Find Academic Supervisors

Thomas W. RepsView profile

Professor

• Program Analysis
• Abstract Interpretation
• Model Checking
• +4 more

Thomas W. Reps is the J. Barkley Rosser Professor & Rajiv and Ritu Batra Chair Emeritus at the University of Wisconsin-Madison , where he has been a faculty member since 1985. He is also President of GrammaTech, Inc., and a co-founder of the company. Education: Ph.D. in Computer Science from Cornell University (1982), winner of the 1983 ACM Doctoral Dissertation Award. Reps’s research spans program analysis , abstract interpretation , model checking , and computer security . His recent work focuses on quantum computing verification , probabilistic program analysis , and symbolic methods for static analysis . His publications (over 225) include foundational contributions to program slicing (1988 paper with Horwitz and Binkley, cited >1,780 times), machine-code analysis (ETAPS Best-Paper Awards in 2004 and 2008), and programming environments (co-author of The Synthesizer Generator ). Key awards include the ACM SIGPLAN Programming Languages Achievement Award (2017) , Guggenheim and Packard Fellowships , and ACM Fellow (2005) . Students: Mentored award-winning graduates like Akash Lal (SIGPLAN Outstanding Dissertation) and Venkatesh Srinivasan (Outstanding Graduate Student Research Award).

Thomas WiesView profile

Professor

• Program Analysis
• Verification
• Automated Deduction
• +4 more

Thomas Wies is a Professor of Computer Science at the Courant Institute of Mathematical Sciences, New York University, and Chair of the Computer Science Department. He is a member of the Analysis of Computer Systems Group and has a personal website. Affiliation: New York University Research Focus: Program Analysis, Verification, Automated Deduction, Concurrency Teaching: Principles of Programming Languages (undergraduate), Programming Languages (graduate), Rigorous Software Development Research Interests: His work centers on program analysis, verification of concurrent systems, automated deduction, and applications of separation logic. He develops tools like Raven, GRASShopper, and Sprout for verifying concurrent programs and search structures. Recent Articles (2025-2023): Focus on SMT-based verification, concurrent data structures, temporal safety effects, multiparty protocols, and separation logic extensions. These span conferences like OOPSLA, CAV, IEEE S&P, and TACAS. Scientific Awards: Best Paper at ISSRE 2019 Best Paper at ICFP 2014 Professional Activities: Organizer/Co-organizer of VerifyThis 2025, Program Chair roles in NETYS 2023, VMCAI 2022, and others. Active in PC roles for POPL, PLDI, CAV, and VMCAI. Students & Group: Advises PhD students including Elaine Li, Devora Chait-Roth, and Ekanshdeep Gupta. Group alumni include Kshitij Bansal, Siddharth Krishna, and Wei Wang.

Yizhou ZhangView profile

Assistant Professor

• Programming Languages
• Probabilistic Programming
• Compiler Design
• +4 more

Yizhou Zhang is an Assistant Professor at the Cheriton School of Computer Science, University of Waterloo. He specializes in programming language design and implementation, focusing on balancing expressive power with strong guarantees through language abstractions and compiler verification. Designing modular, type-safe language systems Probabilistic programming and inference optimization Algebraic effects and control flow management His recent publications explore lexical effect handlers, certified compiler frameworks, and nested polymorphism models. Awards include the ACM SIGPLAN Distinguished Paper Award (2023) for his work on probabilistic program compilation. Current advisees include PhD candidates Cong Ma, Zhaoyi Ge, Jianlin Li, and Ende Jin. He has served on program committees for POPL, PLDI, and OOPSLA conferences.

Rohan PadhyeView profile

Assistant Professor

• Software Engineering
• Programming Languages
• Systems
• +3 more

Rohan Padhye is an Assistant Professor at the Software and Societal Systems Department (S3D) in the School of Computer Science at Carnegie Mellon University. He leads the PASTA Lab , focusing on program analysis, software testing, and applications. He completed his Ph.D. in Computer Science at UC Berkeley under Koushik Sen, with research on program analysis specialization, and holds a Master's from IIT Bombay in static program analysis. Education: Ph.D. (UC Berkeley), Master's (IIT Bombay), B.E. (not explicitly stated but implied from context) Affiliations: Carnegie Mellon University, CyLab, Amazon Web Services (visiting academic), Microsoft Research (intern), Samsung Research America (intern), IBM Research India (researcher) His research spans software engineering, programming languages, systems, and security, with a focus on automated bug discovery through dynamic program analysis, coverage-guided fuzz testing, and concurrency testing. He has published in top venues like ICSE, ASE, ISSTA, SOSP, and USENIX Security. His recent projects include Fray (concurrency testing), Mu2 (mutation-guided fuzzing), and ChocoPy (educational programming language). Key research trends include: fuzz testing for distributed systems, AI-driven testing techniques, date/time bug analysis, performance issue detection in network controllers, and mutation-based testing guidance. His work integrates machine learning with traditional software testing and emphasizes open science through Green Open Access and artifact sharing. Scientific Awards NSF grants as PI (2025, 2021) Amazon Research Awards (2025, 2022) CyLab funding (2023, 2022, 2021) ACM SIGSOFT Distinguished Paper Awards (2025, 2023, 2025) Distinguished Reviewer Awards (PLDI'25, ACM TOSEM) SOSP 2019 Best Paper Award He advises a team of Ph.D. and Master's students in the PASTA Lab while teaching courses on program analysis and software testing. His lab's research is funded by NSF, CyLab, and Amazon.

