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Jürgen GieslView profile

Professor

• Program Verification
• Automated Deduction
• Termination Analysis
• +12 more

Jürgen Giesl is a Professor at the Teaching and Research Area Computer Science 2 within the Department of Computer Science at RWTH Aachen University , Germany. He leads research in programming languages, formal verification, automated deduction, and term rewriting systems. Research Interests: Automated Termination and Complexity Analysis of Programs Dependency Pairs and Term Rewriting Systems Verification of Probabilistic and Integer Programs Static Analysis and Symbolic Execution Model Checking and Constrained Horn Clauses Development of Automated Tools (AProVE, LoAT) His recent research, reflected in the latest publications, focuses on termination and complexity analysis for probabilistic programs, polynomial loops, and integer programs, using advanced techniques such as dependency pairs, loop acceleration, and semiring semantics. He also contributes to SMT solving and transitive relation learning for infinite-state model checking. Scientific Awards: Best Tool Paper Award at iFM 2017 Silver Medal (Second Best Paper) at SEFM '16 Best Paper Honourable Mention at IJCAR 2024 Best Student Paper Honourable Mention at IJCAR 2024 Advising and Grants: Giesl has supervised numerous PhD and Master’s students, including prominent researchers such as Fabian Frohn, Jens Hensel, Nils Lommen, and Marcel Hark. He leads a large research group focused on automated verification and has contributed extensively to international verification competitions. His work is supported by ongoing research grants and collaborations with leading institutions in formal methods. Labs and Teams: He leads the Programming Languages and Verification research group at RWTH Aachen, which develops and maintains the AProVE and LoAT tools. These tools are central to automated termination and complexity analysis and are regularly submitted to international competitions such as TERMCOMP and VBS.

Ganesh Lalitha GopalakrishnanView profile

Professor

• Computer Science
• Formal Methods
• High-Performance Computing (HPC)
• +6 more

Ganesh Gopalakrishnan is a Professor of Computer Science at the University of Utah's School of Computing. His research focuses on software correctness, floating-point arithmetic, and formal methods for HPC applications. He leads the ComPort DOE project and NSF REU Site on Trust and Reproducibility. He has advised 26 PhD students and holds seven active NSF grants and a DOE award. Education: B.Sc.(EE), National Institute of Technology Calicut (1978) M.Tech (EE), Indian Institute of Technology Kanpur (1980) PhD in Computer Science, Stony Brook University (1986) Research Interests: Formal methods, HPC correctness, GPU debugging, floating-point error analysis, neural network compression, and reproducible scientific computing. His tools include FPBoxer, HiRace, and FPDetect. Awards & Recognition: ACM Distinguished Scientist IEEE Senior Member University of Utah Beacon of Excellence Award (2012) NSF and DOE funding leadership Labs & Projects: Principal Investigator of the ComPort project (DOE) and NSF REU Site. Co-developed the Jove system for automata education and the Flit floating-point testing framework.

Richelle Allen-KingView profile

Professor

• Contaminant Transport in Groundwater
• Hydrogeochemistry
• Organic Contaminants
• +5 more

Richelle Allen-King serves as Professor and Director of Graduate Studies in the Department of Earth Sciences within the College of Arts and Sciences at the University at Buffalo. Her academic career centers on hydrogeochemistry and environmental geochemistry, with specialized expertise in contaminant transport processes in groundwater systems. Her educational background includes: PhD in Earth Sciences (Hydrogeology) from the University of Waterloo (1991) Dr. Allen-King's research focuses on understanding the fate and transport of contaminants in groundwater , particularly organic pollutants like chlorinated solvents and nutrients. She integrates field measurements, laboratory experiments, and numerical modeling to investigate critical processes including sorption, diffusion, and biotic/abiotic degradation in heterogeneous aquifers. Her work addresses fundamental limitations in predicting natural attenuation and designing effective remediation strategies for contaminated sites, with significant contributions to understanding nonlinear sorption in low-organic-carbon sediments and aquifer heterogeneity effects. Analysis of her publication record reveals three dominant research trajectories: (1) Advanced characterization of chlorinated solvent behavior in sedimentary rock aquifers , particularly diffusion and degradation processes in low-permeability media; (2) Investigation of nutrient transport dynamics in watersheds with applications to Lake Erie eutrophication; and (3) Development of educational frameworks for early-career geoscientists. Her recent work increasingly incorporates high-fidelity modeling of heterogeneous systems and field validation at research sites like the Borden Aquifer. Her research is supported by major external funding including: SERDP Project ER-2533: Developing field methods for quantifying chlorinated solvent diffusion and degradation in low-permeability media NSF IGERT ERIE grant: Fostering interdisciplinary training in ecosystem restoration Dr. Allen-King has mentored 14 graduate students to completion, with alumni now working as hydrogeologists at firms including Geosyntec Consultants, Leggette Brashears & Graham, and Intera Inc. She teaches advanced courses in environmental geochemistry and supervises thesis research focused on contaminant hydrology. Her laboratory investigations frequently involve collaborative field work at the Borden Aquifer research site in Ontario, Canada, where she examines lithofacies controls on contaminant transport properties.

