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Sylvain BoulméView profile

Associate Professor

• Formal Verification
• Formal Methods
• Programming Language Semantics
• +7 more

Sylvain Boulmé is an Associate Professor (Maître de Conférences) at Grenoble Institute of Technology (Grenoble-INP), France, and a member of the Verimag research laboratory at Université Grenoble Alpes. His research lies at the intersection of formal verification, programming language semantics, and verified compilation, with a strong emphasis on machine-checked proofs using the Coq proof assistant. Research Interests: Formal verification of software and hardware systems Semantics of programming languages Verified compilation (e.g., CompCert and Chamois CompCert) Abstract interpretation and refinement calculi Type theory and dependent types Certification of SAT solvers and verification tools His recent work includes formally verified defensive programming techniques, certified compilation optimizations, and Coq-verified SAT solver certification tools like SatAns-Cert. He actively contributes to open-source projects and collaborates with researchers such as David Monniaux and Thomas Vandendorpe. Teaching & Outreach: He teaches courses at Ensimag (École nationale supérieure d'informatique et de mathématiques appliquées de Grenoble) covering topics like programming languages, compilation, code analysis for safety and security, and formal verification. He also engages in public communication, such as his 2024 Interstices article on building reliable software. Contact & Affiliation: Verimag Laboratory, Université Grenoble Alpes 150 place du torrent, 38401 St Martin d'Hères, France Email: Sylvain.Boulme@univ-grenoble-alpes.fr

• Query Optimization
• Database Systems
• Parallel Heuristic Algorithms
• +3 more

Leonard Wörteler is a Researcher at the University of Konstanz's Department of Computer and Information Science, affiliated with the Database and Information Systems group. He joined as a PhD student in 2015 after completing his Bachelor's (2012) and Master's (2015) in Computer and Information Science at the same institution. His research focuses on query optimization, including architectures, parallel heuristic algorithms, and non-relational databases. He has contributed to teaching, including courses on database systems and computer science fundamentals. His research explores advanced optimization techniques, such as neural language models for cardinality estimation and landmark-based algorithms for graph databases. He has published in venues like IDA, DBPL, and SIGRAD, addressing topics ranging from XQuery optimization to real-time transportation visualization. Wörteler's work emphasizes practical implementations, such as optimizing Neo4j's performance through landmark embedding. His contributions bridge theoretical optimization frameworks with real-world applications in databases and data mining.

Xingfu WuView profile

Research Professor

• High-performance computing
• Performance modeling and analysis
• Energy and power modeling and analysis

Xingfu Wu is a Research Professor of Computer Science affiliated with Argonne National Laboratory (ANL). He holds a Ph.D. in Computer Science from Beijing University of Aeronautics and Astronautics and M.S. and B.S. degrees in Mathematics from Beijing Normal University. His research focuses on high-performance computing, performance modeling and analysis, and energy-efficient computing. Education: Ph.D. in Computer Science, Beijing University of Aeronautics and Astronautics, Beijing, China M.S. in Mathematics, Beijing Normal University, Beijing, China B.S. in Mathematics, Beijing Normal University, Beijing, China Research Interests: Xingfu Wu's research is centered around high-performance computing, performance modeling and analysis, and energy and power modeling. His work emphasizes optimizing parallel systems, developing frameworks for performance prediction (e.g., MuMMI), and enhancing energy efficiency in high-performance computing environments. Scientific Awards: Best Paper Award, 14th IEEE International Conference on Computational Science and Engineering (CSE-2011), 2011 Second Place, Beijing Science and Technology Advancement Awards, 1997 Labs/Teams: Wu contributes to research at Argonne National Laboratory, particularly through initiatives like the MuMMI framework for performance modeling and analysis.

J. Todd McDonaldView profile

Professor

• Software Protection and Assurance
• Secure Software Engineering
• Anomaly Detection
• +5 more

