جست‌وجوی استاد و پژوهشگر

Stéphane Devismesمشاهده پروفایل

استاد

• Distributed Computing
• Distributed Algorithms
• Fault-Tolerance
• +۵ مورد دیگر

Stéphane Devismes is a Professor at the University of Picardy Jules Verne , affiliated with the ALCO team (Algorithmics and Complexity) in the Laboratoire MIS (UR 4290) . His research focuses on Distributed Algorithms , Fault-Tolerance , and Autonomous Mobile Robots with self-stabilizing properties. University: University of Picardy Jules Verne Department: Laboratoire MIS (UR 4290) Team: ALCO (Algorithmics and Complexity) Research Interests: Devismes specializes in Self-Stabilizing Algorithms for distributed systems, particularly in Graph Exploration and Robot Coordination . His work addresses challenges like chirality constraints , asynchronous environments , and polynomial convergence . Publication Trends: Recent articles emphasize infinite grid exploration with minimal robots, model checking for distributed algorithms, and efficient self-stabilization in directed networks. Themes include autonomous systems , resource allocation , and network dynamics , often leveraging propositional satisfiability and SAT solvers . Scientific Awards: 2022 Wilkes Award for "Terminating Exploration Of A Grid By An Optimal Number Of Asynchronous Oblivious Robots" Best Paper at NETYS'2020 Best Student Paper at ICDCN'2023 Grants & Projects: Involved in the ANR SkyData project for intelligent autonomous data systems and developed the SASA simulator for self-stabilizing algorithms. His HDR (2020) on "Generality and Efficiency in Self-Stabilizing Distributed Systems" highlights his leadership in certified algorithmic frameworks. Teaching & Mentorship: Authored seminal books like "Introduction to Distributed Self-Stabilizing Algorithms" (2019) and "Bases de données - Informatique BUT 1re année et L1" (2024). Co-organized conferences including AlgoTel'2025 and served on program committees for PODC , DISC , and SSS .

Marlon Azinovic-Yangمشاهده پروفایل

استادیار

• Computational Economics
• Financial Economics
• Macroeconomics
• +۵ مورد دیگر

Marlon Azinovic-Yang is an Assistant Professor in the Economics Department at the University of North Carolina at Chapel Hill. He joined UNC in 2025 after postdoctoral positions at the University of Zurich and the University of Pennsylvania. He holds a Ph.D. in Finance from the University of Zurich and the Swiss Finance Institute (2021), where he was advised by Felix Kübler and co-advised by Simon Scheidegger. Research Areas Macroeconomics Financial Economics Computational Methods Deep Learning-Based Solutions Heterogeneous Agent Models Inequality Publication Trends Marlon’s work focuses on developing deep learning-based computational methods to solve macroeconomic models with heterogeneous agents, inequality, and complex constraints. His research bridges theoretical economics with modern machine learning, emphasizing equilibrium models and asset pricing. Earlier work in physics explores quantum annealing applications for computational problems in satisfiability filters. Awards 3rd Place Best Poster Award at PASC Conference 2019 Advisors Ph.D. Advisor: Felix Kübler Co-Advisor: Simon Scheidegger

David Monniauxمشاهده پروفایل

پژوهشگر

• program verification
• abstract interpretation
• static analysis
• +۸ مورد دیگر

