Find Academic Supervisors

Ruzica PiskacView profile

Professor

• Software Verification
• Security and Applied Cryptography
• Automated Reasoning
• +4 more

Ruzica Piskac is a Professor of Computer Science at Yale University, where she leads the Rigorous Software Engineering (ROSE) group. She has made significant contributions to the fields of software verification, security, automated reasoning, and code synthesis, focusing on improving software reliability and trustworthiness through formal techniques. Dr. Piskac received her PhD from the Swiss Federal Institute of Technology (EPFL) in 2011, where her dissertation won the Patrick Denantes Prize. Prior to joining Yale, she led an independent research group at the Max Planck Institute for Software Systems in Germany (2012-2013). Her research spans several key areas: symbolic execution for Haskell (G2), privacy-preserving formal methods (PPFM), functional reactive synthesis, verification of configuration files, and analysis of software updates. Her work consistently bridges theoretical formal methods with practical applications in real-world systems. Dr. Piskac's recent publications demonstrate a strong trend toward applying formal verification techniques to emerging challenges including large language models, quantum computing security, legal accountability of automated systems, and cyber-physical systems. Her research increasingly intersects with AI, cryptography, and legal domains while maintaining strong foundations in formal methods. Her scientific achievements have been recognized with numerous prestigious awards: Multiple Amazon Research Awards Yale University's Ackerman Award for Teaching and Mentoring Facebook Communications and Networking Award Microsoft Research Award for the Software Engineering Innovation Foundation (SEIF) Patrick Denantes Prize for her PhD dissertation Dr. Piskac has graduated five PhD students, four of whom have gone on to become assistant professors of computer science. She has served as Program Chair of the 37th International Conference on Computer Aided Verification and is on the Steering Committee of the Formal Methods in Computer-Aided Design conference. She leads the Rigorous Software Engineering (ROSE) group at Yale, which focuses on several key projects including: Symbolic Execution Engine for Haskell (G2) Privacy Preserving Formal Methods (PPFM) Functional Reactive Synthesis Verifications for Configuration Files Analysis of Software Updates and Configuration Files

Mary Elizabeth KurzView profile

Associate Professor

• Scheduling
• Metaheuristics
• Industrial Engineering
• +5 more

Mary Elizabeth Kurz is an Associate Professor in the Department of Industrial Engineering at Clemson University's College of Engineering, Computing and Applied Sciences. Her research focuses on scheduling optimization, metaheuristics, and assembly line balancing for complex manufacturing systems. Education: B.S., Systems Engineering, University of Arizona (1995) M.S., Systems Engineering, University of Arizona (1997) Ph.D., Systems and Industrial Engineering, University of Arizona (2001) Research interests include: Development of heuristics and metaheuristics for scheduling Assembly line balancing with ergonomic constraints Flexible flowline scheduling with sequence-dependent setups Application of genetic algorithms and particle swarm optimization Recent work trends show applications in opioid crisis modeling, photolithography scheduling, and automotive configuration management. She has presented at INFORMS and IISE conferences, with special emphasis on multi-objective optimization and real-world industrial constraints. Scientific awards: Third Place Best Paper, ASME Manufacturing Engineering Division (2014) As an INFORMS member and Institute of Industrial Engineers Senior member, she has taught courses in operations research, decision support systems, and metaheuristics. Her work spans both theoretical and applied domains, with a strong focus on manufacturing system efficiency.

