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Ruben MartinsView profile

Assistant Professor

• Constraint Programming
• Program Synthesis
• Formal Verification
• +3 more

Ruben Martins is an Assistant Professor at Carnegie Mellon University's School of Computer Science and serves as the program director of the Master of Science in Computer Science (MSCS) . His research focuses on the intersection of constraint programming, program synthesis, analysis, and verification, with recent work aiming to make formal methods tools more accessible through automated reasoning. Ruben earned his Ph.D. with honors from the Technical University of Lisbon, Portugal (2013) , followed by postdoctoral research at the University of Oxford (2014-2015) and UT Austin (2015-2017) . Research Interests : Ruben's work bridges constraint programming and program synthesis , with applications in software verification , optimization , and automated reasoning . He has developed award-winning tools like Open-WBO , a modular MaxSAT solver that has won gold medals in international competitions. His publications span top-tier venues such as POPL , PLDI , FSE , SAT , and CP , often addressing real-world challenges from program analysis to network security. Scientific Awards include: Distinguished Paper Award at PLDI 2018 Distinguished Paper Award at FSE 2021 Distinguished Paper Award at SAT 2022 Gold medals for Open-WBO in MaxSAT competitions Teaching & Advising : Ruben mentors Ph.D., Master’s, and undergraduate students in research projects related to program synthesis, formal methods, and constraint solving. He teaches courses such as Bug Catching: Automated Program Verification and Advanced Topics in Logic: Automated Reasoning and Satisfiability , emphasizing hands-on experience with tools like Why3. His advising spans topics from AI-driven program repair to network protocol verification , fostering collaboration across disciplines.

• Embedded Systems
• Software Verification and Validation
• Model Checking
• +5 more

Stefan Kowalewski serves as Professor of Embedded Software at RWTH Aachen University, leading the Chair of Embedded Software (Informatik 11) within the Department of Computer Science. His research spans critical domains including medical cyber-physical systems, automotive software, and industrial automation, with over 150 publications demonstrating sustained scholarly impact. Professor Kowalewski's work focuses on three interconnected research pillars: Embedded Systems Verification: Pioneering model checking techniques for PLC code, particularly addressing state space challenges in GRAFCET-based specifications Medical Cyber-Physical Systems: Developing safety-critical software for mechanical ventilation, extracorporeal membrane oxygenation, and ARDS diagnosis systems with strong clinical collaborations Automotive Software: Creating verification frameworks and safety architectures for automated vehicles through projects like UNICARagil Recent publications reveal an increasing integration of AI techniques with traditional verification methods, particularly for medical applications involving neonatal care and critical respiratory support. His 2024-2025 work shows particular emphasis on timing isolation in vehicle communication systems, middleware performance evaluation, and robust AI models for medical diagnosis. Professor Kowalewski maintains active collaborations with RWTH Aachen University Hospital's medical departments and automotive industry partners. His laboratory operates specialized facilities including the Cyber-Physical Mobility Lab for vehicle research and in-vivo testing setups for medical device validation. He has supervised numerous doctoral candidates, with recent students focusing on topics like ARDS classification algorithms, GRAFCET verification techniques, and safety architectures for software-defined vehicles. His educational contributions include developing remote teaching platforms for cyber-physical systems education.

Simon RothöhlerView profile

Professor

• Visual Culture
• Media Studies
• Digital Humanities
• +4 more

Simon Rothöhler is a Professor of Visual Culture and Media Infrastructure at the Ruhr University Bochum , affiliated with the Institute for Media Studies . His research examines the intersection of digital media, archival systems, and infrastructural aesthetics. Chair: Visual Culture and Media Infrastructure Contact: simon.rothoehler@rub.de Research Focus Rothöhler investigates: Virtual image archives and their historical contexts Techno-aesthetics of digital systems Forensic visualization practices Media infrastructure studies Operational images in computational environments Epistemological dimensions of digital imagery Publications & Projects Active in publishing and organizing workshops, Rothöhler collaborates on projects like the Virtual Image Archives book and SFB-Workshops on imagelessness and virtual collections. His work bridges media theory with practical digital archiving challenges. Teaching He contributes to academic programs through lectures and supervision in media studies and digital humanities, focusing on contemporary media aesthetics and infrastructure.