Pierre-Yves LajoieView profile

Assistant Professor

• Robotics
• Computer Vision
• Artificial Intelligence
• +5 more

Pierre-Yves Lajoie is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, a leading engineering school affiliated with Université de Montréal. His research focuses on robotics and artificial intelligence, with specialization in robotic perception for single and multi-agent systems. He has held research positions at prestigious institutions including the Massachusetts Institute of Technology (2019), Samsung AI Center (2023), and University of Oxford (2024). Education: Ph.D. in Computer Engineering, Polytechnique Montréal Dr. Lajoie's research interests span across robotics, computer vision, and distributed systems. He specializes in developing algorithms for robotic perception in challenging environments, with applications in aerial, underground, indoor, and space robotics. His work focuses on enabling robots to understand their surroundings through visual and sensor data, particularly in collaborative multi-robot scenarios where communication may be limited or unreliable. His primary research center of excellence is the Industry of the Future and Digital Society, with secondary centers in Modeling and Artificial Intelligence and New Frontiers in Information and Communication Technologies. His publication record demonstrates a strong focus on collaborative SLAM (Simultaneous Localization and Mapping) systems, with recent work addressing challenges in planetary exploration, swarm robotics, and pedestrian positioning. His research combines computer vision, machine learning, and distributed systems to create robust solutions for real-world robotic applications, particularly in environments with communication constraints. Scientific Awards: Vanier Canada Scholarship Best Paper Award at IEEE ICC 2024 Dr. Lajoie is actively recruiting graduate students for PhD and Master's programs, with openings for Fall 2025 and Spring 2026. He encourages students to apply for various scholarship opportunities including NSERC, FRQ, and IVADO scholarships at multiple academic levels. His research is supported by collaborations with academic and industrial partners, focusing on applications in space robotics, automated manufacturing, and service robotics. He has supervised research projects in areas such as search and rescue with sparsely connected swarms and distributed risk-aware exploration systems.

Hamed NematiView profile

Assistant Professor

• Security of systems software
• Formal methods and program logics
• Interactive theorem proving
• +2 more

Hamed Nemati is an Assistant Professor at the Division of Network and Systems Engineering under the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology in Stockholm, Sweden. He was previously a Visiting Assistant Professor at Stanford University and a Research Group Leader at the Helmholtz Center for Information Security (CISPA) , where he also worked as a PostDoc and Research Fellow. Education : PhD in Computer Science from KTH Royal Institute of Technology Research Interests : Security of systems software, formal methods and program logics, interactive theorem proving, machine code analysis, applied machine learning Current Projects : Systematic verification of multi-language security protocols, hardware-software co-design for Spectre mitigation, capability-based access control models Scientific Awards : WASP (Wallenberg AI, Autonomous Systems and Software Program) faculty member Teaching Activities : Formal Methods in Security (Fall 2020-2023) at CISPA/Saarland University Digital Forensics and Incident Response (EP2780) (Fall 2024) at KTH

Sunoo ParkView profile

Assistant Professor

• Security
• Privacy
• Technology Law
• +6 more

Sunoo Park is an Assistant Professor in Computer Science at NYU Courant Institute of Mathematical Sciences, with a secondary affiliation at NYU School of Law. He directs the DeTaIL Lab , focusing on security, privacy, and transparency in digital technologies. His educational background includes a J.D. from Harvard Law School, a Ph.D. in Computer Science from MIT, and a B.A. from the University of Cambridge. He is a licensed attorney in New York. His research bridges computer science and technology law , with core interests in cryptography, election security, AI ethics, blockchain, and digital policy. Recent work emphasizes legal risks in security research, verifiable voting systems, and adversarial robustness in AI. Park's publications (2017–2025) reveal strong trends in cryptographic applications for societal challenges , including election auditing, deniable encryption, and blockchain vulnerabilities. He consistently addresses tensions between technological capabilities and legal/policy frameworks. Teaching includes graduate courses on Digital Technology Law and AI Ethics , alongside clinical work in NYU's Technology Law & Policy Clinic. Service roles include program committees for IEEE Security & Privacy and NeurIPS (Ethics Committee).

