Tej Chajed is an Assistant Professor in the Department of Computer Sciences at the University of Wisconsin-Madison, focusing on formal verification of systems software. His research bridges theoretical foundations and practical implementations to ensure software correctness in concurrent and crash-safe systems. Research interests include formal verification, concurrency, crash safety, and programming languages, particularly using Coq, Perennial, and Goose frameworks. He has contributed to systems like DaisyNFS, a verified file system with sequential reasoning, and Verus, a foundation for systems verification. His work appears in top venues like SOSP, OSDI, and PLDI. 2025: Dafny PC Member 2024: PLDI Committee Member, CoqPL Co-chair 2023: CoqPL Co-chair, POPL Program Committee He actively mentors students and develops tools for systems verification education, including extensive Coq-based course materials.
Umang Mathur is an Assistant Professor at the National University of Singapore's School of Computing, where he leads the FOCS Lab and is affiliated with PLSE@NUS. His research focuses on Formal Methods , Concurrency , and Decidability in Programming Languages and Software Engineering . PhD in Computer Science from the University of Illinois at Urbana-Champaign (advisor: Prof. Mahesh Viswanathan) Former Research Scientist at Facebook Inc. and Research Fellow at the Simons Institute Recipient of Google PhD Fellowship, 2024 CPP Distinguished Paper Award, 2023 ACM SIGPLAN Award, and ASPLOS 2022 Best Paper Award His recent work explores algorithmic techniques for detecting concurrency bugs , decidable program verification , and synthesis , with a focus on weak memory models, predictive monitoring, and automata-theoretic approaches. Articles span topics like causal concurrency, tree clock data structures, and probabilistic counting algorithms, reflecting interdisciplinary intersections of logic and systems research. Scientific Awards Google PhD Fellowship 2024 CPP Distinguished Paper 2023 ACM SIGPLAN Distinguished Paper 2022 ASPLOS Best Paper 2018 ESEC/FSE Distinguished Paper He advises PhD students in Formal Methods and supervises teams in the FOCS Lab. Teaching includes advanced modules on Automata Theory, Logic, and Verification at NUS.
Andrea Simonetto is a Research Professor at the Applied Mathematics Unit (UMA) , ENSTA Paris, Institut Polytechnique de Paris. His work spans optimization, control theory, and learning algorithms for large-scale and streaming data , with applications in smart grids, intelligent transportation, personalized health, and quantum computing. Current research focuses on online algorithms for time-varying optimization , personalized optimization for cyber-physical systems , and variational quantum algorithms . Past contributions include theoretical and algorithmic advances in convex/non-convex optimization, distributed optimization (robotic networks, smart grids), and signal processing for sparse reconstructions and parallel computing in particle filtering. Key application domains include renewable energy integration , quantum state preparation , and human-in-the-loop control systems . His research is published in journals like ACM Transactions on Quantum Computing , IEEE Control Systems Letters , and Automatica .
Aws Albarghouthi is affiliated with the University of Wisconsin-Madison, USA. He is an active researcher with significant contributions to program synthesis, formal verification, and machine learning. Key roles: Author, Session Chair, Committee Member in conferences like PLDI, POPL, VMCAI, SPLASH, and ICFP. Research spans quantum computing, differential privacy, and static analysis. Research Trends include: Quantum Circuit Compilation and Optimization Probabilistic Verification of Fairness and Privacy Synthesis of Datalog and MapReduce Programs Neural-Augmented Static Analysis Bias Detection in Data Security Robustness in Machine Learning
Toufik AZIB is a Full Professor and scientific coordinator of the ECMS (Energy and Conception of Mechatronic Systems) research theme at ESTACA Engineering School in France. He leads a team of 6 teacher-researchers and 13 PhD students, focusing on optimal design of power electronics and energy management for hybrid power systems. His work bridges academic research and industrial applications in sustainable mobility, with strong collaborations across Europe and Algeria. Dr. AZIB received his Electrotechnical Engineering Diploma from the University of Setif, Algeria in 2006, followed by an M.Sc. in Electrical Engineering from ENSEM-INPL, France in 2007. He earned his Ph.D. in electrical engineering from the University of Paris South XI in 2010 and completed his HDR (Habilitation à Diriger des Recherches) from the University of Paris Saclay in 2021. His academic journey reflects a strong foundation in both theoretical and applied electrical engineering. His research focuses on