David Monniaux is a senior researcher (directeur de recherche) at CNRS and an adjunct professor at École polytechnique. He works at VERIMAG, a computer science laboratory jointly operated by CNRS and the University of Grenoble. Dr. Monniaux obtained his PhD in 2001 from Université Paris Dauphine under Professor Patrick Cousot, with a dissertation on the static analysis of probabilistic programs by abstract interpretation. He later earned his habilitation in computer science in 2009 from Université Joseph Fourier, Grenoble, and also holds an agrégation in mathematics. Monniaux's research focuses on program verification, with particular emphasis on proving software correctness. His work spans theoretical foundations in computability theory and practical applications in safety-critical systems. He has made significant contributions to abstract interpretation, static analysis, and the verification of numerical properties in programs. His research bridges computer science theory with practical engineering challenges, particularly in the context of critical embedded systems where software failures can have severe consequences. His work connects to diverse fields including game theory, algebra, and convex optimization. His recent publications demonstrate a strong focus on improving the precision and efficiency of static analysis techniques. Key themes include polyhedral approximation, program analysis with local policy iteration, abstraction of arrays and maps, synthesis of ranking functions, and computing worst-case execution times. These works collectively advance the field of program verification by addressing challenges in handling nonlinear constraints, branching, and complex data structures while maintaining computational feasibility. Monniaux has supervised several students including Julien Henry, Alexis Fouilhé, George (Egor) Karpenkov, and Alexandre Maréchal (now at LIP6), with current students Hang Yu and Valentin Touzeau. He has led significant research projects including VERASCO (2012-2015), which aimed at integrating a static analyzer into the CompCert certified compiler, and STATOR (2012-2017), an ERC starting investigator grant exploring advanced techniques for automatic inference of program invariants. At VERIMAG, Monniaux is part of a vibrant research community focused on critical systems. His work connects with broader efforts in formal methods, with applications in aviation, automotive systems, and other safety-critical domains where software reliability is paramount.

• Formal Methods
• Program Verification
• Term Rewriting Systems
• +۳ مورد دیگر

Ștefan Ciobâcă is a Professor at the Faculty of Computer Science , Alexandru Ioan Cuza University in Iași, Romania. He specializes in formal methods, program verification, and term rewriting systems, with a focus on tools like Dafny and K Framework. Current research: Interactive proof modes for Dafny (Amazon Research Award) Teaching: Verification Driven Program Development and Logic in Computer Science Research Interests include formal verification of programs, reachability logic, and static analysis of C/C++ code. His work bridges operational semantics with SMT solvers and applies coinductive methods to prove program properties. Scientific Awards include the Amazon Research Award Coq-mechanized soundness proofs DBLP publication citations Student Supervision covers Dafny/F*-based verification projects on algorithms like Boyer-Moore, DPLL, and greedy methods. He leads the RMT: Rewriting Modulo Theories tool development and contributes to K Tool framework.

Irena Burićمشاهده پروفایل

استاد

• Educational Psychology
• Teacher Emotions
• Personality Psychology
• +۴ مورد دیگر

Irena Burić is a Professor in the Department of Psychology at the University of Zadar, Croatia. With a distinguished academic career, she has established herself as a leading researcher in educational psychology, particularly focusing on teacher emotions, personality, and professional performance. Her extensive research portfolio includes multiple projects funded by the Croatian Science Foundation and the Ministry of Science, Education and Sport. Professor Burić's research interests center on teacher self-efficacy, emotional regulation strategies among educators, the relationship between personality traits and teaching performance, and the psychological well-being of teachers. Her dynamic perspective examines how these factors interact and evolve over time, providing important insights into teacher effectiveness and burnout prevention. She has developed assessment tools for teaching quality and investigated longitudinal relationships between teacher characteristics and performance outcomes. Her recent publications (2024-2025) demonstrate consistent focus on validating teaching quality measures, examining longitudinal relationships between teacher characteristics and performance, and exploring contextual factors influencing teacher effectiveness. This work bridges theoretical psychology with practical educational applications, contributing significantly to both academic understanding and classroom practice. Professor Burić serves on the editorial boards of several prestigious journals including Educational Psychology , International Journal of School and Educational Psychology , and Psychological Test Adaptation and Development , contributing to scholarly discourse in her field. As an academic mentor, she has guided doctoral students, including Krešimir Jakšić, whose dissertation focused on teacher self-efficacy and personality dynamics. Her commitment to developing educational resources is evident in her co-edited handbook 'How to be a satisfied and successful teacher?'