Robert Y. LewisView profile

Lecturer

• Formal Methods
• Logic
• Theoretical Computer Science
• +3 more

Robert Y. Lewis is a Lecturer in the Department of Computer Science at Brown University, specializing in formal methods, logic, and interactive theorem proving. His work bridges computer science and mathematics, focusing on the verification of mathematical proofs and program correctness. Education: PhD in Pure and Applied Logic (2018), Carnegie Mellon University MS in Pure and Applied Logic (2015), Carnegie Mellon University BA in Mathematics (2010), Rice University Research Interests: Lewis’s research spans formal verification, logic, type theory, and automated reasoning. He explores the application of logical tools like the Lean proof assistant in mathematics education and software verification. Teaching: At Brown, he teaches courses such as Introduction to Discrete Structures and Probability and Formal Proof and Verification . Prior to Brown, he taught Logic and Modeling at Vrije Universiteit Amsterdam and served as a teaching assistant at Carnegie Mellon University. Publications: His recent work includes advancements in formalizing mathematical structures (e.g., Witt vectors, Cap Set Problem), integrating proof assistants with computational tools (Lean-Mathematica interface), and developing educational resources for logic and formal methods. Contact: Email: robert_lewis@brown.edu Office: Center for Information Technology 203, Brown University

• Mathematical Logic
• Computer Science
• Proof Theory
• +5 more

Kazushige Terui is an Associate Professor at the Research Institute for Mathematical Sciences (RIMS), Kyoto University. His research focuses on mathematical logic and its applications to computer science, particularly proof theory, computational complexity, and nonclassical logics. He investigates proof normalization complexity, algebraic reformulations of proof-theoretic techniques, and logical foundations of computation. Terui maintains an active research group at RIMS and teaches courses including Mathematical Logic and Computer Science Fundamentals. Research Interests: Terui's work spans: Proof-theoretic aspects of nonclassical logics (linear logic, substructural logics) Computational complexity of proof normalization in lambda calculus Algebraic reformulation of logical techniques (cut-elimination, interpolation) Denotational semantics approaches to complexity characterization Effective proof discovery methods based on programming language theory Publications: His recent articles primarily explore proof theory, computational complexity, and logical foundations, with frequent focus on lambda calculus, linear logic, and type systems. Works frequently bridge theoretical computer science and mathematical logic. Education & Outreach: Authored the book Can Computers Become Mathematicians? (2015) for general audiences and maintains extensive lecture materials on mathematical logic and computer science foundations.

• Reinforcement Learning
• Neural Network
• Deep Reinforcement Learning
• +5 more

Abhinav Verma is an Assistant Professor in Computer Science and Engineering, focusing on reinforcement learning, neural networks, and formal verification of control systems. His research bridges machine learning, program synthesis, and theoretical computer science to ensure interpretable and verifiable AI. Research Interests : Reinforcement learning, neurosymbolic AI, policy synthesis, formal guarantees in control systems. Key Contributions : Developed frameworks combining neural networks with formal methods for verifiable sequential decision-making, contributed to explainable AI through programmatic policy learning. Article Trends : Recent work emphasizes temporal logic constraints, counterfactual experience replay, and reduced-variance reinforcement learning. His publications highlight compositional approaches, differentiable programs, and neurosymbolic integration. Collaborations : Collaborates with institutions and researchers in computer science, with a focus on stochastic systems and interpretable machine learning.

• Artificial Intelligence
• Medical Informatics
• Software Engineering
• +4 more

Dr. rer. nat. Joscha Grüger is a researcher at the Experience-based Learning Systems department of the University of Trier . His work bridges artificial intelligence, medical informatics, and software engineering, focusing on AI-driven solutions for healthcare and data-intensive applications. Current research projects include: KI-AIM : AI-based anonymization in medicine KIAFlex : Interactive AI assistance for predictive and flexible control in discharge management DaTreFo : Encrypted data stewardship for medical research Pre-OnkoCase : Case-oriented decision support for skin cancer treatment His publications highlight expertise in probabilistic programming, IoT-enhanced event logs, and clinical decision support systems. Collaborations span international conferences like Petri Nets 2025, ICCBR, and RCIS. Contact: Joscha.Grueger@dfki.de .