the modeling, control, and optimal design of embedded energy systems under multi-physical constraints (electrical, thermal, electromagnetic compatibility, volume, reliability). He specializes in energy management strategies for hybrid systems combining fuel cells, batteries, and ultracapacitors, with applications in electric vehicles and the 'more electric aircraft.' His work integrates numerical and experimental approaches to develop methodologies for pre-dimensioning and real-time energy management, addressing challenges in sustainable transportation. Analysis of Dr. AZIB's recent publications reveals a strong trend toward multidisciplinary design optimization for automotive applications, particularly electronic throttle systems. His research increasingly incorporates knowledge management techniques and addresses reliability considerations in hybrid power source design. There's a clear progression from fundamental energy management strategies to sophisticated eco-driving solutions for electric vehicles, reflecting the evolving demands of sustainable mobility. Best Paper Award for 'Structure and Control Strategy for a Parallel Hybrid Fuel Cell/Supercapacitors Power Source' at IEEE VPPC'09 Dr. AZIB has supervised numerous PhD and Master's students across multiple institutions in France, Algeria, and Colombia. He leads significant research projects including MIMe (Module d'Intégration et de simulation Mécatronique), ECOS Nord (Eco-driving strategies for electric motorcycle), and AmCoAIR (improving air quality in vehicle cabins), securing funding from national and international sources. His work demonstrates strong industry collaboration with partners like Valeo, PSA, and Renault. As experimental platforms coordinator since 2012, Dr. AZIB oversees 10 specialized experimental facilities at ESTACA's S2ET-Paris Saclay research pole, including those for autonomous electric vehicles, drones, electric machines, and power modulators. His team regularly develops proof-of-concept demonstrators to validate research findings, such as the Formula Student electric vehicle and the 'Electric Appeal' streamliner project, demonstrating practical applications of their theoretical work.
Petr Kuznetsov is a Professor at Telecom Paris (Institut Polytechnique de Paris), affiliated with the Department of Computer Science and Networks (INFRES). He leads the Autonomous Critical Embedded Systems (ACES) research team at the Information Processing and Communication Laboratory (LTCI). His work bridges theoretical foundations and practical applications in distributed systems. Research Focus: Kuznetsov specializes in distributed algorithms, synchronization protocols, failure detection mechanisms, and the application of algebraic topology to distributed computing. His recent work explores Byzantine fault tolerance, blockchain consensus, and concurrency in networking infrastructures. Recent Publication Trends (2015-2025): His articles predominantly focus on scalability and resilience in distributed systems, with emerging themes in blockchain technologies, Byzantine fault tolerance, and concurrency optimization. Theoretical contributions include computability theorems and complexity bounds, while applied work targets payment systems and distributed ledgers. Awards & Honors: Best Paper Award at DISC 2019 for Scalable Byzantine Reliable Broadcast Best Student Paper Award at PODC 2018 for An Asynchronous Computability Theorem for Fair Adversaries Projects & Advising: He directs the TrustShare Innovation Chair (large-scale data synchronization) and DISCMAT (mathematical foundations of distributed computing). Actively seeks PhD candidates for projects on distributed algorithms and concurrency. Laboratory & Teams: Heads the ACES team at LTCI, focusing on critical embedded systems and fault-tolerant distributed architectures. Collaborates internationally through workshops like SPTDC.
Masao Fukushima is a Professor at the Department of System and Mathematical Sciences within the Faculty of Science and Engineering at Nanzan University, Japan. His research focuses on advanced optimization methodologies, including nonlinear programming, variational inequalities, and stochastic optimization. He holds editorial roles in academic journals and was recognized as a 2010 ISI Highly Cited Researcher in Mathematics. His work emphasizes theoretical development and algorithmic innovation in optimization fields such as complementarity problems and equilibrium-constrained programming. Research Interests: Nonlinear Programming Parallel Optimization Algorithms Global and Stochastic Optimization Mathematical Programs with Equilibrium Constraints Nonsmooth Optimization Editorial Activities: Maintains editorial board memberships as of July 2017. No specific grants or labs are detailed in the provided text, though his academic profile reflects sustained contributions to optimization theory and applications.
