جست‌وجوی استاد و پژوهشگر

• Algorithmic Game Theory
• Stochastic Games
• Distributed Systems
• +۴ مورد دیگر

Hugo Gimbert is a CNRS Researcher at LaBRI (Laboratoire Bordelais de Recherche en Informatique), affiliated with the University of Bordeaux, where he serves as a PhD advisor and contributes to the Formal Methods research team. His work bridges theoretical computer science with practical applications in diverse domains. His research spans Algorithmic Game Theory, Stochastic Games, Distributed Systems, and Robotics, with current focus on stochastic games with partial observation, decidability of distributed games, and applications in precision agriculture. He explores intersections with social choice theory, probabilistic logics, and humanoid robot control using Markov Decision Processes. Publications from 2010-2017 reveal consistent contributions to game theory foundations (stochastic/mean-payoff/parity games), automata theory (decidability problems, stabilization monoids), and applied robotics (vineyard trellising systems). His work demonstrates a trajectory from pure theoretical results toward real-world implementations in agriculture and education systems. Gimbert actively mentors PhD candidates including Soumyajit Paul, Simon Mauras, and Edon Kelmendi. He leads critical national projects: serving as Chargé de mission for Parcoursup (France's centralized college admission platform) since 2018, developing its core algorithms with Claire Mathieu to handle quotas, housing constraints, and transparency requirements. He also co-founded the Rhoban System spin-off applying robotic control algorithms to precision agriculture. As a core member of the Rhoban robotics project, he develops real-time image processing systems for robot soccer competitions. His software contributions include Stamina (automata theory toolkit), Marmotte (CNRS committee management system), and BipBip (ROS-based weeding robot for vineyards), demonstrating commitment to translating research into tangible societal impact.

Işıl Dilligمشاهده پروفایل

دانشیار

• Programming Languages
• Static Analysis
• Program Verification
• +۴ مورد دیگر

Işıl Dillig is an Associate Professor in the Department of Computer Science at the University of Texas at Austin, leading the UToPiA research group. She focuses on programming languages, with emphasis on static analysis, verification, and synthesis to enhance software reliability and security. Education: BS, MS, PhD in Computer Science from Stanford University Her research addresses critical challenges in: Program analysis for security and correctness Automated program synthesis for complex tasks Verification of concurrent and database-driven systems Recent publications span neurosymbolic synthesis, database integration, and smart contract optimization. Trends include hybrid AI-formal methods approaches and domain-specific language design. Scientific recognition includes: Sloan Fellowship NSF CAREER award She actively contributes to academic leadership as committee member, program chair, and keynote speaker in top conferences like PLDI, OOPSLA, and POPL.

• Natural Language Processing
• Grapholinguistics
• Digital Typography
• +۴ مورد دیگر

Yannis Haralambous is a full professor at the Data Science Department of IMT Atlantique, Brest, France. He is a member of the DECIDE research group affiliated with the CNRS Lab-STICC laboratory. His career spans academia and entrepreneurship, with a focus on natural language processing, grapholinguistics, and knowledge representation since transitioning from algebraic topology and digital typography research in the 1990s. Research Interests Natural Language Processing with emphasis on explainable AI and speech analysis Grapholinguistics, particularly script reform and writing systems Explainable Representation of Complex Systems using automata and time series Fuzzy Logic applications in recruitment analytics Semantic Web extensions to pragmatic and social representation Teaching Graph theory, logic, knowledge representation, and computational linguistics Curriculum design for the Data Science Master of Science at IMT Atlantique Recent Publications 2024: 550-page Springer textbook on NLP with exercises and educator resources 2023: Frameworks for Pragmatic Web and fuzzy logic in recruitment (SN Computer Science, Future Internet) 2022: Conference papers on resume segmentation, job offer term extraction, and complex system modeling Projects 2024-2026: COGITAMUS project on spontaneous e-learning from open-source data Laboratory collaborations with Lab-STICC and La Mètis company Academic Background 1990 Ph.D. in Algebraic Topology (University of Lille I) 2020 HDR (University of Western Brittany) Professional Timeline 1990-2001: Digital typography R&D and Inalco lectureship 2001-present: IMT Atlantique professor 2010: Full DECIDE team member

• Temporal logic
• Deontic logic
• Timed automata
• +۱ مورد دیگر

Paweł Głuchowski is a researcher at the Department of Computer Engineering within the Faculty of Information and Communication Technology at Wrocław University of Science and Technology. His work focuses on formal verification methods and temporal logic applications in safety-critical systems. Specialization: Temporal logic, Deontic logic, Timed automata, Safety analysis of transportation systems Affiliation: Wrocław University of Science and Technology His research primarily addresses safety analysis of transportation systems through formal verification techniques. Key methodologies include applying temporal logic frameworks like CTL/RTCTL and duration calculus to model complex system behaviors with time dependencies. Recent publications demonstrate his expertise in using tools like NuSMV for airport traffic control verification, fault tree analysis with temporal dependencies, and duration calculus applications. These works span 2007-2016, showing sustained focus on formal methods in safety-critical domains. Contact details: Office located in building C-3, room 313, with phone available at +47 71 320 2740. His email is pawel.gluchowski@pwr.edu.pl.