Zachary KincaidView profile

Associate Professor

• Program Analysis
• Logic
• Programming Languages
• +7 more

Zachary Kincaid is an Associate Professor in the Department of Computer Science at Princeton University. His research focuses on program analysis , logic , and programming languages , with emphasis on making analysis compositional and robust . PhD, University of Toronto (2016) BSc, Western University Research Interests Dr. Kincaid develops algebraic program analysis frameworks combining symbolic methods with abstract interpretation. His work addresses challenges in: Compositional analysis of concurrent and recursive programs Termination analysis for loops with complex control flow Non-linear numerical invariant generation Strategy synthesis for logical games Parameterized program verification Publication Trends His research output spans program analysis (2024-2010), formal verification (2018-2010), concurrency (2016-2010), and automated synthesis (2013-2012). Recent work (2024) explores polynomial ideals and nonlinear ranking functions , while foundational contributions include vector addition systems and recurrence-based invariants . Scientific Engagement Dr. Kincaid contributes to the academic community through: Program Committee service (PLDI, POPL, CAV, IJCAI, LICS, FMCAD, ESOP, etc.) Co-developing the Duet analyzer for unbounded concurrency Collaborative work with leading researchers (Tom Reps, Azadeh Farzan, Jason Breck) Advising & Grants He advises PhD students and leads research funded by the ONR grant N00014-19-1-2318 . Current advisees include Jake Silverman and Shaowei Zhu, while former student Charlie Murphy (PhD 2023) now holds a postdoctoral position at University of Wisconsin-Madison. Labs & Teams Dr. Kincaid co-developed the Duet program analyzer and contributes to tools like Srk and SimSat . His work integrates SMT solvers (MathSAT, Z3) and mathematical frameworks (rational vector addition systems, recurrence relations) for robust program analysis.

• Boolean Functions
• Horn Formulas
• Computational Complexity
• +7 more

Ondřej Čepek is an Associate Professor at the Department of Theoretical Computer Science and Mathematical Logic, Faculty of Mathematics and Physics, Charles University in Prague. His academic career spans several decades with numerous publications demonstrating his expertise in theoretical computer science, particularly in Boolean logic, computational complexity, and operations research. Čepek's research primarily focuses on Boolean functions, Horn formulas, and computational complexity. His work explores structural properties of logical constructs, minimization techniques, and applications in knowledge representation. He has made significant contributions to understanding satisfiability testing complexity, CNF minimization, and Boolean function representations using interval structures. His research also extends to scheduling problems, particularly just-in-time scheduling with periodic time slots, where he has developed efficient algorithms for multislot scheduling on identical parallel machines and nonpreemptive flowshop scheduling with machine dominance. Analysis of his recent publications reveals a consistent research trajectory from theoretical foundations to practical applications. His work demonstrates expertise in tractable classes of Boolean formulas, knowledge compilation techniques, and the relationship between computational complexity and logical representations. The recurring themes include efficient representations for logical formulas, characterization of tractable problem classes, and development of optimization algorithms for discrete structures. His collaborations with researchers like Petr Kučera, Roman Barták, and Endre Boros have produced influential work in constraint programming and artificial intelligence. Distinguished Paper Award at CP2004 for 'Unary resource constraint with optional activities' While specific details about his advising activities are not provided in available sources, his extensive publication record spanning from 1989 to 2017 suggests substantial involvement in academic mentoring. His numerous collaborations both within Charles University and internationally indicate an active role in the academic community. His research has practical applications in knowledge-based systems, constraint satisfaction problems, and artificial intelligence. Čepek maintains an active research profile with publications continuing through 2017. His recent work has focused on knowledge compilation techniques, recognition of tractable DNFs, and the complexity of CNF minimization. He has also explored applications of Boolean techniques to DNA microarray data analysis, demonstrating the interdisciplinary nature of his research.

• Formal Methods
• Automated Reasoning
• SAT Solving
• +3 more

Adrian Rebola Pardo is a Researcher at the Institute of Computer Engineering (E192-04) within the Faculty of Informatics at TU Wien. His work focuses on formal methods, automated reasoning, and SAT solving, with an emphasis on proof theory and verification. He holds a PhD in Computer Science from TU Wien (2021), where he developed interference-based proof systems for SAT solvers. **Education**: PhD in Computer Science, TU Wien (2021) **Research Interests**: His research centers on advancing SAT solving techniques, proof complexity, and formal verification. Key areas include quantified Boolean formulas, DRAT proof systems, and efficient proof generation. His work intersects computational logic and theoretical computer science, with applications in automated theorem proving and verification frameworks. **Grants & Projects**: LCS Project (2017–2025): Interpolants and Interference BITVECTOR Project (2016–2020): Exploring SAT refutation verification techniques **Advising**: Supervised Jakob Altmanninger's 2019 diploma thesis on SAT proof generation and DRAT checking. **Labs/Teams**: Member of the Formal Methods in Systems Engineering group at TU Wien.

