Benjamin Gregoire is a Researcher at INRIA Sophia Antipolis , affiliated with the Marelle Team . His work focuses on compilers , formal verification , cryptography , proof assistants , and type theory . Education : PhD in Computer Science, Université Paris 7 (2003) Research Interests : Dr. Gregoire specializes in formal verification of cryptographic systems, compiler design for security-critical applications, type-based termination, and proof assistants like Coq. His projects include the INRIA-Microsoft Research Joint Lab , ANR Scalp (Security of Cryptographic Algorithms with Probabilities), and ANR DeCert (Certified Decision Procedures). He led the Mobius project (IP FET) and contributed to Java security validation via the JACK tool . Scientific Awards : He received the Best Paper Award at CRYPTO 2011 for 'Computer-Aided Security Proofs for the Working Cryptographer.' Advising & Collaborations : Dr. Gregoire has advised PhD students Michael Armand , Julien Charles , Sylvain Heraud , and Jorge-Luis Sacchini , with former advisee Cesar Kunz . He collaborates with teams including Marelle and INRIA-Microsoft Research .
Prof. Dr. Mario Fritz is a leading academic at the CISPA Helmholtz Center for Information Security and Saarland University , with a focus on Trustworthy Information Processing . His work sits at the intersection of AI, Machine Learning, Security, and Privacy, addressing challenges in foundation models, health data, and adversarial robustness. Key Projects : ELLIOT (Multi-Modal Foundation Models), ELSA (Secure AI), PriSyn (Synthetic Health Data), AIgency (Generative AI in Cybersecurity), HMSP (Medical Security) Research Themes : AI/ML security, privacy-preserving techniques, causal modeling, healthcare applications, and ethical AI Recent Publications : Focus on LLM sampling, causal inference, model stealing, and privacy-aware document analysis Collaborations : European Laboratory for Learning and Intelligent Systems (ELLIS), BMBF-funded initiatives, GHGA (Human Genome Archive) Academic Leadership : As a Professor , he coordinates large-scale EU projects and mentors emerging researchers in AI ethics and security.
Christine Rizkallah is a Senior Lecturer in the School of Computing and Information Systems at the University of Melbourne, Australia. She joined the university in December 2021 after serving as a Lecturer at the University of New South Wales (UNSW) from April 2018 to December 2021. Her research focuses on interactive theorem proving, formal verification, programming languages, and systems, with an emphasis on building practical tools for high-assurance software development. She leads a research group working on the Cogent and Dargent languages, aiming to reduce the burden of formal verification in systems programming. Education: PhD in Computer Science, Universität des Saarlandes and Max-Planck-Institut für Informatik, Germany (2015), thesis: Verification of Program Computations , supervised by Prof. Dr. Kurt Mehlhorn. MSc in Computer Science, Universität des Saarlandes, Germany (2009), thesis: Proof Representations for Higher Order Logic , supervised by Prof. Dr. Gert Smolka and Dr. Chad E. Brown. BSc in Computer Science, German University in Cairo, Egypt (2007), thesis: X2-Planner: A Hierarchical Task Network Planner for Real Time Gaming Applications , supervised by Prof. Dr. Slim Abdennadher and Dr. Thorsten Maier. Her research interests lie at the intersection of programming languages and formal methods. She develops domain-specific languages with strong type systems and verified compilers to enable trustworthy software systems. Her work spans algorithms, logic, security, and social choice theory, reflecting a strong interdisciplinary approach. She has published extensively in top venues such as POPL, ICFP, ASPLOS, JAR, and PACMPL, with a focus on certifying compilation, refinement verification, and mechanized reasoning. Her recent publications reveal a consistent focus on formal verification of systems software, particularly through the Cogent language and its ecosystem. Key themes include verified data layout refinement (Dargent), property-based testing, termination analysis, cost modeling, and integration with foreign functions. Her work combines theoretical rigor with practical implementation, often involving mechanized proofs in Isabelle/HOL and Coq. Scientific Awards and Recognition: Distinguished Artefact Award at SLE'22 (awarded to Zilin Chen for work under her supervision). First Prize, SPLASH'22 Student Research Competition (undergraduate), won by Raphael Douglas Giles. Second Prize, ACM-wide Student Research Competition (undergraduate, 2023), won by Raphael Douglas Giles. She has supervised numerous PhD, Masters, and Honours students, many of whom have continued in academia or industry research roles. She has received research funding through institutional support and collaborative grants, though specific grants are not detailed in the provided text. She is actively involved in the programming languages community, serving on program committees for POPL, ICFP, CPP, PLDI, and others, and holding leadership roles such as Program Chair for FUNARCH'25 and Diversity and Inclusion Co-Chair for PLDI'25. She teaches core courses including Declarative Programming and Models of Computation at the University of Melbourne. She leads a vibrant research team and collaborates widely across institutions including UNSW, University of Pennsylvania, and international partners. Her lab focuses on building verified systems using functional programming and formal methods, with strong ties to the DeepSpec project and the Isabelle/HOL community.