Jan Friso Grooteمشاهده پروفایل

استاد

• Formal Methods
• Verification Technology
• Software Engineering
• +۱۲ مورد دیگر

Jan Friso Groote is a Full Professor and Chair of the Formal System Analysis group in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). He also holds professorial roles in the EAISI Foundational and EAISI High Tech Systems institutes. Since 2016, he has been working part-time at ASML, contributing his expertise in formal verification to industrial applications. Education: Born in 1965, studied Computer Science at Twente University of Technology (now University of Twente), 1983–1988. PhD in 1991 from the University of Amsterdam with thesis 'Process algebra and structured operational semantics', based on research at CWI (Centrum Wiskunde en Informatica). Jan Friso Groote is a leading researcher in formal methods and software verification. His work focuses on enabling the development of flawless software through rigorous formal analysis. Key research areas include structural operational semantics, model checking, branching bisimulation, protocol verification, and the development of the mCRL2 toolset. His current goal is to integrate formal techniques into complete software system design, improving both development speed and quality. His research has demonstrated that formal methods can reduce development time by a factor of three and increase quality tenfold, with potential for zero-defect software. His recent publications demonstrate sustained contributions in formal verification, including work on mutual exclusion algorithms, industrial control system modeling, probabilistic systems, and efficient bisimulation algorithms. The articles span topics such as tunnel control systems, simulation lower bounds, and formal methods for critical systems, reflecting both theoretical depth and practical application. Scientific Awards: Best Paper Award FACS 2018 FMICS-AVoCS Best Paper Award (2017) Jan Friso Groote has held significant leadership roles in education, including Director of Education for Computer Science (2000–2010) and for multiple bachelor’s and master’s programs. He has advised numerous researchers and supervised a large body of research output (over 320 publications). He leads the Formal System Analysis group and has been involved in projects such as 'Composable Embedded Systems for Healthcare'. His work bridges academia and industry, particularly through collaborations with ASML and Rijkswaterstaat, and he has been a visiting researcher at institutions across Europe and China. He is a key contributor to the mCRL2 toolset, which supports modeling and verification of software behavior with data, time, and probabilities. His research fingerprints highlight strong expertise in model checking, transition systems, software design, and process algebra. He teaches courses such as System Validation, Embedded Software, and Capita Selecta in Formal System Analysis.

Christopher Hampsonمشاهده پروفایل

مدرس ارشد

• Modal and Temporal Logics
• Algorithms and Computational Complexity
• Theoretical Computer Science
• +۴ مورد دیگر

Dr. Christopher Hampson is a Senior Lecturer in Computer Science (Education) at King’s College London's Department of Informatics, part of the Faculty of Natural, Mathematical & Engineering Sciences. He specializes in theoretical computer science, modal logics, and algorithmic complexity. He holds an MSc in Mathematical Logic from the University of Manchester and a PhD from King’s College London on modal logic topics. His research focuses on Modal and Temporal Logics Computational Complexity Formal Verification Counter Machine Theory Computer Science Education Recent work includes studies on non-repudiation in healthcare AI systems (2024), termination analysis of faulty counter machines (2021), and dialogue systems for handling misunderstandings (2022). He collaborates with the Computing Education Research Centre (CERC) to advance pedagogical tools and curricula in computer science. Awards: none explicitly listed. Supervision: no named advisees found. Active in research groups focused on formal methods and education innovation.