Aslan AskarovView profile

Associate Professor

• Computer Security
• Programming Languages
• Information Flow Security
• +4 more

Aslan Askarov is an Associate Professor in the Department of Computer Science at Aarhus University, where he leads research in computer security and programming languages. He is a member of the Logic and Semantics Group and maintains an active research program with several ongoing projects. Dr. Askarov's research interests span computer security and privacy, with a focus on foundations, information-flow, covert channels, metadata privacy, and formal methods for security. He also works extensively in programming languages, particularly in semantics, design, type systems, and program analysis. His work bridges theoretical foundations with practical security applications, particularly in web and mobile security contexts. His active projects include Troupe, a programming language for concurrent and distributed programming with dynamic information flow control, and DenIM, a protocol for secure instant messaging with metadata privacy. These projects reflect his commitment to developing practical security solutions grounded in formal methods. Dr. Askarov has published extensively in top security and programming languages venues, with recent work focusing on metadata privacy in instant messaging, separation logic for virtual machine security, and oblivious execution techniques for reactive programs. His research demonstrates a consistent pattern of addressing fundamental security challenges through formal methods and language-based approaches. CSF 2026 ESOP 2026 PLDI 2025 CSF 2025 CSF 2022 CSF 2021 CSF 2020 PriSC 2020 Nordsec 2019 (co-chair) POST 2019 Euro S&P 2018 PLAS 2017 FCS 2017 (co-chair) HotSpot 2017 FCS 2016 (co-chair) CSF 2016 ESSOS 2015 FCS-FCC 2014 ARES 2014 FCS 2013 ARES 2013 PLAS 2013 ARES 2012 PLAS 2011 (co-chair) ISARCS 2010 PLAS 2009 VODCA 2008 Dr. Askarov teaches advanced courses in computer science, including Compilers in Fall 2024 and Language-Based Security in Spring 2024. He is actively recruiting PhD students and postdocs to work in the areas of Programming Languages and Computer Security, demonstrating his ongoing commitment to mentoring the next generation of researchers.

Jürgen CitoView profile

Associate Professor

• Software Engineering
• Explainable AI
• Performance Engineering
• +3 more

Jürgen Cito is an Associate Professor with tenure at Vienna University of Technology (TU Wien), specializing in software engineering, explainable AI, and performance engineering. He leads research at the IPA Lab (as indicated by his personal website) and maintains a visiting researcher position at Google. His academic journey began with joining TU Wien as an Assistant Professor in Spring 2020, with promotion to Associate Professor announced in April 2024. His research interests span multiple critical areas of modern software development, with particular focus on developer experience, program comprehension, and the intersection of AI with software engineering practices. His work bridges theoretical foundations with practical industrial applications, as evidenced by collaborations with major technology companies. Analysis of his recent publications reveals a strong emphasis on practical tools and methodologies that enhance software quality, performance, and security. His research trajectory shows increasing focus on explainable AI techniques applied to software engineering problems, performance prediction from source code, and automated security testing approaches that leverage large language models. best teaching award for distance learning for Web Engineering (2020) Cito actively contributes to the software engineering community through numerous conference committee roles, including program committee positions at ASE, ICSE, ESEC/FSE, and other major venues. His lab appears to focus on developer tools, program analysis, and AI-assisted software engineering, with connections to both academic and industrial research environments.