• Formal Verification
• Model Checking
• Automated Reasoning
• +۹ مورد دیگر

Georg Weissenbacher is a Full Professor of Computer Science at Vienna University of Technology (TU Wien), working in the Institute of Logic and Computation within the Faculty of Informatics. He leads the Formal Methods in Systems Engineering research group and has established himself as a leading researcher in formal verification and automated reasoning. His educational background includes a DPhil from Oxford University (2008-2010), research at ETH Zürich (2005-2010), and a Master's degree from TU Graz (completed by 2003). He completed his Habilitation at TU Wien in 2016 with a thesis on Logical Methods in Automated Hardware and Software Verification. Weissenbacher's research focuses on developing automated tools for software and hardware verification, with particular emphasis on detecting and explaining bugs in complex systems. He is renowned for his work on heisenbugs - bugs that disappear when analyzed, which are particularly challenging in concurrent and multi-core systems. His research bridges theoretical foundations in logic with practical applications in software engineering, with significant contributions to interpolation-based verification techniques and SAT/SMT solving applications. His recent publications show a clear progression from traditional software verification toward emerging challenges in AI security, neural network verification, and sophisticated concurrency models. The research trajectory demonstrates increasing sophistication in handling complex systems properties, with a growing emphasis on probabilistic guarantees and formal methods applied to modern computing challenges. OOPSLA'18 Distinguished Paper Award for 'Randomized Testing of Distributed Systems with Probabilistic Guarantees' Weissenbacher has advised numerous PhD students and postdocs, including current researchers Mai AL-Zu'bi, Katalin Fazekas, and Sarah Sallinger. His research has been supported by significant grants including the Vienna Research Groups for Young Investigators (2011), the National Research Network 'Rigorous Systems Engineering' funded by FWF, and a Microsoft Research PhD Scholarship (2016). He actively contributes to the academic community through his service as co-chair for major conferences including CAV 2018 and FMCAD 2017. As leader of the FORSYTE research group at TU Wien, Weissenbacher oversees a vibrant research team working at the intersection of logic, verification, and practical software engineering challenges. The group is currently involved in the Doctoral College on Automated Reasoning, funded by FWF, which aims to train the next generation of researchers in this critical field.

Hazem Torfahمشاهده پروفایل

استادیار

• cyber-physical systems
• formal verification
• runtime monitoring
• +۵ مورد دیگر

Hazem Torfah is a tenure-track Assistant Professor at the Computer Science and Engineering Department at Chalmers University of Technology, where he leads the Safe and Trustworthy Autonomous Reasoning lab (STARlab). Previously, he was a postdoctoral researcher in the EECS Department at UC Berkeley, USA, and obtained his Ph.D. in 2019 from Saarland University, Germany. His research focuses on developing theoretical foundations and techniques for constructing safe and reliable autonomous cyber-physical systems. Hazem earned his Ph.D. from Saarland University in 2019, followed by postdoctoral research at UC Berkeley. His educational background has positioned him at the forefront of formal methods research for autonomous systems. His research interests center on the formal specification, verification, and synthesis of cyber-physical systems, with a particular focus on quantitative approaches for verifying and explaining system behavior. He investigates methods to ensure safety and reliability in autonomous systems through runtime monitoring, specification mining, and assurance frameworks. His work bridges theoretical computer science with practical applications in autonomous driving and robotics. An analysis of his recent publications reveals a strong focus on runtime monitoring techniques for operational design domains, specification mining for predictive safety, and frameworks for runtime assurance of cyber-physical systems. His work frequently combines formal methods with machine learning to address safety challenges in autonomous systems, with applications primarily in autonomous driving. Hazem's research is funded by the Wallenberg AI, Autonomous Systems, and Software Program, reflecting the significance and potential impact of his work in the field of assured autonomy. He has supervised several Master's students, including Samuel Collier Ryder and Johannes Holmgren (2025), and Lucas Karlsson and George Kayembe (2024). His teaching includes courses on Formal Methods for Security, Oracle-Guided Inductive Synthesis, and Data Structures and Algorithms. As the leader of STARlab, Hazem directs research on safe and trustworthy autonomous reasoning, focusing on developing methods to ensure the reliability and explainability of autonomous cyber-physical systems through formal verification techniques.

• Formal Methods
• Model Checking
• Automata Theory
• +۵ مورد دیگر

Mahesh Viswanathan is a Professor and Associate Head at the Siebel School of Computing and Data Science at the University of Illinois. His primary research focuses on formal methods, automata theory, and model checking, with applications in computer security, runtime verification, and cyber-physical systems. He received the NSF CAREER Award in 2005 for his contributions to these fields. His research explores: Foundations of automata theory and formal verification Runtime assurance mechanisms for safety-critical systems Concurrency analysis and race detection algorithms Differential privacy and security protocol verification Theoretical aspects of real-time and hybrid systems Viswanathan's recent publications demonstrate a strong focus on developing theoretically-grounded verification techniques for practical applications. His work frequently combines formal methods with machine learning approaches to solve challenging problems in program verification and system security. Awards and Honors: NSF CAREER Award (2005)