V. Arvind is a Professor in the Theoretical Computer Science faculty at the Institute of Mathematical Sciences (IMSc) , Chennai. His research is centered on computational complexity theory, with a focus on structural complexity, randomized and algebraic computation, and quantum information and computation. He explores the deep connections between theoretical computer science and mathematics. Institution: Institute of Mathematical Sciences (IMSc), Chennai School: Theoretical Computer Science Academic Rank: Professor Arvind's research interests include computational complexity, structural complexity theory, algebraic computation, derandomization, and quantum computing. He is particularly interested in the interplay between mathematical structures and computation. His work often bridges theoretical computer science with algebra, combinatorics, and logic. His recent publications, primarily expository articles in the EATCS Bulletin’s Computational Complexity Column, cover a wide range of topics such as robust oracle machines, the Alon-Roichman theorem, noncommutative arithmetic circuits, graph isomorphism, and quantum computation. These works reflect trends in foundational complexity theory, algebraic methods in computation, and the exploration of quantum models. The articles emphasize structural insights, lower bounds, and connections to mathematical disciplines. Professional Service and Editorial Roles: Associate Editor, ACM Transactions on Computation Theory Editor, EATCS Computational Complexity Column (since June 2011) Editorial Board Member, International Journal of Computer Mathematics (2009–2013) Co-organizer, ICM Satellite Conference on Algebraic and Probabilistic Aspects of Combinatorics and Computing Program Committee Member for WALCOM 2014, STACS 2012, COCOON 2009, FSTTCS (multiple years, including chair roles), CCC 2006, INDOCRYPT (2002, 2005), and others Teaching: Arvind has taught advanced courses including Computational Complexity, Algorithms, Algebra and Computation, and Discrete Mathematics, often based on foundational texts and notes from leading experts. Lecture notes from his courses have been compiled by students and collaborators. Collaborations: He has an extensive list of co-authors, including prominent researchers such as Manindra Agrawal, Eric Allender, Johannes Köbler, Meena Mahajan, Jacobo Torán, and Ramprasad Saptharishi, indicating strong collaborative research networks in complexity theory and algorithms.
Benjamin Pierce is the Henry Salvatori Professor in the Department of Computer and Information Science at the University of Pennsylvania. His research spans programming languages, formal verification, and sustainable computing, with a focus on practical applications in software reliability and security. He leads initiatives like Carbon Connect (NSF Expedition in Sustainable Computing) and serves on climate-focused committees such as Penn's Faculty Senate Select Committee on the Climate Emergency. Research Interests Pierce's work integrates theoretical and applied computer science, emphasizing: Programming Languages : Type systems, language-based security, and compiler verification Formal Methods : Computer-assisted verification, proof automation, and property-based testing Sustainability : Reducing computing's environmental impact through algorithmic efficiency and policy Recent Publications His 2023-2025 publications demonstrate a strong focus on enhancing software testing (e.g., Tyche for property-based testing), advancing formal verification tools (e.g., Coq deautomation), and pioneering sustainable computing frameworks. Climate-related research is a growing theme. Awards and Honors 2024: Distinguished Paper Award (ICSE) 2020: Best Paper Award (POPL) 2015: Most Influential Paper Award (ACM SIGPLAN) 2013: LICS Test of Time Award 2012: ACM Fellow Advising and Grants He advises 8 PhD students on topics ranging from type systems to verified compilation. Notable projects include: NSF-funded Carbon Connect expedition SHF grant for usable property-based testing Development of verification tools (VERSE, Unison) Professional Activities Serves on editorial boards for Journal of Functional Programming and Logical Methods in Computer Science , and organizes major conferences (PLDI, POPL, OOPSLA). Advocates for low-carbon virtual conferences.
