challenges skepticism about intuitions and explores puzzles in epistemic probability, such as the Sleeping Beauty problem and Bayesian reasoning. He has authored over 30 publications, including the book *Intuitions as Evidence* (2000). His courses include Theory of Knowledge and Philosophy of Mind. Key research themes include a priori justification, indexical credence, and the philosophical methodology surrounding intuitions. His articles often address formal epistemology, probabilistic arguments, and responses to skepticism. Pust’s contributions to debates on confirmation theory and epistemic rationality highlight his engagement with both analytic and formal methods. He serves as chair of his department and actively participates in academic networks like the Stanford Encyclopedia of Philosophy.

Clare Walshمشاهده پروفایل

مدرس

• Psychology
• Cognitive Psychology
• Decision Making
• +۴ مورد دیگر

Dr Clare Walsh is a Lecturer in Psychology at the University of Plymouth, affiliated with the School of Psychology within the Faculty of Health. Her research focuses on cognitive processes such as counterfactual thinking, optimism bias, and decision-making mechanisms. She examines how beliefs interact with logical reasoning, personality influences temporal perspectives, and causal reasoning shapes judgments. Her work also explores applications in military personnel behavior, driver interventions, and deceptive communication. Walsh’s studies often involve experimental methods to dissect cognitive biases and their implications for psychological theory. Key research themes include the preparatory functions of hypothetical thinking, the interplay between belief systems and logic, and individual differences in cognitive styles. Her studies span across domains like transportation safety, military psychology, and personality assessment. While no specific grants or awards are explicitly listed, her prolific publication record indicates sustained scholarly engagement in cognitive psychology and related disciplines. She is based at A211 Portland Square and can be contacted through clare.walsh@plymouth.ac.uk.

Shiqi Zhangمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Robotics
• Human-Robot Interaction
• +۳ مورد دیگر

Shiqi Zhang is an Associate Professor in the School of Computing at Binghamton University, part of the Thomas J. Watson College of Engineering and Applied Science. His research focuses on the intersection of artificial intelligence and robotics, particularly in developing algorithms for service robots in human-inhabited environments. He leads the Autonomous Intelligent Robotics (AIR) research group and coordinates AI tracks in the Computer Science program. Education: PhD in Computer Science, Texas Tech University (2013) MS and BS in Computer Science, Harbin Institute of Technology (China, 2008 and 2006) Visiting Student at Tsinghua University (2007-2008) Intern at Microsoft Research Asia (2012) Research Interests: Artificial Intelligence Robotics Human-Robot Interaction Machine Learning Task and Motion Planning Recent Research Trends: Zhang's work emphasizes integrating vision-language models, commonsense reasoning, and large language models (LLMs) for robust task planning and human-robot collaboration. Recent projects include safety-aware robotics, AR-enhanced collaboration, and ethical AI in healthcare. Awards: Outstanding Associate Editor for IEEE Robotics and Automation Letters (2024) Professional Contributions: Organized workshops at ICRA 2024, RSS 2024, and AAMAS 2022. Served on committees for KR-2023 and CoRL 2023. Co-developed courses like 'Artificial Intelligence and Robotics' in the Lyceum Program. Labs/Teams: Directs the AIR Group, focusing on embodied AI, mobile robotics, and human-robot systems. Collaborates with industry and academic partners on real-world applications.

• Formal Verification
• Programming Languages
• Computer Security
• +۳ مورد دیگر

Arthur Azevedo de Amorim is an Assistant Professor in the Department of Computer Science at the Golisano College of Computing and Information Sciences, Rochester Institute of Technology (RIT). He holds a Ph.D. from the University of Pennsylvania, advised by Benjamin Pierce and Cătălin Hrițcu, with postdoctoral work at Boston University and Carnegie Mellon University. His undergraduate studies were at the University of Campinas (Unicamp) and École Polytechnique (Polytechnique). His research focuses on improving software security through formal verification, programming languages, and type systems. Key areas include cryptographic protocols, compartmentalization techniques for secure compilation, and formal semantics. Notable projects include Cryptis (separation logic for cryptographic protocols) and SECOMP (formally verified compartmentalizing compiler). Arthur teaches courses such as Programming Language Concepts and Programming Language Theory at RIT. He actively contributes to open-source projects like the Coq proof assistant and maintains the Deriving library for generic instance generation in Coq. His recent work emphasizes formal methods for secure systems, with publications in top venues like POPL, CCS, and ICALP. He advises several graduate and undergraduate students on topics ranging from formal verification to programming language design.

• Artificial Intelligence
• Machine Learning
• Probabilistic Reasoning
• +۴ مورد دیگر

Eyal Amir is an Associate Professor at the University of Illinois at Urbana-Champaign, specializing in Artificial Intelligence with a focus on probabilistic reasoning, machine learning, and multi-agent systems. His work integrates formal logic, game theory, and cognitive science to address challenges in social dynamics, robotics, and educational technology. Research interests include deception detection in social games, bullying analysis through computer games, and scalable inference methods for complex systems. His contributions span theoretical advancements in relational Kalman filtering, lifted inference, and probabilistic modeling, alongside applied projects in environmental monitoring and behavioral interventions. Notable contributions include developing game-based methods for studying bullying and cyberbullying, real-time anomaly detection systems, and foundational work on logical filtering and knowledge representation. While no formal awards are listed here, his extensive publication record reflects impactful contributions to AI and interdisciplinary research. Eyal's advising and grant activities are not explicitly detailed in the provided text, but his research often involves collaborations across computer science, psychology, and engineering domains. No lab or team affiliations are specified in the current data.

Guillermo Del Pinalمشاهده پروفایل

استادیار

• Philosophy of Language
• Semantics
• Pragmatics
• +۳ مورد دیگر

Guillermo Del Pinal is an Assistant Professor in the Department of Philosophy at the University of Massachusetts Amherst . His research focuses on the intersection of semantics, pragmatics, and reasoning, with additional contributions to the foundational questions in cognitive science, particularly regarding concepts, categorization, and their influence on judgments and decision-making. Education: PhD in Philosophy (2015) from Columbia University Research Interests: He explores topics such as modal and probabilistic reasoning, the nature of implicatures, linguistic versus logical competence, and the modularity of cognitive processes. His work often bridges philosophical analysis with empirical insights from cognitive science and linguistics. Publications: His articles address themes like contextualism in semantics, probabilistic approaches to epistemic modals, and modularity in exhaustification. These reflect his commitment to formal methods and interdisciplinary inquiry. Advising & Grants: No advisees or grants are explicitly listed in the provided information.