Lutz Schröderمشاهده پروفایل

استاد

• Formal Methods
• Logic in Computer Science
• Knowledge Representation
• +۵ مورد دیگر

Lutz Schröder is a Professor and head of the Chair of Computer Science 8 (Theoretical Computer Science) at the Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). He is actively involved in research and leadership within formal methods and logic in computer science. His research interests include Formal Methods , Logic in Computer Science , Knowledge Representation , and Coalgebraic Logic . His work emphasizes theoretical foundations of programming semantics, modal and fixpoint logics, and automated reasoning, often employing category-theoretic and coalgebraic frameworks. His recent publications span top conferences such as LICS, POPL, CSL, and CONCUR, focusing on graded semantics, behavioral metrics, nominal automata, and generic model checking. These works exhibit a strong trend toward unifying logical systems and developing modular, coalgebraic tools for verification. EATCS Best Paper Award at ETAPS 2006 Best Theory Paper at FM 2019 He advises several researchers, including Paul Wild, Jonas Forster, and Daniel Hausmann, many of whom are frequent co-authors. He leads DFG projects such as CoMoC (Coalgebraic Model Checking), SpeQT (Spectra of Behavioural Distances), and is a principal investigator in the DFG Research Training Group 2475 on Cybercrime and Forensic Computing. He has been a PC member or co-chair for major conferences including LICS, IJCAI, FoSSaCS, and STACS, and co-chaired IFIP WG 1.3 from 2016–2022. He is also involved in the development of reasoning tools like COOL and COOL-MC.

• Automata Theory
• Logic in Computer Science
• Infinite-State Systems
• +۷ مورد دیگر

Wojciech Czerwiński is an Associate Professor at the Institute of Informatics, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw. His research lies at the intersection of automata theory, logic, and computational complexity, with a focus on infinite-state systems such as vector addition systems (VASS) and Petri nets. His research interests include: Automata and logic Infinite-state systems Reachability and separability problems Complexity of computational models Formal verification and concurrency theory His recent work has significantly advanced the understanding of the complexity of reachability in VASS, proving it to be Ackermann-complete. This line of research has been published in top venues including FOCS, STOC, LICS, and CONCUR, where several papers received Best Paper Awards. His publications reflect a strong trend toward resolving long-standing open problems in decidability, complexity, and logical definability in infinite-state models. Scientific awards include: Best Paper Award, CONCUR 2022 Best Paper Award, STOC 2019 He leads an ERC-funded project and is actively recruiting PhD students and post-docs. He organizes the Friday Afternoon Seminar and co-organized the Infinite Automata Workshop (2024). He has also contributed to public understanding of science as an editor and author for the journal Delta from 2013 to 2022. His work involves collaboration with leading researchers such as Sławomir Lasota, Jérôme Leroux, Georg Zetzsche, and others. He has made foundational contributions to problems like bisimilarity, language equivalence, and regular separability in various automata models.

• Verification
• Probabilistic Models
• Infinite-State Systems
• +۲ مورد دیگر

Mahsa Shirmohammadi is a CNRS researcher at Institut de Recherche en Informatique Fondamentale (IRIF) , Université de Paris. Her research focuses on verification, probabilistic models, infinite-state systems, automata theory, and numerical computation. Education : PhD from LSV, ENS de Cachan (France) and ULB (Belgium). Previous Affiliation : Postdoctoral researcher at University of Oxford (UK). Her work addresses stochastic games , timed automata , matrix groups , and algebraic computation . Recent publications analyze strategy complexity, synchronization in decision processes, and parametric algebraic problems. Key collaborators include Stefan Kiefer, Richard Mayr, James Worrell, and Patrick Totzke. Her research has been published in venues like ACM SIGLOG News, ICALP, LICS, and ISSAC. Contact: mahsa@irif.fr , +33 (0)1 57 27 92 29, Office 4017 (Sophie Germain building, Paris).

• Logic in computer science
• linear dynamical systems
• automated verification
• +۳ مورد دیگر

James Worrell is a Professor of Computer Science at the University of Oxford , with a focus on logic in computer science , linear dynamical systems , and automated verification . He is also a Fellow of Green Templeton College. His research spans theoretical computer science and formal methods , including work on metric temporal logic , probabilistic semantics , and category theory . His publications address decision problems , verification of linear dynamical systems , and automata theory . James has received the EPSRC Established-Career Fellowship for his work in linear dynamical systems verification . His recent papers include polynomial invariants , polyhedral escape problems , and skolem problem solutions . He has advised students such as Mehran Hosseini , Pascale Gourdeau , and Ventsislav Chonev , and teaches courses like Computational Learning Theory and Logic and Proof . His work appears in venues like ICALP , LICS , and SODA .

• Algorithms
• Game Theory
• Automata
• +۵ مورد دیگر

Marcin Jurdzinski is a Professor at the Department of Computer Science, University of Warwick, with a focus on algorithms, games, automata, and logic. His career spans institutions like the University of Aarhus, University of Paris 7, and UC Berkeley. Research interests include Parity games Stochastic games Timed automata Formal verification Game theory . Recent articles highlight work on parity games, stochastic systems, and timed automata, published in venues like SIAM Journal on Computing, LICS, and CAV. Keywords span Computer Science , Game Theory , and Formal Methods . PhD students mentored include Thejaswini K. S., Michail Fasoulakis, and Ashutosh Trivedi. Funded projects such as Solving Parity Games in Theory and Practice (2017-2021) reflect his research priorities.