Shin YooView profile

Professor

• Software Testing
• Debugging
• Search-based Software Engineering
• +7 more

Shin Yoo is a tenured Full Professor in the School of Computing at Korea Advanced Institute of Science and Technology (KAIST), where he leads the Computational Intelligence for Software Engineering (COINSE) research group. He received his PhD from King's College London in 2009 under the supervision of Prof. Mark Harman. Currently, he serves as the General Chair for ASE 2025, which will be held in Seoul, Korea. Professor Yoo earned his PhD in Computer Science from King's College London (2009), following an MSc in Software Engineering with Distinction from the same institution (2006). His academic journey includes positions as Tenured Associate Professor (2021-2025), Associate Professor (2018-2021), and Assistant Professor (2015-2018) at KAIST, as well as Lecturer and Research Associate positions at University College London and King's College London. His research focuses on the intersection of software engineering and artificial intelligence, particularly in search-based software engineering, software testing, automated debugging, SE4AI (Software Engineering for AI), and AI4SE (AI for Software Engineering). Professor Yoo's work bridges theoretical foundations with practical applications, developing innovative techniques for fault localization, test case generation, and debugging using machine learning and genetic programming approaches. His research has significant implications for improving software reliability and development efficiency in both traditional software systems and AI-powered applications. Professor Yoo's recent publications demonstrate a clear trend toward leveraging large language models and deep learning techniques for software engineering tasks. His work spans fault localization, automated debugging, GUI testing, and program analysis, with increasing focus on the challenges and opportunities presented by AI systems. His research shows a consistent evolution from traditional search-based software engineering to AI/ML-enhanced approaches, reflecting the broader trends in the field. ACM SIGEVO HUMIES Silver Medal (2017) for human competitive application of genetic programming to fault localization research IEEE TCSE Most Influential Paper Award (ICST 2024) for work on mutation-based fault localization Professor Yoo has supervised five PhD students to completion, with his former students now holding positions as assistant professors, post-doctoral researchers, and software engineers at institutions including Kyoungpook National University, Max-Planck Institute Security & Privacy, Università della Svizzera Italiana, Roku Korea, and NUS. He currently serves as an associate editor for the Journal of Empirical Software Engineering and ACM Transactions on Software Engineering and Methodology, and has held significant leadership roles in major software engineering conferences including Program Co-chair for SSBSE (2014), ICST (2018), and ICSE NIER track (2020), General Chair for SSBSE (2022), and Testing & Analysis Area Chair for ICSE (2024). As leader of the Computational Intelligence for Software Engineering (COINSE) group at KAIST, Professor Yoo directs research that combines computational intelligence techniques with software engineering challenges. The group focuses on developing novel approaches to software testing, debugging, and analysis using search-based and AI-driven methods. Their work spans both theoretical foundations and practical implementations, with strong connections to industry challenges and applications.

• Natural Language Processing
• Large Language Models
• Soft Robotics
• +4 more

Peiyi Wang is an Assistant Professor at Peking University's School of Electronics Engineering and Computer Science, Institute for Artificial Intelligence. With strong research output spanning both natural language processing and robotics, Wang maintains significant collaborations with Southern University of Science and Technology and National University of Singapore, particularly in soft robotics research with Professor Cecilia Laschi. Additionally, Wang is actively involved with DeepSeek-AI, contributing to several major language model initiatives including DeepSeek-R1 and DeepSeek-V2. Peking University, School of EECS, Institute for Artificial Intelligence (Primary) Southern University of Science and Technology (Collaborative) National University of Singapore (Collaborative) DeepSeek-AI Research Organization Dr. Wang's research spans two primary domains with significant intersection points. In natural language processing, Wang focuses on large language model reasoning capabilities, mathematical verification, uncertainty estimation, and preference alignment. The robotics work centers on soft robotics, particularly origami-inspired designs, strain-based modeling, and control systems for continuum manipulators. These domains converge in Wang's work on vision-language models, embodied AI, and multimodal reasoning systems. Recent work demonstrates particular innovation in mathematical reasoning verification (Math-Shepherd), soft robotic control systems, and red teaming frameworks for language model safety. Wang's publication record shows remarkable productivity, with over 40 publications between 2021-2025 across top-tier venues including ACL, EMNLP, CVPR, and IEEE Transactions on Robotics. The work demonstrates consistent progression from foundational NLP tasks to increasingly sophisticated multimodal and reasoning systems. The most recent publications (2024-2025) show particular emphasis on mathematical reasoning verification, soft robotics control, and language model safety evaluation. While specific awards aren't documented in the provided materials, Wang's work has clearly gained significant recognition through acceptance at top-tier conferences and collaborations with leading researchers in both NLP and robotics fields. Wang's research demonstrates strong interdisciplinary connections, bridging theoretical NLP work with practical robotics applications. The work with DeepSeek-AI suggests active industry collaboration while maintaining strong academic research output. Current research directions appear focused on improving language model reasoning reliability while developing novel soft robotic systems that can interact safely and effectively with complex environments.