Maryam Mehri Dehnavi is an Associate Professor in the Department of Computer Science at the University of Toronto and a Principal Research Scientist at NVIDIA. She holds the Canada Research Chair in Parallel and Distributed Computing and leads the ParaMathics research group. Research focuses on high-performance computing , machine learning , sparse matrix optimizations , and compiler design for heterogeneous systems. Her work develops domain-specific languages , scalable numerical libraries , and auto-vectorization techniques for cloud and GPU platforms. Recent publications address LLM compression , sparse code translation , GPU kernel synchronization , and control flow optimization . Scientific recognition: Ontario Early Researcher Award (2021), NSF CRII Grant, NSERC New Frontiers in Research Fund. Current students: Mushegh Shahinyan , Martin Phan , Maryam Haghifam , and others. Former advisees: Kazem Cheshmi (NJIT), Zachary Blanco (MIT Lincoln Lab), Yuanxi Li (Amazon).
Arnaud Legrand is a tenured CNRS researcher at the University of Grenoble, France, affiliated with the Laboratoire d'Informatique de Grenoble (LIG). He earned his M.S. and Ph.D. from École Normale Supérieure de Lyon in 2000 and 2003, respectively, and completed his Habilitation Thesis at Grenoble University in 2015. His work focuses on optimizing large-scale distributed computing infrastructures and advancing reproducible research methodologies. Education: M.S., École Normale Supérieure de Lyon Ph.D., École Normale Supérieure de Lyon Habilitation Thesis, University of Grenoble Legrand is a leader of the SimGrid project, an open-source simulation toolkit for parallel and distributed system optimization. He has actively promoted open science, reproducibility, and rigorous experimental practices through tutorials and keynotes globally.
Yasmina Abdeddaïm is an Associate Professor at Université Gustave Eiffel and affiliated with ESIEE Paris. She works within the Laboratoire d'Informatique Gaspard-Monge (Softwares, Networks and Real-time team) and serves as Head of the Master in Artificial Intelligence and Cybersecurity (AIC) program. Her research focuses on real-time systems, critical systems, and scheduling algorithms. University: Université Gustave Eiffel Role: Head of Master AIC program Laboratory: Laboratoire d'Informatique Gaspard-Monge Team: Softwares, Networks and Real-time Her research spans real-time systems , mixed-criticality scheduling , energy-harvesting systems , and probabilistic schedulability . Recent publications analyze compilation optimization impacts on timing variability and propose new models for real-time deep neural networks over GPUs. She employs formal methods like timed automata for scheduling verification. Her teaching includes courses on Real-time Systems , Model Checking , Critical Application Development , and Artificial Intelligence . She is based at Cité Descartes, Champs-sur-Marne, France, with office contact details provided.
Kenza Kellou-Menouer is a researcher affiliated with the ETIS Laboratory at ENSEA, France, and part of the MIDI research group . Her work focuses on schema discovery for Semantic Web data, data mining, and big data optimization. Research: Semantic schema discovery, clustering/classification algorithms, and association rules. Teaching: Semantic Web technologies, database design, algorithms, and programming languages (Java, C++, C#, C). Research Interests center on Semantic Web data integration, RDF schema inference, and hybrid machine learning approaches. She has contributed to scalable schema discovery systems and real-time profiling techniques for large datasets. Publications include work on schema inference tools (SchemaDecrypt++, HInT) and methodological frameworks presented at top-tier venues like VLDB (A*), ICDE (A*), SSDBM (A), and ISWC . Her research bridges theoretical advancements with practical implementations for RDF datasets. Community Contributions include organizing tutorials at the International Semantic Web Conference (ISWC) 2022 and developing educational materials for database and programming courses.