Dr. J. Todd McDonald is a Professor of Computer Science at the University of South Alabama's School of Computing. He serves as Director of the Center for Forensics, Information Technology, and Security (CFITS) and has held academic roles including Associate Professor (2011-2014) and Assistant Professor at the Air Force Institute of Technology (2006-2009). His education includes a Ph.D. in Computer Science from Florida State University (2006), MS in Computer Engineering from AFIT (2000), MBA from University of Phoenix (1996), and BS from the U.S. Air Force Academy (1990). Research Interests: Focus on software/hardware protection (obfuscation, watermarking), malware analysis, secure embedded systems, and cybersecurity. Notable projects include Phase-Space Analysis for seizure prediction, CAN network security, and development of the Program Encryption Toolkit (PET) for circuit protection research. Publications: Over 80 peer-reviewed articles in journals/conferences (e.g., IEEE, ACM) covering topics like side-channel analysis, malware detection, and cybersecurity frameworks. Recent work includes 2025 research on embedded system anomaly detection and 2021 studies in Android malware classification. Awarded Best Poster (IEEE HOST 2016) and Best Paper (CISR 2014) Managed NSF Scholarship for Service program ($6M+ funding) Advised 20+ graduate students in cybersecurity and software protection Led USA's DayZero Cyber Defense Competition teams (5th NCCDC 2017) Labs/Teams: SPERG (System Protection & Exploitation Research Group), CFITS directorship, and leadership in SSPREW workshop series. Active in developing cybersecurity education curricula and industry partnerships.

• Algorithm Design
• Automated Assessment Tools
• Educational Data Mining
• +2 more

Ruben Acuña is an Assistant Teaching Professor in the School of Computing and Augmented Intelligence at Arizona State University (ASU). He holds a Master of Science in Computer Science from ASU (2015). His primary research focuses on algorithm design, automated assessment tools, educational data mining, and compiler technologies. He has been actively involved in teaching core courses such as data structures and algorithms (SER 222), operating systems (SER 334), and special topics courses like honors thesis and practicum (SER 493/580). Acuña’s research emphasizes improving educational outcomes through advanced assessment systems and exploring compiler optimizations. His teaching spans multiple semesters, reflecting his commitment to foundational computer science education. Though no specific awards are highlighted in the text, his contributions to curriculum development and automated grading systems demonstrate impact in both pedagogy and technical innovation. Academic advising and grants are not explicitly mentioned, but his extensive course load and focus on educational technology suggest active engagement in student mentorship. No specific lab affiliations are noted, though his work aligns with computational and educational technology initiatives within the School of Computing.

• Embedded Systems
• Internet of Things (IoT)
• Machine Learning
• +3 more

Bruce Belson is a Lecturer in the Department of Engineering and Related Technologies at James Cook University. He holds a PhD in Engineering and Related Technologies and specializes in embedded systems design, IoT applications, and asynchronous programming techniques. Teaching Roles: Embedded Systems Design (Lecturer/Tutor: 2021-2025) Design Project (Lecturer/Tutor: 2023-2024) Digital Logic and Embedded Systems (Lecturer: 2025) Special Study A (Lecturer: 2024) Research Interests: Optimizing memory access patterns in edge devices for machine learning inference Coroutine implementation on microcontrollers and IoT systems Vibration analysis for mining conveyor belt systems Development of digital insurance verification frameworks Key Projects: "Vibration analysis of mining industry conveyor belt systems" (2019-2020) "Development of digital apps for Fijian homeowner insurance" (2019)

• Cloud Computing
• High-Performance Computing (HPC)
• Energy-Efficient Systems
• +4 more

Ivona Brandić is a University Professor for High Performance Computing Systems at TU Wien's Institute of Software Engineering and Interactive Systems. Born in Gradačac, Bosnia and Herzegovina, she moved to Austria in 1992 as a refugee during the Bosnian War. She earned a master's degree (2002) and doctorate (2007) in business computer science from TU Wien and completed her habilitation in applied computer science there in 2013. Her career includes roles as an assistant professor (University of Vienna, 2002–2007) and postdoctoral researcher (University of Melbourne, 2008). She transitioned to a tenure-track position at TU Wien in 2014 and became a full professor in 2016. Brandić’s research focuses on cloud computing, energy-efficient ultra-scale systems, and hybrid quantum-classical computing. She has been recognized with the MiA Award (2011), the Austrian Science Fund's Start-Preis (2015), and membership in the Austrian Academy of Sciences' Young Academy (2016). Her work emphasizes sustainable computing, edge systems, and optimizing resource management for distributed applications. Education: Bachelor's degree in Business Informatics (University of Vienna/TU Wien) Master's in Business Computer Science (University of Vienna, 2002) PhD in Applied Computer Science (TU Wien, 2007) Habilitation in Practical Computer Science (TU Wien, 2013) Research Interests: Brandić’s work spans cloud computing, energy efficiency in HPC systems, edge computing, and quantum-classical hybrid systems. She explores autonomic resource management, distributed system resilience, and sustainability in ultra-scale infrastructures. Her projects often address real-world applications like drug design, environmental monitoring, and smart energy grids. Publications: Her 2009 paper Cloud Computing and Emerging IT Platforms is a seminal work in the field. Recent publications focus on quantum-edge integration, energy optimization in AI models, and adaptive edge analytics frameworks. These contributions highlight trends toward sustainable, distributed, and hybrid computational paradigms. Awards: 2011: MiA Award for distinguished contributions by international backgrounds 2015: Austrian Science Fund’s Start Prize 2016: Austrian Academy of Sciences Young Academy Membership Advising & Grants: Brandić leads research groups and has secured grants for projects like NESSUS (energy-efficient cloud systems) and CHIST-ERA’s SDCDN (distributed networks). She mentors students in HPC, edge computing, and quantum systems. Advised topics include workload scheduling, fault tolerance, and energy-aware algorithms. Labs & Teams: She directs research on autonomic cloud management, edge intelligence frameworks (e.g., Sea-LEAP, FRESCO), and quantum-classical workflow systems (RIGOLETTO). Her teams collaborate internationally, integrating academia and industry for scalable, sustainable solutions.