Mehrdad Sabetzadehمشاهده پروفایل

استاد

• Software Engineering
• Requirements Engineering
• Applied Artificial Intelligence
• +۵ مورد دیگر

Mehrdad Sabetzadeh is a Full Professor and Co-director of the Sedna Research Lab at the University of Ottawa's School of Electrical Engineering and Computer Science. He holds a PhD from the University of Toronto and has held roles at institutions like Simula Research Lab and the University of Luxembourg. His research focuses on software engineering, requirements engineering, AI applications, and legal compliance, with industry collaborations across sectors like finance, energy, and automotive. He leads over $7M in industry-funded projects and co-developed tools like PLEDGE, NARCIA, and Modus. Teaching includes graduate courses on NLP/ML in software engineering and undergraduate computing. Research emphasizes applying AI (NLP, ML) to software challenges, with a focus on IoT and safety-critical systems. Key contributions include frameworks for legal compliance simulation (e.g., GDPR), automated requirement analysis, and safety evidence management. His work bridges academia and industry, addressing real-world system certification and reliability issues. Notable achievements include 150+ publications, tool development for requirement slicing, security control analysis, and safety modeling. He actively mentors graduate students and chairs major conferences like ASE and RE. Current projects explore LLMs for requirement completeness and compliance automation, reflecting his commitment to advancing impactful software engineering practices.

Yap Rolandمشاهده پروفایل

دانشیار

• Constraint Programming
• Optimization
• Combinatorial Problems Modelling
• +۵ مورد دیگر

Yap Roland is an Associate Professor at the School of Computing, National University of Singapore (NUS), and a member of the Institute of Operations Research and Analytics (IORA). His research focuses on constraint programming and solving, optimization, combinatorial problems, vehicle routing, and big data applications. He actively contributes to advancing methodologies in computational logic, software security, and algorithm design. His work spans theoretical foundations of constraint satisfaction (CSP/SAT) and practical applications in database systems, graph neural networks, and transportation logistics. Notable contributions include benchmarking tools like OSS-Bench for coding LLMs, novel approaches to detecting logic bugs in graph databases, and enhancing security through randomized pointer techniques. His research bridges algorithmic theory and real-world challenges in AI, cybersecurity, and efficient resource allocation. Yap Roland has published extensively in top-tier venues such as the International Conference on Principles and Practice of Constraint Programming (CP) and the International Conference on Theory and Applications of Satisfiability Testing (SAT). His recent work emphasizes scalability, fairness in machine learning, and robustness against memory errors in software systems.

• Multi-agent systems
• Real-Time Systems
• Explainable AI (XAI)
• +۵ مورد دیگر

Davide Calvaresi is an Associate Professor at HES-SO Valais-Wallis (University of Applied Sciences and Arts Western Switzerland) in the Engineering and IT school within the Computer Science and Communication Systems department. His research focuses on multi-agent systems , real-time systems , explainable AI (XAI) , and blockchain for trustworthy applications in healthcare and safety-critical domains. Current projects include EXPECTATION (Personalized Explainable AI for decentralized agents) and past projects like Axe Santé 2020 (interdisciplinary health research) and Simulator of multi-agent systems (timing reliability analysis). Collaborations include researchers from University of Bologna, University of Luxembourg, and Ozyegin University. Recent publications focus on swarm intelligence in IoT , ethical AI for aging populations , and explainable health coaching systems Technical contributions include DEXiRE (rule extraction from neural networks), SCoDES (blockchain-based consent management), and HAExA (parsimonious XAI architecture)