Phong Nguyen is a Research Professor at Inria (Directeur de recherche) and a part-time professor at the Computer Science Department (DI ENS) of École Normale Supérieure (ENS), PSL University in Paris. He leads the ENS Crypto Team (Inria Equipe Projet Cascade) and serves as the principal investigator for the ERC Advanced Grant PARQ (2020) focused on lattices in parallel and quantum computing. He holds a PhD (1999) and Habilitation (2007) from ENS-Lyon, with an agrégation de mathématiques (1997). His research integrates cryptography, algorithmic number theory, and lattice-based computations, emphasizing: Cryptanalysis : Deconstructing cryptographic protocols, especially lattice-based systems Post-quantum cryptography : Developing quantum-resistant solutions Lattice algorithms : Optimization of reduction, enumeration, and sieving techniques Real-world applications : Bridging theoretical constructs with practical security implementations His publications (spanning Eurocrypt, Asiacrypt, and Journal of Cryptology) demonstrate deep expertise in lattice cryptography, with recurring themes in algorithm efficiency, cryptanalysis of NTRU/GGH systems, and theoretical advancements in lattice reduction. Recent work (2024) continues this trajectory with improved BKZ analysis and hypercubic lattice optimizations. Awards include : ERC Advanced Grant (2020) for PARQ project Best Paper Award at EUROCRYPT 2006 Cor Baayen Award (2001) He advises PhD students (e.g., Henry Bambury, Leo Ducas) and interns from institutions like École Polytechnique and ENS. He directs the ENS Crypto Team and previously held leadership roles as: French Director of the Japanese-French Laboratory for Informatics (2015-2019) European Director of LIAMA (Sino-European Computer Science Lab, 2013-2015) Coordinator of ECRYPT II virtual labs (2008-2012)
Alexandre Duret-Lutz is a Professor at École pour l'Informatique et les Techniques Avancées (EPITA) in the Laboratoire de Recherche de l'Epita (LRE). He holds a habilitation (HDR) from Université Pierre & Marie Curie (Paris 6). His research focuses on ω-automata and their application in model checking, particularly through the development of the SPOT library, a C++ tool for manipulating ω-automata and implementing model checkers. Education: HDR from Université Pierre & Marie Curie (Paris 6). Research interests include formal verification, automata theory, and LTL synthesis. He has contributed to tools like Vaucanson and Seminator, and is involved in the reactive synthesis competition SYNTCOMP. His work emphasizes optimizing automata constructions and improving verification efficiency. Key awards include the Best Paper Award at CIAA'24 and the Best Paper Award at Ada-Europe'01. He teaches courses on algorithms, complexity, and reproducible research at EPITA. Labs/Teams: Active contributor to the LRE and SPOT library development. Collaborates on projects involving formal methods and automated synthesis.
Stephen Chong is a Gordon McKay Professor in the Harvard John A. Paulson School of Engineering and Applied Sciences , where he co-directs the Undergraduate Studies in Computer Science program. His research intersects programming languages and information security , focusing on language-based security frameworks. Education : PhD in Computer Science from Cornell University (2008), B.Sc.(Hons) and B.A. from Victoria University of Wellington (New Zealand). Research : Develops tools like Formulog (Datalog + SMT for static analysis) and Accrue (Java interprocedural analysis), emphasizing security guarantees proportional to programmer effort. Grants : Funded by NSF , DARPA , AFOSR , and Google Faculty Research Award . Recent publications focus on neurosymbolic approaches (e.g., Guess & Sketch ), Datalog synthesis (e.g., Making Formulog Fast ), and quantitative robustness in cyber-physical systems. His group has pioneered formal methods for secure assembly transpilation and sensor attack modeling. Awards : NSF CAREER Award AFOSR Young Investigator Award Sloan Research Fellowship Advising : Supervised numerous PhD and senior thesis students, including Aaron Bembenek , Anitha Gollamudi , and Lucas Waye . Mentored projects like AbcDatalog (multi-threaded Datalog engine) and Shill (secure shell scripting). Labs/Teams : Leads the Programming Languages at Harvard group, collaborating with institutions globally. Organized workshops (e.g., NSF Workshop on Formal Methods for Security ) and chaired committees at conferences like CSF , POPL , and PLDI .
Hanjun Kim is a researcher at Yonsei University, focusing on compiler design, machine learning optimization, and hardware-aware programming techniques. His work bridges theoretical research with practical implementations in embedded systems and security domains. Research Interests Compiler-driven optimization for PIM (Processing-in-Memory) architectures Homomorphic encryption compiler design Parallel computing for DNN/LLM inference Network function program analysis Recent research trends include: application of compiler techniques to optimize resource utilization in heterogeneous computing environments, particularly for AI workloads and secure computation. His publications demonstrate expertise in tackling performance bottlenecks through architectural and compiler co-design. Conference Service 2025 SPLASH OOPSLA Review Committee 2025 LCTES Program Committee 2024 CGO Program Committee 2023 LCTES Program Committee 2022 CGO Organization Committee 2020 LCTES Program Committee