Laure Gonnord is a Full Professor in Computer Science at Grenoble INP , affiliated with the Esisar Engineer School in Valence, France, since September 2021. She is a member of the CTSYS research team at the LCIS laboratory and an external member of the CASH team at the University of Lyon / CNRS / LIP / Inria. Her research focuses on compilation , static analysis , and applications to safety , security in high-performance and embedded systems . Fields of Interest : Compiler Design Static Analysis for Safety & Security Abstract Interpretation Embedded Systems High-Performance Programming Hardware Security Engineering Research Trends (from recent publications): Her work explores modular verification through monadic abstract interpreters, complexity bounds in term rewriting , and educational tools for theorem proving . Notable contributions include compiler hardening schemes for hardware security and memory layout optimizations for algebraic data types. Academic Leadership : Scientific Director of the Summer School EJCP (École Jeune Compilation et Programmation) Board Member of the French national research group GDR GPL Teaching Responsibilities at Grenoble INP include courses in architecture , compilation , programming languages , algorithms , and databases . She has also taught at University of Lyon, ENS Lyon, Polytech'Lille, and INSA.
Michael Soltys is an Adjunct Professor in the Department of Computing and Software at McMaster University. His work bridges theoretical computer science, algorithms, and practical applications in cybersecurity and education. Research interests include logic, circuit complexity, and pairwise comparisons. Publications span 2002–2021, with recent focus on cloud computing education, digital forensics, and graph theory. Active in academic service through editorial contributions (e.g., Foreword for Franco-Canadian workshop proceedings). His scholarly activity maps to subdisciplines such as Computer Systems Theory, Logic, Discrete Applied Mathematics, and Operations Research. Dr. Soltys' work on pairwise comparisons and clique covers provides foundational insights for decision systems and graph optimization. He has also contributed to cloud curriculum development and malware analysis frameworks. As an educator, he co-authored An Introduction to the Analysis of Algorithms (2018, 2012, 2009), a textbook exploring algorithmic foundations. Current affiliations include the McMaster Experts database, with collaborations across theoretical computer science and applied cybersecurity research.
Martin Trapp is an Academy Postdoctoral Researcher in the Department of Computer Science at Aalto University, specializing in probabilistic machine learning. He is affiliated with Professor Arno Solin's research group, focusing on advancing tractable probabilistic models for real-world applications. His research centers on Probabilistic Circuits , Probabilistic Programming , and Bayesian Nonparametrics , with emphasis on hardware-efficient implementations for edge devices and multimodal systems. Key interests include uncertainty quantification in deep learning, neurosymbolic AI integration, and medical imaging applications. His work bridges theoretical foundations with practical deployment constraints, particularly in resource-limited environments. Analysis of his 15 most recent publications (2022-2025) reveals three dominant trends: (1) hardware-aware probabilistic inference for TinyML applications, (2) scalable Bayesian methods using bitstring representations and probabilistic programming, and (3) multimodal robustness in vision-language systems and medical imaging. His contributions span from theoretical circuit representations to real-world implementations in mammography analysis and vision-language models. Trapp secured a HIIT short-term project grant (November 2022) for "Positive Semi-Definite Circuits" under the Department of Computer Science. No formal advising relationships are documented in available sources. He actively collaborates with researchers including Arno Solin, Rui Li, and Marcus Klasson across institutions like Aalto University and the Helsinki Institute for Information Technology. As a core member of Aalto's Probabilistic Machine Learning group, he contributes to advancing probabilistic AI methodologies with applications in healthcare, edge computing, and multimodal reasoning. His current work emphasizes deployable probabilistic systems that maintain rigorous uncertainty quantification while meeting hardware constraints.
Fabrice Boissier is an Associate Professor at EPITA, specializing in digital methods for humanities and social sciences. He earned his PhD and MSc from Université Paris 1 Panthéon-Sorbonne, focusing on knowledge extraction and reuse in knowledge-intensive processes, enterprise modeling for decentralized organizations, and applications of formal concept analysis, natural language processing, and data visualization. Current Research: Formal Concept Analysis, Topic Modeling, Text Processing, Data Visualization, Knowledge Extraction, and Knowledge-Intensive Processes. Collaborations: Working with Nida Meddouri in the Security and Systems team and Marie Puren in the DMHSS (MNSHS) team. Teaching: Courses in algorithmics, computer architecture, programming languages, and operating systems at EPITA's Bachelor CyberSécurité program. Supervision: Mentoring research and industry interns from EPITA, Université de Sousse, and Université Paris 1 Panthéon-Sorbonne.