• Knowledge representation and reasoning
• Planning
• Nonmonotonic reasoning
• +2 more

Yannis Dimopoulos is a Professor in the Department of Computer Science at the University of Cyprus. He has previously held research positions at the Max-Planck Institute for Computer Science in Saarbrücken and the University of Freiburg in Germany. He earned his B.Sc. and Ph.D. in Computer Science from the Athens University of Economics and Business. His primary research interests include: Knowledge representation and reasoning Planning Nonmonotonic reasoning Constraint satisfaction Machine learning His recent research, based on publications from 2017 to 2024, focuses on the theoretical and computational aspects of abstract argumentation, particularly control argumentation frameworks, probabilistic extensions, and the integration of argumentation with Boolean networks and negotiation under incomplete information. He has also contributed significantly to Answer Set Programming (ASP) for planning, developing the plasp 3 framework for effective ASP-based planning solutions. His scholarly work appears in top-tier venues such as AAAI, IJCAI, ECAI, KR, AAMAS, and journals like Artificial Intelligence and Autonomous Agents and Multi-Agent Systems. His most frequent collaborators include Pavlos Moraitis, Jean-Guy Mailly, Antonis C. Kakas, and Wolfgang Dvorák. No scientific awards or honors are mentioned in the provided text. Yannis Dimopoulos has advised or collaborated with several researchers, including Jean-Guy Mailly, Pavlos Moraitis, Nabila Hadidi, and Muhammad Adnan Hashmi, though formal student-advisor relationships are not explicitly detailed. His work often involves theoretical and computational modeling, and while specific grants or funding sources are not listed, his sustained publication record suggests active research support. He is actively involved in research teams and collaborations focused on argumentation, multi-agent systems, and automated reasoning, as evidenced by his extensive co-authorship network.

• Boolean Optimization
• Constraint Reasoning
• Satisfiability (SAT) Solving
• +3 more

Matti Järvisalo is a Professor in the Department of Computer Science at the University of Helsinki, Finland, holding the title of Docent and serving as Supervisor for the Doctoral Programme in Computer Science. He is affiliated with the Helsinki Institute for Information Technology (HIIT), a leading collaborative research institute between the University of Helsinki and Aalto University. His research centers on computational logic and constraint-based reasoning, with core expertise in Boolean optimization, SAT/MaxSAT solving, and argumentation frameworks. He develops declarative approaches for combinatorial problems in computational social choice, judgment aggregation, and fair division, emphasizing certified algorithms and preprocessing techniques. His work bridges theoretical computer science with practical implementations in optimization and AI. Recent publications (2024-2025) reveal a strong focus on multi-objective optimization, certified reasoning, and argumentation under incomplete information. Key trends include symmetry-aware core learning for Pseudo-Boolean optimization, Pareto-optimality certification in MaxSAT, and novel algorithms for manipulation analysis in judgment aggregation, demonstrating his leadership in advancing SAT-based AI methods. Professor Järvisalo's significant contributions have been recognized by prestigious awards: IJCAI-JAIR Best Paper Prize (2019) Best Researcher Award from University of Helsinki Department of Computer Science (2011) CP 2017 Distinguished Paper Award ECAI 2016 Runner-Up Best Student Paper Award Honorary Mention at ICCMA 2015 He actively mentors the next generation of researchers and secures major research funding: Supervision: 6 doctoral theses and 6 Master's/Licentiate theses Active Grant: Academy of Finland project 'Next-generation Unsatisfiability-based Declarative Optimization' (2023-2027) Past Projects: 'Symbolic Techniques for Formally Verified and Explainable AI' (2020-2022), 'Declarative Boolean Optimization: Pushing the Envelope' (2019-2023) As a core member of HIIT, he collaborates within Finland's premier information technology research ecosystem, contributing to the institute's mission of advancing fundamental and applied IT research through interdisciplinary teamwork and international partnerships.