Ramyaaمشاهده پروفایل

استادیار

• Theory of Computation
• Computational Complexity
• Logic
• +۷ مورد دیگر

Ramyaa is an Assistant Professor in the Department of Computer Science & Engineering at New Mexico Tech. Her research focuses on the intersection of computation, logic, and emerging models of computation, including implicit complexity theory and biologically inspired neural networks. She also explores machine learning applications in real-world problems and interpretable AI. Education: Ph.D. in Computer Science, with a focus on theoretical foundations. Research Interests: Implicit complexity (relating logical complexity to computational resource constraints), formalization of computational models (e.g., biological neural networks), machine learning (including neural network training, adversarial robustness, and program synthesis), and applications in healthcare, security, and education. Her work emphasizes adaptable complexity measures for novel computational frameworks. Recent Trends in Publications: Recent work includes reinforcement learning for astrophysical data workflows, biologically inspired sleep algorithms for neural networks, and machine learning applications in nutritional epidemiology. She also explores educational technology, such as games for teaching logic and interactive programming tutorials. Grants & Advising: Advises research in machine learning, theoretical computer science, and interdisciplinary applications. Active in grant-seeking for projects at the intersection of theory and applications. No listed students, but collaborates widely with researchers globally. Affiliations: Fellow at the Simons Institute for the Theory of Computing (Berkeley), organizer of conferences like ICALT and CSR, and contributor to initiatives like WiCS at NMT. Teaches courses in formal languages, automata theory, and reinforcement learning.

Henrik Björklundمشاهده پروفایل

دانشیار

• Natural Language Processing
• Formal Languages
• Machine Learning
• +۳ مورد دیگر

Henrik Björklund is an Associate Professor at the Department of Computer Science, Umeå University. His research focuses on natural language processing , formal languages , and mitigating social bias in large language models . Primary affiliation: Umeå University Department: Computing Science Role: Faculty member Research interests include: Detecting and mitigating gender bias in NLP systems like ChatGPT Foundational studies in formal languages and automata theory Developing language technology for Swedish, particularly nonbinary pronouns like 'hen' Publication trends show: Recent work (2023-2024) on intersectional bias analysis in LLMs 2017-2023 studies on hyperedge replacement grammars and DAG language transduction 2013-2017 contributions to XPath evaluation and tree pattern queries Contact : henrik.bjorklund@umu.se

• Formal Language Theory
• Machine Learning
• Semantic Parsing
• +۶ مورد دیگر

Johanna Björklund is an Associate Professor at the Department of Computing Science , Umeå University, specializing in Formal Language Theory , Machine Learning , and Semantic Parsing of Multimodal Data . Her research focuses on translating complex media (e.g., videos with audio/subtitles) into graph-based semantic representations for algorithmic processing. Current projects include WARA Media & Language (2024–2026) and AI-Driven Contextual Communication (2021–2023). Key research areas: tree automata , graph transduction , contextual advertising , and computational linguistics . Her recent publications highlight advances in tree-to-graph transduction , multimodal semantic analysis , and privacy-preserving advertising . She has secured significant grants, including SEK 12 million (2021) and 4 million SEK (2020), for AI and deep learning initiatives. Grants: SEK 12 million (2021) for AI projects. 4 million SEK (2020) for Deep Learning methods. Scientific Awards: Lead researcher in multiple EU-funded projects. Recognized for contributions to formal languages and machine learning . She collaborates with teams in semantic analysis , tree automata , and multimodal AI , emphasizing practical applications like visual analytics and advertising systems .

Petter Ericsonمشاهده پروفایل

پژوهشگر

• Responsible AI
• Graph Theory
• Formal Grammars
• +۴ مورد دیگر

Petter Ericson is a Researcher at the Department of Computer Science , Umeå University , specializing in Responsible AI . His work bridges graph theory , formal grammars , and ethics , with interdisciplinary interests in music and sociotechnical systems . Affiliated with the Responsible AI Research Group , he explores the alignment of AI with human values. Ericson’s research spans formal computational models , including hyperedge replacement grammars and order-preserving DAGs , alongside AI ethics and fairness frameworks . His publications address sociotechnical limits in AI safety, artistic shifts through AI, and graph language learnability. He has contributed to interdisciplinary projects like Concordia , a musical XR instrument for planetary data sonification, and Musereduce , a hierarchical music analysis framework. Ericson applies computational methods to Bayesian music theory and jazz harmony datasets.