Michael Eichberg is a Professor at Technische Universität Darmstadt, Germany, where his work centers on software engineering, static analysis, programming languages, and secure software development tools. He is the principal architect of the OPAL framework for Java bytecode analysis and has an extensive publication record spanning PLDI, ICSE, ESEC/FSE, ISSTA, ASE, FSE, SOAP, and other premier venues. Research Interests: Static program analysis and its scalability to real-world code bases Software security, particularly cryptographic API misuse and Android app repackaging detection Concurrent and parallel programming models, including deterministic concurrency in Scala Software architecture conformance, drift and erosion detection, and rule reuse Development of open extensible tools and frameworks (OPAL, LectureDoc, QScope, Sextant, XIRC, IRC) Publication Trends: His recent work (2015-2022) demonstrates a strong focus on empirical evaluation of static analysis techniques, modular composition of analyses, and security-related program understanding. Key themes include unsoundness in call graph construction, purity and immutability analyses, parallelization of static analyses, and large-scale studies of cryptographic API misuse. Tools & Frameworks: OPAL – A flexible Java bytecode analysis and manipulation framework (core developer until 2019) LectureDoc 2 – Web-based lecture material authoring and presentation system QScope – Open extensible metrics framework for modern software projects Sextant – Eclipse-integrated software exploration tool XIRC/IRC – Frameworks for enforcing system-wide properties and architectural constraints
Stavros Tripakis is an Associate Professor at the Khoury College of Computer Sciences at Northeastern University , where he joined in 2018. He is on sabbatical during the 2024-2025 academic year. His research focuses on the foundations of software and system design , emphasizing formal methods , computer-aided verification and synthesis, with applications to safety-critical, embedded, and cyber-physical systems, security, and trustworthy AI. He leads a group developing theory and tools for designing better systems. Recent publications explore distributed protocol synthesis, neural network verification, and inductive invariant inference, reflecting trends in formal methods for AI and distributed systems. His work often intersects with automated reasoning, model checking, and tool development. Scientific awards include the Distinguished Artifact Award at TACAS 2018 for the Refinement Calculus of Reactive Systems (RCRS) toolset. He advises Derek Egolf , Daniel Melcer , and William Schultz (graduated 2025). Former postdocs include Rômulo Meira-Góes (now Penn State) and Eunsuk Kang (now CMU). Current projects include the NSF FMitF grant (2023-2027) on safe multi-agent reinforcement learning and the NSF SaTC grant (2018-2022) on protocol design.
Andreas Papasalouros is an Associate Professor at the Department of Mathematics, University of the Aegean. He holds a Ph.D. in Engineering from NTUA (2004), a Diploma in Electrical and Computer Engineering (2000), and a BSc in Physics (1992). His research focuses on Educational Technology , Adaptive Hypermedia , and Ontology Engineering . Education Ph.D. in Mechanics, School of Electrical and Computer Engineering, NTUA (2004) Diploma in Electrical and Computer Engineering, NTUA (2000) BSc in Physics, National and Kapodistrian University of Athens (1992) Research Interests Papasalouros's work centers on leveraging UML and Ontologies for designing Educational Software . He explores Automated Assessment systems, Accessibility solutions (e.g., TeX-to-Braille), and Mobile Learning applications. His studies often intersect with Collaborative Learning and Semantic Web technologies. Key Contributions His publications span Adaptive Hypermedia , Ontology-Driven Learning , and Accessibility Tools . Notable works include Ob-AHEM (2002), Grid4All Ontology (2008), and TeX-to-Braille Transcribing (2017). Recent trends emphasize Game-Based Learning and Query Log Analysis for ontology creation. Courses Taught New Technologies in Education (3rd semester) Introduction to Computer Science (2nd semester) Advanced Programming Languages (6th semester) Postgraduate Course in New Technologies in Education
Professor Prokar Dasgupta serves as Chair in Robotic Surgery & Honorary Consultant Urological Surgeon at King's College London's School of Medicine, specifically within the Peter Gorer Department of Immunobiology. He is a pioneering figure in robotic urological surgery in the UK and serves as Editor-in-Chief of the British Journal of Urology International (BJUI) since 2013. As theme lead for Experimental Surgery within King's Health Partners, he oversees significant translational research initiatives within one of the UK's largest Academic Health Sciences Centers. Professor Dasgupta's research spans multiple cutting-edge domains in urological surgery. His primary focus includes robotics in urology with scientific evaluation of procedures, stem cell and cell-targeted therapies for prostate and bladder cancer, bladder physiology research focusing on receptors like TRPV1 and P2X3, and innovative applications of botulinum toxin for overactive bladders. His work integrates engineering principles with clinical practice, developing