Felix Ulrich-OlteanView profile

Lecturer

• Constraint Satisfaction
• Combinatorial Optimization
• Boolean Satisfiability
• +3 more

Dr. Felix Ulrich-Oltean is a Lecturer in the Department of Computer Science at the University of York. His research focuses on constraint satisfaction, combinatorial optimization, boolean satisfiability, and machine learning applied to automated algorithm selection and configuration. He holds a PhD in Computer Science from the University of York (2019–2023), a PGCE in Secondary Mathematics from Leeds Trinity University, and a BSc in Computer Science from the University of York. His recent work emphasizes SAT encoding techniques for pseudo-boolean and linear integer constraints, with contributions to automated tabulation methods in constraint models. Research trends include integrating machine learning for algorithm selection, optimizing constraint satisfaction problem resolution, and developing efficient SAT-based solutions for complex combinatorial problems. No scientific awards or grants are explicitly mentioned in the provided texts. He advises no listed students and has no disclosed lab affiliations. His office is located at CSE/108, and contact is facilitated through a university web form to protect email privacy.

Sylwia StachowiakView profile

Assistant Professor

• Cryptography
• Cryptanalysis
• Network Security
• +3 more

Sylwia Stachowiak serves as an Assistant Professor at SWPS University within the Faculty of Design in Warsaw and the Department of Mathematics and Logic. Holding a Doctor of Engineering degree in information and communication technology, she bridges theoretical computer science with practical security applications through her research and teaching. Her research specializes in formal methods for analyzing computer network security systems, with particular focus on cryptanalysis of symmetric ciphers using computational techniques for solving Boolean satisfiability problems (SAT). This work represents a critical intersection of theoretical mathematics and real-world security solutions, emphasizing rigorous mathematical approaches to vulnerability assessment. Dr. Stachowiak contributed to a significant 2020 National Centre for Research and Development project (POIR.01.01.01-00-0829/18-00) conducted with the Institute of Computer Science of the Polish Academy of Sciences, developing secure communication protocols for the Warsaw Stock Exchange. Her teaching portfolio comprehensively covers foundational computer science subjects including cryptography and number theory, logic and set theory, discrete mathematics, and algorithms and data structures, reflecting her dual expertise in mathematics and computer science.

Johan HåstadView profile

Professor

• Theoretical Computer Science
• Computational Complexity
• Circuit Complexity
• +3 more

Johan Håstad is a Professor at the Department of Mathematics, School of Engineering Sciences, KTH Royal Institute of Technology. His research focuses on theoretical computer science, particularly algorithms, computational complexity, approximation algorithms, and cryptography. He is funded by the Knut and Alice Wallenberg Foundation through project grants and the Wallenberg AI, Autonomous Systems and Software Program (WASP). External Funding: Knut and Alice Wallenberg Foundation, WASP Editorial Roles: Theory of Computing, TheoretiCS Professional Activities: Cyber Defense Center, Royal Swedish Academy of Sciences (former chairman) Research Interests : • Algorithms and Complexity • Circuit Complexity • Approximation Algorithms • Quantum Computing and Cryptography Scientific Awards : Knut and Alice Wallenberg Foundation Support Labs and Teams : • Involved in KTH's Cyber Defense Center • Editor for key journals in theoretical computer science