• Artificial Intelligence
• Software Development
• Large Language Models
• +4 more

Kai-Kristian Kemell is a Research Fellow in the Computing Sciences department, focusing on interdisciplinary research at the intersection of Artificial Intelligence, Software Engineering, and Ethical AI. His work explores practical applications of Large Language Models (LLMs), autonomous agents in software development, and regulatory frameworks like the EU AI Act. Research Interests : His primary areas include AI-driven software development tools, ethical implementation of AI systems, multi-agent systems for code refactoring, and systematic literature reviews on trustworthiness in LLMs. He investigates how LLMs can automate tasks like microservice generation from API definitions and assist early-stage software startups through prompt engineering. Collaborations : Active collaborations include projects with researchers like Prof. Petri Abrahamsson, focusing on topics such as RAG systems, AI ethics governance, and hybrid work practices in software engineering. His work bridges theoretical AI concepts with practical industrial applications. Publications : His 2025 publications emphasize autonomous software development agents, EU AI Act critiques, and ethical alignment strategies for LLM-based systems. Earlier work (2023–2024) addresses AI ethics implementation via user stories, hybrid work impacts, and MLOps challenges. Awards : No specific scientific awards mentioned in the provided texts. Grants & Labs : No explicit details on grants or affiliated labs, but his research frequently involves collaborative projects with industry and academic partners.

Marco GuarnieriView profile

Associate Professor

• Security and Privacy
• Program Verification
• Programming Languages
• +3 more

Marco Guarnieri is an Associate Professor at the IMDEA Software Institute in Spain. His research focuses on the design, analysis, and implementation of secure systems, with particular emphasis on security at the hardware-software boundary. His work addresses microarchitectural attacks (e.g., Spectre), secure compilation, hardware verification, and database security. Education PhD in Computer Science, ETH Zurich (2017) MSc in Computer Engineering, Università degli Studi di Bergamo (2012) BSc in Computer Engineering, Università degli Studi di Bergamo (2010) Research Focus Guarnieri's research spans several interconnected areas: Hardware-Software Security: Developing foundations for reasoning about security at the hardware-software boundary Microarchitectural Attacks: Analysis and mitigation of speculative execution attacks Formal Methods: Application of verification techniques to security problems Secure Compilation: Ensuring compiler-generated code maintains security guarantees Database Security: Information flow control and access mechanisms Research Trends His recent publications demonstrate a strong focus on hardware-software co-design for security, with increasing emphasis on formal verification of processor security (especially RISC-V), automated testing of speculation countermeasures, and leakage contract frameworks. His work consistently bridges theoretical foundations with practical implementations. Awards and Honors Best Paper Award at CCS 2024 Distinguished Paper Award at CCS 2023 Distinguished Paper Award at CCS 2022 Best Paper Award at S&P 2021 Research Leadership Guarnieri leads research projects on secure speculation and hardware-software contracts. He actively recruits research interns, PhD students, and postdocs to work on security at the hardware-software interface. His group develops tools like SPECTECTOR for detecting speculative information flows and LeaVe for verifying processor security.