Jens PalsbergView profile

Professor

• Programming Languages
• Quantum Computing
• Software Engineering
• +3 more

Jens Palsberg is a Professor and former Department Chair of Computer Science at the University of California, Los Angeles (UCLA), where he currently serves as Director of the UCLA-Amazon Science Hub for Humanity and Artificial Intelligence and co-director of UCLA's quantum research center. He chairs ACM SIGPLAN and is a member of the ACM Council. His research spans programming languages, software engineering, quantum computing, compilers, embedded systems, and information security. Palsberg has authored over 80 technical papers, co-authored the book Object-Oriented Type Systems , and revised Appel's textbook on Modern Compiler Implementation in Java . His recent work shows a significant shift toward quantum computing, including compiler techniques and program analysis for quantum systems. Analysis of his recent publications reveals a clear transition from traditional programming language research to quantum computing, with nearly half of his 2022-2024 publications focusing on quantum topics while maintaining strong work in software engineering and programming languages. His quantum research particularly emphasizes compiler optimization, abstract interpretation, and circuit analysis. ACM SIGPLAN Distinguished Service Award (2012) UCLA teaching award for quantum computing courses (2023) National Science Foundation CAREER and ITR awards Purdue University Faculty Scholar award IBM Faculty Award Okawa Foundation research award Palsberg has served in numerous leadership roles including general chair of POPL, conference chair of LICS, and vice chair of ACM SIGBED. His research has been supported by DARPA, Intel, British Telecom, and the National Science Foundation. He was instrumental in establishing UCLA's Masters degree in quantum science and has mentored numerous students through his legendary proof sessions. He leads a research group of over 30 professors in UCLA's quantum research center and maintains active collaborations across academia and industry, particularly with Amazon through the UCLA-Amazon Science Hub.

• Algorithms for Big Data
• Parallel Computing
• External-Memory Algorithms
• +5 more

Ulrich Meyer is a Professor at the Institute for Computer Science at Goethe University Frankfurt. He serves as a prominent researcher in algorithms for big data, with extensive contributions to parallel and external-memory graph algorithms. His work spans theoretical foundations and practical implementations for processing large-scale data sets. Spokesperson of the DFG priority program (SPP 1736) on Algorithms for Big Data in Germany SEA23 Symposium on Experimental Algorithms, Steering Committee Chair ALENEX23 Algorithm Engineering and Experiments, Program Committee Member Professor Meyer's research interests focus on the theoretical and experimental aspects of processing large data sets on advanced computational models. His work particularly emphasizes parallel and external-memory graph algorithms, with recent focus on efficient large-scale network generation according to various stochastic models. His research has produced significant contributions including the parallel Delta-Stepping algorithm (which received the ESA Test of Time Award in 2019) and the first BFS approach with sublinear I/O. He has also explored more specialized topics like energy-efficient sorting (with records in the JouleSort competition 2009/10 and the Germany Land of Ideas Award) and fragile computing (which earned him a best-paper award at ESA 2019). His recent publications demonstrate a strong focus on graph algorithms, network generation, and parallel computing techniques. The research trends show consistent advancement in scalable algorithms for massive graphs, with particular emphasis on efficient sampling methods, shortcutting techniques, and communication-free distributed approaches. His work bridges theoretical computer science with practical engineering considerations for real-world big data applications. ESA Test of Time Award 2019 for Parallel Delta-Stepping algorithm Records in the JouleSort competition 2009/10 Germany Land of Ideas Award Best-paper award at ESA 2019 for fragile computing research Professor Meyer has made substantial contributions to the academic community through his leadership in the DFG priority program on Algorithms for Big Data, which has fostered significant research collaborations across Germany. His extensive publication record in top venues demonstrates sustained research productivity and impact in the algorithms community. While specific grant details aren't provided in the text, his role as spokesperson for a major DFG priority program indicates substantial research funding and leadership responsibilities. His work appears to be conducted within collaborative research environments focused on algorithm engineering and experimental evaluation. His research appears to be conducted within the Institute for Computer Science at Goethe University Frankfurt, likely involving collaborations with other researchers in the Algorithms for Big Data priority program. The extensive list of co-authored publications suggests active participation in research teams focused on parallel algorithms, graph processing, and network generation.