Yadi ZhongView profile

Assistant Professor

• Applied Cryptography
• Cryptology
• Algebraic Cryptanalysis
• +7 more

Yadi Zhong is an Assistant Professor in the Department of Electrical and Computer Engineering at Auburn University, part of the College of Engineering. He holds both a Ph.D. and a Bachelor of Engineering from the same institution, reflecting a strong academic foundation in electrical and computer engineering disciplines. His research focuses on critical areas in modern cybersecurity and computational logic, including: Applied Cryptography and Cryptology Algebraic Cryptanalysis Privacy-Enhancing Cryptography Boolean Satisfiability (SAT) Solving VLSI Testing and Design for Testability These interests position his work at the intersection of hardware security, formal methods, and cryptographic protocol analysis, contributing to secure and reliable computing systems. While no recent publications are listed in the provided text, the research areas suggest a focus on both theoretical underpinnings and practical applications in secure integrated circuits and privacy-preserving technologies. There are no scientific awards mentioned in the available information. Dr. Zhong advises students within the Electrical and Computer Engineering graduate program, though specific advisees are not listed. There is no mention of externally funded grants or sponsored research projects in the current profile. He is likely involved in research labs related to cybersecurity, hardware security, or VLSI design, though specific lab affiliations are not stated.

Cayden CodelView profile

Researcher

• Programming Languages
• Formal Verification
• Satisfiability (SAT) Solvers
• +3 more

Cayden Codel is a Researcher at Carnegie Mellon University's Computer Science Department , focusing on programming languages and formal verification. His work bridges theoretical logic with practical applications in automated reasoning and constraint solving. Research Interests: Programming Languages, Formal Verification, Satisfiability (SAT) Solvers, Satisfiability Modulo Theories (SMT), Automated Theorem Proving, Machine Learning Institution: Carnegie Mellon University (CMU) His publications emphasize formal verification for logical systems, SMT/SAT solvers , and reinforcement learning applications. Articles from 2024-2019 reveal a trajectory from foundational logic to real-world dataset design (e.g., Minecraft-based AI research). Thesis Advisors: Marijn Heule, Jeremy Avigad Contact: ccodel@andrew.cmu.edu

Richard ChangView profile

Associate Professor

• Computational Complexity Theory
• NP-optimization Problems
• Approximation Algorithms
• +7 more

Richard Chang is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a Ph.D. from Cornell University (1991) and has been affiliated with UMBC since 1991, serving in various roles including tenure-track positions and joint appointments at the University of Maryland Institute for Advanced Computer Studies (1994–2004). His research focuses on computational complexity theory, particularly bounded query classes, NP-optimization problems, approximation algorithms, and relativized complexity. He has authored numerous papers on topics such as query complexity, Boolean hierarchies, and space-bounded computations. Chang's academic contributions include significant work on the theoretical foundations of computational complexity, including studies on the Boolean hierarchy, randomized reductions, and the structure of NP computations. He has secured multiple research grants, including from the National Science Foundation and the National Security Agency. His teaching spans a wide range of computer science courses, from introductory programming to advanced topics like compiler design and automata theory. He actively participates in academic service, serving on departmental, college, and university committees, as well as organizing conferences and reviewing for top journals. His work emphasizes bridging theoretical computer science with practical algorithmic challenges, contributing to both academic discourse and educational excellence.

• Constraint Programming
• Boolean Satisfiability
• Artificial Intelligence
• +5 more

Steve Prestwich is a Lecturer at the School of Computer Science and Information Technology, University College Cork. He specializes in Artificial Intelligence, Data Analytics, and Algorithmics, with research interests spanning constraint programming, Boolean satisfiability, and hybrid search methods. Education: BA (Hons) Mathematics from University of Oxford, MSc and PhD in Computer Science from University of Manchester. Research Focus: His work integrates constraint programming, SAT solving, and metaheuristics for optimization under uncertainty, with applications in inventory control, protein design, and stochastic modeling. Awards: Runner-up, Constraint Modelling Challenge Bronze medal, SAT'05 Solver Competition

• Algorithms
• Constraint Programming
• SAT Solving
• +2 more

Florentina Voboril is a Research Fellow in the Algorithms and Complexity group at Technische Universität Wien. Her research explores how Large Language Models can solve Constraint Programming instances efficiently, with additional focus on SAT-solving and algorithm design. She investigates applications of AI in combinatorial optimization problems and develops innovative approaches to algorithmic challenges. Voboril has developed methods for SAT-based local improvement in string problems and generates streamlining constraints using LLMs. Her work bridges theoretical computer science with practical applications in computational biology and AI-assisted programming.