Cristina CifuentesView profile

Adjunct Professor

• Program Analysis
• Secure Languages
• Code Comprehension
• +7 more

Cristina Cifuentes is an Adjunct Professor at the University of Queensland (School of Information Technology and Electrical Engineering) and Queensland University of Technology (School of Electrical Engineering and Computer Science). She serves as Vice President of Software Assurance at Oracle Labs, leading a team focused on large-scale application security and vulnerability detection. PhD in Computer Science (1994) from Queensland University of Technology Chancellor's Outstanding Alumnus (2001) from QUT Her research interests span program analysis , secure languages , and binary translation , with a focus on enterprise systems and commercial applications. Her work includes static analysis tools like Oracle Parfait and cryptographic API misuse detection. Recent publications address secure programming language design (POPL 2020), scalable static analysis (SAS 2021), and malware analysis platforms (ColdPress). These works emphasize code comprehension , vulnerability detection , and automated security frameworks . Scientific Awards LABSCon 2024 Lifetime Achievement Award Mother of Decompilation Chancellor's Outstanding Alumnus (2001) from QUT She actively contributes to academic communities through committee roles (PriSC, SPLASH) and mentoring, particularly in women in STEM . Her impact includes dozens of patents and leading Oracle Labs Australia for 12 years.

David PichardieView profile

Professor

• Formal Methods
• Programming Languages
• Program Verification
• +3 more

David Pichardie is a Professor of Computer Science at ENS Rennes (France) and a Researcher at Meta. He holds a part-time teaching position at ENS Rennes while working on sabbatical leave. His research spans formal methods, programming languages, program verification, software security, and static analysis. He specializes in machine-checked proofs using Coq and abstract interpretation, with significant work on the verified C compiler CompCert. He has served on program committees for SAS, OOPSLA, POPL, and other leading conferences. Research Interests: Formal Methods, Static Analysis, Compiler Verification, Security, Abstract Interpretation, Programming Languages Awards: ERC Consolidator Grant (2018-2021) His recent publications focus on verified JIT compilation, constant-time cryptography, SSA-based compiler optimizations, and concurrency verification. He has contributed to the formal verification of garbage collectors, WCET estimation tools, and information-flow architectures. His work often bridges theoretical formal verification with practical compiler design, emphasizing machine-checked proofs and integration into real-world systems like CompCert. He has mentored students and collaborated on formal verification of Java bytecode, defensive copying policies, and static analysis of self-modifying code. His teaching includes courses on static analysis, formal methods, and algorithms at institutions such as University Rennes 1, INSA engineering school, and ENS Cachan.

Michael FranzView profile

Professor

• Security
• Systems
• Software Engineering
• +3 more

Michael Franz is a Distinguished Professor (academic rank: Professor) in the Department of Computer Science at the Donald Bren School of Information and Computer Sciences, University of California, Irvine, with a courtesy appointment as Professor in Electrical Engineering and Computer Science at the Henry Samueli School of Engineering. He directs UCI's Secure Systems and Software Laboratory and is a Fellow of AAAS, ACM, IEEE, and IFIP. Franz earned his Dr. sc. techn. degree in Computer Science and Dipl. Informatik-Ing. ETH degree from ETH Zurich under advisor Niklaus Wirth. His research pioneers compiler and system-level techniques for software safety and performance, focusing on Security (multivariant execution, code randomization), Systems (JIT compilation, memory management), and Software Engineering (binary recompilation, attack surface reduction). Franz created foundational trace compilation technology adopted in Firefox's JavaScript engine and continues developing practical defenses against real-world exploits. Recent publications reveal escalating integration of machine learning in binary analysis (e.g., StackBERT) and hardware-assisted security (PKRU-Safe), with consistent output in top venues like USENIX Security and EuroSys. His work transitions from theoretical frameworks to deployed solutions, evidenced by patents and industry adoption. Scientific awards include: Fellow of AAAS (2019) Fellow of ACM Fellow of IEEE Inaugural Fellow of IFIP (2019) ACM Charles P. "Chuck" Thacker Breakthrough in Computing Award (2021) Humboldt Research Award (2018) UCI Innovator of the Year Award (2018) Best Paper Award at ACSAC 2024 SIGSOFT Distinguished Paper Award at ESEC/FSE 2023 Best Paper Award at EuroSys 2022 Test of Time Award at Dynamic Languages Symposium (2019) Franz has graduated 40 Ph.D. students as primary advisor and secured over $24 million in federal grants ($16M+ as sole PI), plus $1 million in industry gifts. His advisees hold key roles at Apple, Google, Meta, and Yonsei University, with Dokyung Song becoming an Assistant Professor there. The Secure Systems and Software Laboratory develops survivable execution environments (A8 MVX) and binary transformation tools (BinRec), bridging academic research with real-world impact like Firefox's TraceMonkey engine and compartmental memory management. Current projects focus on distributed multivariant execution and hybrid binary recompilation.