Gérard BerryView profile

Professor

• Computer Science
• Lambda Calculus
• Functional Programming
• +5 more

Gérard Berry (born December 25, 1948) is a distinguished French computer scientist currently serving as Professor at the Collège de France, holding the permanent chair Algorithmes, machines et langages (Algorithms, Machines, and Languages) since 2012. He previously held the Informatique et sciences numériques chair (2009-2010) and the Technological Innovation Liliane Bettencourt chair (2007-2008) at the same institution. Before joining Collège de France full-time, he served as Director of Research at INRIA Sophia Antipolis (2009-2012) and at École des Mines de Paris (1977-2001). His research spans over 30 years in three main fields: lambda calculus and functional programming, parallel and real-time programming languages, and design automation for synchronous digital circuits. He is particularly renowned for developing the Esterel programming language. His work bridges theoretical computer science with practical industrial applications. Berry's research has evolved to include current work in Hop and HipHop for Web programming, formal verification of compilers, and languages for computer music. His publications demonstrate consistent contributions to programming language theory, formal methods, and their applications in hardware and software systems. Gold Medal of CNRS (2014) Chevalier de l'Ordre de la Légion d'Honneur (2012) Member of French Academy of Sciences (2002) Member of Academia Europaea (1993) Monpetit Prize of Académie des sciences (1990) Berry has advised 17 PhD students and reviewed numerous theses. His industrial experience includes serving as Chief Scientist Officer of Esterel Technologies (2000-2009), where he directed the implementation of the Esterel v7 compiler. He has also held significant leadership roles including President of the Scientific Council of IRCAM and membership on the Scientific Council of the National Education. His teaching at Collège de France has covered topics ranging from the foundations of computation to the societal impact of digital technology, with courses including The Informatics of Time and Events and Proving Programs: Why? When? How? His laboratory work has focused on developing practical applications of theoretical computer science concepts.

• Marketing Management
• Consumer Behavior
• Service Exclusion
• +12 more

Rajesh Rajaguru is a Senior Lecturer in Marketing at the Tasmanian School of Business and Economics (TSBE), University of Tasmania. He is actively engaged in research, teaching, and industry collaboration, with a focus on marketing management, consumer behavior, sustainability, and digital technologies. His work bridges academia and practice, particularly in service ecosystems, SME resilience, and ethical consumption. Research Interests: Marketing Management and Strategy Consumer Behavior and Decision-Making Sustainability and Responsible Consumption Digital Marketing and eWOM Blockchain and AI in Consumer Trust Service Exclusion and Inclusive Service Design SME Resilience and Market Shaping His recent publications reflect a strong trend toward interdisciplinary research, integrating insights from psychology, information systems, and environmental science. A significant portion of his work explores how technology and sustainability concerns influence consumer trust and purchasing behavior, particularly in food, hospitality, and retail sectors. He also investigates pedagogical innovations in higher education and supply chain dynamics in emerging markets. Scientific Awards and Recognition: Certified Practicing Marketer, Australian Marketing Institute (since 2019) Supervision and Grants: Rajesh Rajaguru has successfully supervised multiple PhD students to completion and is currently supervising a doctoral candidate on SME resilience. He has secured both internal and external funding, including grants from the University of Tasmania, Australian Institute of Business, and the Korean Government. He is also a key participant in the Marine Bioproducts Cooperative Research Centre, a major $59 million initiative funded by the Australian Government and industry partners. Labs and Research Teams: He collaborates within interdisciplinary research teams focused on service ecosystems, sustainable business models, and digital transformation. His work is aligned with the UN Sustainable Development Goals, particularly Responsible Consumption and Production , Industry, Innovation and Infrastructure , and Climate Action .