Peter SewellView profile

Professor

• Concurrency
• Programming Languages
• Formal Methods
• +5 more

Peter Sewell is Professor of Computer Science at the University of Cambridge Computer Laboratory, where he builds rigorous foundations for real-world computer systems to enhance robustness, security, and formal verification of hardware-software interactions. His educational background includes undergraduate studies at the University of Cambridge and University of Oxford, followed by a PhD from the University of Edinburgh in 1995 under Robin Milner's supervision. Professor Sewell's research focuses on concurrency models (x86, ARM, Power, C/C++11), verified compilation, formal semantics for C/linking/filesystems/TLS, and applied semantics tools. He pioneers executable ISA specifications through projects like Sail and Cerberus, addressing relaxed-memory concurrency and capability-based security architectures. His 2020-2026 publications reveal a clear trajectory toward formal verification of hardware security properties, with increasing emphasis on capability systems (Arm Morello, CHERI) and real-world applicability of concurrency models across ARM, RISC-V, and MIPS architectures. Scientific recognition: Royal Society University Research Fellowship (1999-2007) He leads major research initiatives in systems security formalization, supported by Cambridge positions and collaborative projects with industry partners. His work bridges theoretical formal methods and practical systems engineering through executable semantics frameworks. As a core member of Cambridge's Systems Research Group, he directs projects including Sail (ISA semantics), Cerberus (C semantics), and verification frameworks for capability architectures, fostering interdisciplinary collaboration across hardware and software security domains.

• Mathematical Logic
• Philosophical Logic
• Philosophy of Mathematics
• +3 more

Prof. Dr. Reinhard Kahle is a faculty member at the University of Tübingen in the Faculty of Philosophy . He holds the academic rank of Professor and his research focuses on Mathematical Logic , Philosophical Logic , Philosophy of Mathematics , and History of Logic . He also investigates the Societal Relevance of Science and Philosophy of Language . Education : Studium der Mathematik, Philosophie und Informatik in Göttingen, Zürich und München (1987-1993) Diplom in Mathematik, LMU München (1993) Promotion in Informatik, Universität Bern (1997) Habilitation in Informatik, Universität Tübingen (2007) Habilitation in Mathematik, Universidade de Coimbra (2008) Awards : Carl Friedrich von Weizsäcker-Stiftungsprofessor für Theorie und Geschichte der Wissenschaften, University of Tübingen (2019) Publications : Advances in Proof Theory (2016, co-editor) Gentzen's Centenary: The quest for consistency (2015, co-editor) Over 40 peer-reviewed journal articles and book chapters focusing on proof theory, mathematical logic, and philosophical implications of formal systems