Ankur Moitraمشاهده پروفایل

استاد

• Theoretical Computer Science
• Machine Learning
• Algorithms
• +۳ مورد دیگر

Ankur Moitra is the Norbert Wiener Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Department of Electrical Engineering and Computer Science and the Theory of Computation research group. His work focuses on foundational aspects of algorithms, machine learning, and theoretical computer science, with applications to cryptography, quantum computing, and statistical learning. He leads research initiatives in algorithmic robustness, tensor decomposition methods, and reinforcement learning. Moitra’s research spans algorithm design, computational complexity, and probabilistic models. Notable contributions include robust learning algorithms for mixtures of distributions, tensor decomposition techniques, and theoretical analyses of reinforcement learning and adversarial machine learning. His work bridges mathematical theory with practical computational challenges, often addressing algorithmic guarantees under noise or adversarial conditions. His recent publications highlight advancements in areas such as cryptographic watermarking, quantum Hamiltonian learning, and efficient sampling from complex distributions. Despite no explicitly listed awards, his contributions have influenced major areas of theoretical computer science. His research group collaborates across MIT’s School of Science and the Computer Science and Artificial Intelligence Laboratory (CSAIL).

• Software Engineering
• Program Analysis
• Compiler Design
• +۵ مورد دیگر

Matthew Dwyer is a Professor in the Department of Computer Science at the University of Virginia's School of Engineering and Applied Science. With an active research program spanning software engineering, program analysis, and neural network verification, he teaches graduate courses including CS6888 as evidenced by his public course repository. His research spans traditional software engineering domains and cutting-edge AI verification challenges. Dwyer's work bridges classic program analysis techniques with modern neural network verification, focusing on creating practical tools for ensuring software correctness. His recent publications demonstrate a strategic shift toward addressing verification challenges in deep learning systems while maintaining strong foundations in static analysis and compiler technologies. Dwyer's publication record shows consistent high-impact contributions with a notable recent emphasis on neural network verification and testing. His work on tools like NeuralSAT and RBT4DNN represents significant advances in making formal verification techniques applicable to modern deep learning systems. The thematic evolution from traditional program analysis to AI safety reflects broader trends in software engineering research. Dwyer has contributed to major software engineering venues including numerous publications in top conferences and journals. His work on the tipc compiler and associated LLVM passes demonstrates his commitment to practical tool development alongside theoretical advances. As an educator, Dwyer maintains active engagement with students through graduate course development and research mentorship. His GitHub presence shows commitment to open scholarship with publicly available course materials and research tools.

• Programming Languages
• Software Engineering
• Compiler Optimization
• +۵ مورد دیگر

Qirun Zhang is an Assistant Professor in the School of Computer Science at the Georgia Institute of Technology . He holds the Catherine M. and James E. Allchin Early Career academic title. His research focuses on programming languages , software engineering , and compiler optimization , with an emphasis on program analysis , static analysis , and formal methods . He received his Ph.D. in Computer Science and Engineering from The Chinese University of Hong Kong (2013) and a Bachelor's from Zhejiang University (2009). Research Interests include techniques for improving software reliability/security via program analysis and compiler optimization. His work leverages computational complexity, analytic combinatorics, graph theory, and formal languages. Notable contributions involve debug information validation , context-free language reachability , and compiler testing frameworks like Skeletal Program Enumeration (SPE) . Recent Work spans scalable cryptographic accelerator design, LLVM-based debug validation, and SMT solving optimizations. His papers often address algorithmic improvements for reachability problems and compiler correctness. Awards include the PLDI Distinguished Paper Award (2020) and Facebook Fellowship (2021). He serves on program committees for top venues like POPL, SAS, and PLDI, and chairs artifact evaluation committees (PLDI'25). Teaching includes courses on compilers (CS 4240), software analysis (CS 6340), and advanced program analysis (CS 8803). He mentors a research group with current Ph.D. students and MS/undergraduate researchers. Lab/Team focuses on rigorous compiler validation and program analysis tools. Open positions are available for Fall 2025.

• Software Verification
• Automata Theory
• Formal Methods
• +۳ مورد دیگر

Matthias Heizmann is a Professor at the University of Freiburg's Department of Computer Science, part of the Faculty of Engineering. His research focuses on software verification, automata theory, and formal methods. He leads the development of the Ultimate Program Analysis Framework , particularly its Ultimate Automizer toolchain. Heizmann teaches courses on program verification, theoretical computer science, and automata theory. His work emphasizes automata-based verification techniques, termination analysis, and abstract interpretation refinement. He actively supervises student projects in program analysis and formal methods, integrating theoretical insights with practical implementations in the Ultimate framework. His research has been presented at conferences like CAV, TACAS, and SAS, with contributions to both theoretical foundations and practical verification tools.