Yonathan ArbelView profile

Professor

• Artificial Intelligence
• Commercial Law
• Consumer Law
• +3 more

Yonathan Arbel serves as the William Alfred Rose Professor of Law and Director of the AI Legal Studies Initiative at the University of Alabama School of Law, where he has been a faculty member since 2017. His interdisciplinary scholarship bridges artificial intelligence, commercial law, and economic analysis, establishing him as a leading voice in law and technology. His educational background includes: Doctoral degree in law and economics from Harvard Law School (Olin and Byse fellow) JSM degree from Stanford Law School Joint degree in Law and Humanities (summa cum laude) from Hebrew University in Jerusalem Professor Arbel's research integrates doctrinal, economic, and socio-legal methodologies to address contemporary challenges in contract interpretation, defamation, and AI regulation. His work demonstrates exceptional innovation in applying machine learning to legal text analysis and developing market-based solutions for information integrity. He has pioneered empirical approaches to studying contract readability and nano-contracts, while his status theory of defamation law redefines traditional frameworks through sociological lenses. His publication trajectory reveals a strategic pivot toward AI-law intersections since 2022, with 10 of 15 most recent articles focusing on artificial intelligence applications, regulation, and safety. This builds upon his foundational work in commercial law and defamation, creating a cohesive research program examining how technological change reshapes legal doctrines and enforcement mechanisms. His scientific recognition includes: Olin and Byse fellowships at Harvard Law School Winner of the American College of Consumer Financial Services Writing Competition (2021) Four teaching distinction awards Multiple selections for prestigious workshops including Stanford/Yale/Harvard Junior Faculty Forum As Director of the AI Legal Studies Initiative, Professor Arbel leads interdisciplinary collaborations exploring regulatory frameworks for emerging technologies. His publicly available teaching tools—including the Hypo Name Generator and Law Review Article Template—demonstrate commitment to pedagogical innovation. Prior consultancy experience (2010-2017) informs his practical approach to contract design and regulatory implementation. The AI Legal Studies Initiative serves as his primary research hub, fostering cross-disciplinary dialogue between legal scholars, computer scientists, and policymakers to address pressing challenges in algorithmic accountability and AI governance.

• Answer Set Programming
• Artificial Intelligence
• Logic Programming
• +4 more

Torsten Schaub is a Professor at the Institute of Computer Science , University of Potsdam. His research focuses on Answer Set Programming (ASP) , constraint solving, temporal reasoning, and combinatorial optimization, with applications in multi-agent pathfinding, product configuration, and course timetabling. Key contributions include ASP-based tools for industrial-scale optimization problems, metric temporal logic implementations, and frameworks for dynamic equilibrium logic. Recent work explores efficient design space exploration, stream reasoning, and multi-shot ASP solving for complex domains. His publications emphasize hybrid ASP systems , integrating constraints and temporal logic, with co-authors across Europe and Asia. He actively develops tools like clingo and Clingraph for practical ASP applications in logistics, bioinformatics, and robotics. The articles reveal a trend toward multi-agent systems (e.g., pathfinding algorithms) and temporal extensions in ASP, combining formal logic with real-world problem-solving. Sub-fields include constraint satisfaction, logical abduction, and declarative modeling for optimization tasks.

Brigitte PientkaView profile

Professor

• Type theory
• Programming languages
• Logical frameworks
• +7 more

Brigitte Pientka is a Full Professor in the School of Computer Science at McGill University, where she leads the Computation and Logic group. She received her PhD from Carnegie Mellon University in 2003, and previously studied at the University of Edinburgh and Technical University of Darmstadt. Her educational background includes: PhD from Carnegie Mellon University (2003) Studies at the University of Edinburgh Studies at Technical University of Darmstadt Dr. Pientka's research focuses on developing theoretical and practical foundations for building and reasoning about reliable, safe software systems. She combines theoretical research on logical foundations of computer science in programming languages and verification with system building. Her work spans logics (classical and non-classical), type theory, theorem proving, logic and functional programming, and logical frameworks. She has made significant contributions to the field of contextual types and mechanized metatheory. Her recent publications demonstrate a strong trend toward modal type theory, contextual types, and session types, with applications to functional programming, verification, and meta-programming. She has made significant contributions to the Beluga system, which explores how to combine functional programming with dependently-typed, higher-order data specified in the logical framework LF. Her work often bridges theoretical foundations with practical implementations for mechanized reasoning. Dr. Pientka has received several notable awards: Humboldt Fellowship Test of Time Award @ PPDP'18 for 'Programming with proofs and explicit contexts' Best student paper award at ICLP'03 She is actively involved in mentoring and academic service, having served as PC Chair for ICFP'24, CPP'23 and CPP'24, and as General Chair for POPL'20. She is an Executive Editor of Logical Methods in Computer Science and serves on the editorial boards of the Journal of Functional Programming and ACM Transactions of Computational Logic. She leads the Computation and Logic group at McGill University, which focuses on developing theoretical and practical foundations for reliable software systems through research in logical frameworks, type theory, and programming language design.