Joseph NearView profile

Associate Professor

• Data Privacy
• Computer Security
• Programming Languages
• +5 more

Joseph Near is an Associate Professor in the Department of Computer Science at the University of Vermont . He is affiliated with the PLAID Lab and the Center for Computer Security and Privacy . His research focuses on differential privacy , secure/verified computation , and programming language design , with applications in machine learning and privacy-preserving analytics . Education Ph.D., Massachusetts Institute of Technology M.S., Massachusetts Institute of Technology B.S., Indiana University His research spans differential privacy , secure computation , and programming language design , with recent work on choreographic programming , privacy-preserving machine learning , and usability of privacy tools . Publications highlight advancements in secure multi-party computation frameworks , compiler verification , and privacy-preserving data analysis . Service and Collaborations Organizer of workshops like TPDP and miniKanren Program Committee member for CCS , USENIX Security , and PETS Students Advised Craig Agricola (PhD) Mako Bates (PhD) Prianka Bhattacharjee (PhD) Onyinye Dibia (PhD) Syed Jafri (PhD) Krystal Maughan (PhD) Ivoline Ngong (PhD) Ratang Sedimo (PhD)

• Bioprocess Engineering
• Nanobiotechnology
• Bioreactor Design
• +4 more

Asst. Prof. Gülizar ÇALIŞKAN BİLGİN is affiliated with the Faculty of Engineering's Genetics and Bioengineering Department at Ege University. Her research focuses on bioprocess optimization, nanobiotechnology, and sustainable applications of microalgae. She holds a B.Sc., M.Sc., and Ph.D. in Bioengineering from Ege University (2011–2020). She has contributed to TÜBİTAK-funded projects on biogenic nanoparticle synthesis and microalgae biotechnology. Education: B.Sc. Bioengineering, Ege University (2011) M.Sc. Bioengineering, Ege University (2014) Ph.D. Bioengineering, Ege University (2020) Research Interests: Dr. Bilgin explores bioreactor design, nanoparticle biosynthesis via microalgae, and machine learning-driven bioprocess optimization. Her work emphasizes sustainability, such as converting food waste into biomaterials and developing eco-friendly nanoparticle synthesis methods. Projects & Grants: She leads a project on sustainable microalgae use and has participated in projects like the TÜBİTAK 1001 initiative. Her research bridges academia and education, including creating learning methodologies for biomaterial development in secondary schools. Labs & Teams: Her research is rooted in the NanoBioprocess and Process Analytical Technology Laboratory, where she developed nanoparticle synthesis techniques during her Ph.D.

Marijn HeuleView profile

Associate Professor

• Satisfiability (SAT) Solving
• Formal Verification
• Combinatorial Mathematics
• +5 more

Marijn Heule is an Associate Professor in the Computer Science Department at Carnegie Mellon University. He received his PhD from Delft University of Technology in the Netherlands. His academic career has been focused on advancing the theory and practice of satisfiability (SAT) solving and its applications. Dr. Heule's research primarily centers on solving hard combinatorial problems in formal verification, number theory, and extremal combinatorics. His work has made significant contributions to both theoretical foundations and practical implementations of SAT solvers. He has developed award-winning SAT solvers, and his preprocessing techniques are incorporated into state-of-the-art SAT solvers used worldwide. His current research focuses on two major challenges: exploiting high-performance computing for SAT solving and validating results from SAT solvers and related tools. Dr. Heule pioneered the "cube-and-conquer" paradigm, a novel parallel SAT solving approach that enables linear time speedups on many hard problems. His first publication on this topic won the best paper award at HVC 2011. He also designed a new proof format with a corresponding fast proof checker for SAT and QBF solvers. This proof logging format has been mandatory for SAT Competitions since 2013, significantly increasing confidence in tool correctness. His work on the Boolean Pythagorean Triples problem, which produced a 200 TB proof that was validated, demonstrated that proof logging and verification is feasible even for the most complex problems. Dr. Heule is one of the editors of the 900+ page "Handbook of Satisfiability," which has become a standard reference in the SAT community. He serves as an Associate Editor of the Journal on Satisfiability, Boolean Modeling and Computation and previously co-chaired the SAT 2015 conference in Austin. Best paper award at HVC 2011 for cube-and-conquer publication Multiple best paper awards/nominations at major conferences including IJCAR, SAT, TACAS Work featured in New York Times, Quanta Magazine, Nature, and other major media outlets Dr. Heule has advised several PhD students including Emre Yolcu, Joseph Reeves, Bernardo Subercaseaux, Cayden Codel, James Gallicchio, and Amar Shah. He has developed important software tools including DRAT-trim (a proof checking utility), QRAT-trim, and implementations of the cube-and-conquer paradigm that have become standard in the SAT solving community.