Lars GrunskeView profile

Professor

• Software Engineering
• Formal Methods
• Model Checking
• +5 more

Lars Grunske is a Professor at the Department of Computer Science, Faculty of Mathematics and Natural Sciences, Humboldt University of Berlin. His research focuses on software and systems engineering, safety-critical systems, and software evolution. Department: Computer Science University: Humboldt University of Berlin Academic Rank: Professor His work spans automated software analysis, probabilistic model checking, and formal methods for complex systems. Key collaborations include researchers from Swinburne University, University of Hull, and University of Queensland. Recent publications address research software engineering, program repair, and explainability in cyberphysical systems. Professional roles include leadership in examination boards and program committees for conferences like ICSE and ASE. Contact info: Email: grunskel@hu-berlin.de Phone: +49 30 2093-41142 Address: Unter den Linden 6, Berlin

Théo WinterhalterView profile

Researcher

• Formal Methods
• Type Theory
• Proof Assistants
• +3 more

Dr. Théo Winterhalter is a researcher at the Deducteam within INRIA Saclay and the Laboratoire de Méthodes Formelles (LMF) at École Normale Supérieure Paris-Saclay. Previously, he held a postdoctoral position at the Max Planck Institute for Security and Privacy (MPI-SP) in Bochum, Germany. He completed his PhD in computer science at the University of Nantes under the supervision of Nicolas Tabareau and Matthieu Sozeau, focusing on the formalization and meta-theory of type theory. His research centers on proof assistants, particularly Coq, and involves advancing formal methods for security, type systems, and dependent type theory. Winterhalter's work includes contributions to the MetaCoq project, enabling meta-programming and formal reasoning about Coq itself. He is also involved in developing verified cryptographic frameworks like SSProve and SecRef*, ensuring secure integration of verified and unverified code. His educational background includes a PhD in type theory and prior work in cryptographic algorithms, such as randomized scalar multiplication. He actively participates in academic communities, serving on program committees for ICFP, TYPES, and POPL. His teaching includes co-teaching the MPRI course on proof assistants with Yannick Forster. Supervision activities include PhD student Yann Leray and multiple interns focusing on Coq extensions and formal verification.

Michael SammlerView profile

Assistant Professor

• Formal Verification
• Programming Languages
• Systems Programming
• +3 more

Michael Sammler is an Assistant Professor leading the Programming Languages and Verification Group at the Institute of Science and Technology Austria (ISTA). He holds a PhD from the Max Planck Institute for Software Systems (MPI-SWS) and was a postdoctoral researcher at ETH Zürich. His research focuses on formal verification of low-level systems code, combining foundational proofs with automation. Key projects include RefinedC (C verification), Islaris (assembly code verification), and DimSum (multi-language interoperability). Education: PhD at MPI-SWS/Saarland Informatics Campus, postdoc at ETH Zürich. Research interests emphasize tool development for safety-critical systems, including Rust verification (RefinedRust), OCaml/C interoperability (Melocoton), and decentralized multi-language semantics (DimSum). Awards: Runner-Up for Informatics Europe 2024 Best Dissertation Award, Dr. Eduard Martin Prize, Distinguished Paper Awards at PLDI/POPL/USENIX, and Google PhD Fellowship. Labs/Teams: Programming Languages and Verification Group at ISTA, collaborations with MPI-SWS and international researchers. His work bridges foundational theory with practical tools for industry-relevant verification challenges.

• Combinatorial Optimization
• Integer Programming
• Quadratic Programming
• +4 more

Cédric Soutil is a Researcher at the Conservatoire National des Arts et Métiers (CNAM) , affiliated with the CEDRIC Laboratory. His work spans combinatorial optimization , integer programming , quadratic programming , and algorithm design , with a focus on solving complex optimization problems in scheduling and graph theory. Recent publications highlight his expertise in non-separable and non-convex quadratic integer programming , knapsack problems , and online computation . His research trends emphasize mathematical reformulations , upper bound algorithms , and optimization models for real-world applications like horse race scheduling and hydrogen production . He has collaborated extensively with researchers such as A. Houdayer , D. Quadri , and P. Tolla , contributing to over two decades of academic output in operations research and combinatorial optimization .