mechatronic sensors, augmented reality systems, and 3D planning tools to enhance robotic surgical precision. His research group employs advanced techniques including micro-array technology, real-time PCR, and immunohistochemistry in both human tissues and animal models. Analysis of Professor Dasgupta's recent publications reveals a strong trend toward integrating artificial intelligence with robotic surgery. His work increasingly focuses on surgical workflow analysis, video recognition systems, and overcoming technical limitations in telesurgery. The publications demonstrate his leadership in both clinical applications of robotics and the underlying technological innovations that enable more precise surgical interventions. His research bridges engineering, computer science, and clinical urology to address fundamental challenges in surgical practice. His scientific recognition includes the prestigious Karl Storz-Harold Hopkins Golden Telescope award from the British Association of Urological Surgeons for significant contributions to urology, along with multiple awards for educational contributions including Best Oral Presentations and Best Posters in surgical education. He has been consistently recognized as one of BJUI's top reviewers. Professor Dasgupta has secured approximately £70 million through 36 research grants from major funding bodies including EUFP7, MRC, MS Society, and BUF. He leads a 28-strong multidisciplinary team comprising basic scientists, engineers, and clinician-scientists at King's College London. His supervisory role extends across numerous PhD students and research fellows, contributing to the 84 PhD students supervised by the 41 principal investigators within his division. His educational contributions include serving as tutor for MSc and FRCS (Urol) courses and as an examiner for the University of London. His research environment includes active collaboration with the Wellcome/EPSRC Centre for Medical Engineering and leadership in several major projects including AI-driven surgical skills acquisition, international AI research ecosystems, and innovative prostate cancer treatment trials. His laboratory work integrates robotics, imaging technology, and molecular biology to advance precision surgery in urological oncology.
Munindar P. Singh is the SAS Institute Distinguished Professor of Computer Science at North Carolina State University . He serves as a core faculty member in the Science of Security Lablet and contributes to initiatives in responsible computing and ethical AI . His research spans artificial intelligence , software engineering , and computing ethics . Education: Ph.D. in Computer Sciences from University of Texas at Austin (1993) B.Tech. in Computer Science and Engineering from Indian Institute of Technology, Delhi (1986) Research Focus: Dr. Singh's work centers on trustworthy AI and sociotechnical systems , with key contributions in Multiagent systems and BDI architectures Defensive cyberdeception using hypergame theory Normative systems for blockchain applications Equitable transportation systems via AI Service-oriented computing and protocol engineering Scientific Recognition: Fellow of AAAI , IEEE , and ACM Recipient of NSF CAREER Award and multiple industry awards Editor-in-Chief of ACM Transactions on Internet Technology Grant Activities: Currently leading several major NSF-funded projects including: SCC: Serving Households in Food Insecurity ($2.018M) RI: Foundations of Ethics for Multiagent Systems ($500K) Science of Security Lablet ($3.65M)
Yu Li is a Lecturer at the University of Picardie Jules Verne (UPJV) and a member of research unit UR 4290 “Optimization and Cryptography, AI – OCIA.” His office is located in room 302, reachable by internal telephone extension 5900. Research Interests Dr. Li’s research spans several inter-related domains: Optimization & Control Theory – developing dynamic optimization algorithms for industrial processes such as continuous casting in steel manufacturing. Cryptography & Security – investigating secure and dependable models for cloud and distributed systems. Artificial Intelligence & Robotics – integrating AI perception and decision-making into cloud-connected robotic platforms, including exoskeletons for rehabilitation and autonomous ground vehicles. Cloud & Fog Computing – designing middleware and domain-specific languages that seamlessly connect robotic devices with cloud and edge resources. Publication Trends Over the past decade, Dr. Li’s publication record reveals a clear evolution from foundational work in software architecture and component-based systems (2010-2016) toward cutting-edge applications in cloud/fog-enabled robotics and AI-driven cyber-physical systems (2017-2023). His studies increasingly emphasize real-world deployment, simulation-driven resource estimation, and human-centric interaction in rehabilitation robotics. Scientific Awards & Recognition No specific awards are listed in the provided materials. Advising & Funding No explicit information about supervised students or funded grants is available in the text supplied. Laboratories & Teams He carries out his research within the UR 4290 research unit “Optimization and Cryptography, AI – OCIA” at UPJV, focusing on collaborative projects that bridge mathematics, computer science, and robotics engineering.