Işıl DilligView profile

Associate Professor

• Program analysis
• Program synthesis
• Program verification
• +4 more

Işıl Dillig is an Associate Professor of Computer Science at the University of Texas at Austin, where she leads the UToPiA research group. Her academic career spans over a decade of significant contributions to programming languages research, particularly in program analysis, verification, and synthesis. Dr. Dillig received all her academic degrees (BS, MS, and PhD) from Stanford University before joining the faculty at UT Austin. Her educational background established the foundation for her innovative research approach that bridges theoretical computer science with practical applications. Her research focuses on developing techniques to make software systems more reliable, secure, and easier to build through advanced program analysis, verification, and synthesis methods. She has pioneered approaches that combine symbolic reasoning with machine learning to tackle complex software engineering challenges across multiple domains including security, databases, and programming language theory. Her work demonstrates exceptional depth in creating practical tools that address real-world software development problems while maintaining strong theoretical foundations. Analysis of Dr. Dillig's publication record reveals a consistent trajectory of innovation in program synthesis, with recent work expanding into neurosymbolic approaches that bridge neural networks with formal methods. Her research shows strong connections between theoretical foundations and practical applications, particularly in security-critical systems, database technologies, and blockchain applications. The evolution of her work demonstrates increasing sophistication in handling complex program structures while maintaining practical usability. Dr. Dillig has received prestigious recognition for her research contributions: Sloan Fellowship NSF CAREER award As a dedicated educator and research leader, Dr. Dillig has served in significant roles including Program Chair for PLDI 2022 and Steering Committee member for PLDI. She has mentored numerous students through her UToPiA research group, guiding research in program synthesis, verification, and analysis. Her work has been supported by substantial research grants that have enabled innovative projects at the intersection of programming languages and security. Dr. Dillig leads the UToPiA (UT Austin Programming, Languages, and Analysis) research group, which focuses on developing novel techniques for program analysis, verification, and synthesis. The group maintains strong collaborations with industry partners and academic institutions worldwide, translating theoretical advances into practical tools that address real software engineering challenges.

Amal AhmedView profile

Professor

• correct and secure compilation
• safe language interoperability
• foreign-function interfaces
• +9 more

Amal Ahmed is a Professor and Associate Dean for Graduate Programs at Khoury College of Computer Sciences, Northeastern University, where she leads research in programming languages and secure compilation. She received her PhD in Computer Science from Princeton University and has established herself as a leading researcher in compiler correctness, language interoperability, and type systems. Her research focuses on correct and secure compilation across the software-hardware stack and safe language interoperability, including design of sound foreign-function interfaces (FFIs) and richly typed compiler intermediate languages. She makes extensive use of semantics and type systems for reasoning about imperative and probabilistic programming languages, multi-language systems, security, concurrency, and provenance. Her work has significantly advanced the understanding of gradual typing, compiler verification, and compositional language interoperability. Dr. Ahmed's publications reveal a research trajectory focused on building solid semantic foundations for language interoperability and secure compilation. Her recent work spans topics from probabilistic separation logic to WebAssembly interoperability, with consistent emphasis on formal verification and semantic techniques. She has developed frameworks for reasoning about multi-language systems that preserve security properties across language boundaries. NSF CAREER Award recipient Editorial Board: Journal of Functional Programming (2017–present) Editorial Board: Mathematical Structures in Computer Science (2016–present) Member: IFIP Working Group 2.8 (Functional Programming, 2014–present) As an educator and mentor, Dr. Ahmed has advised numerous PhD students, postdocs, and undergraduates, many of whom have gone on to successful academic and industry careers. She has organized the Programming Languages Mentoring Workshop and regularly teaches advanced courses in programming languages. She serves on the steering committees of major conferences including POPL, SPLASH, and PLMW, and has chaired program committees for ESOP and POPL.

Marc PouzetView profile

Professor

• Programming Languages
• Synchronous Systems
• Reactive Systems
• +3 more

Marc Pouzet is a Professor at École Normale Supérieure (ENS) in the Department of Computer Science (DIENS), where he serves as Director of CS studies. He leads the INRIA project-team PARKAS and was a Junior Member of the Institut Universitaire de France (2007–2012). His research centers on synchronous programming languages for safety-critical embedded systems, with contributions to real-time software verification, hybrid systems modeling, and probabilistic reactive programming. Research Focus Pouzet's work bridges theory and practice in: Synchronous Languages : Design/extensions of Lustre, Lucid Synchrone, and Zelus for embedded control Formal Methods : Mechanized semantics (Coq) and verified compilers (Vélus) for correctness guarantees Hybrid Systems : Integrating ODEs with discrete logic (ProbZelus for probabilistic inference) Real-time Systems : Scheduling, latency constraints, and memory-safe compilation Awards & Leadership Inria–Académie des sciences Innovation Award (2016) Program committees: EMSOFT, PLDI, POPL, ECRTS Associate Editor: EURASIP Journal on Embedded Systems Advising & Projects Supervised 19+ PhD students on topics spanning compiler verification (Bourke, Pesin), probabilistic languages (Baudart), and hybrid systems (Pauget). Leads development of open-source tools: Zelus (synchronous language with ODEs) Vélus (verified Lustre compiler) ReactiveML (reactive extension of OCaml)

Laure PetrucciView profile

Professor

• Formal Methods
• Concurrent Systems
• Petri Nets
• +3 more

Laure Petrucci is a Professor at Sorbonne Paris Nord University, affiliated with the Networks and Telecommunications Department and the LoVe (Logic and Verification) team at LIPN (Paris Nord Computer Science Laboratory, CNRS UMR 7030). She also serves as Deputy Scientific Director of CNRS for Normandy. Her research specializes in formal verification of concurrent systems using Petri nets and parameterized models, with a focus on combating state-space explosion through distributed algorithms. Her work spans formal methods , distributed systems , and model checking , emphasizing practical applications in network verification and synthesis. Recent publications explore controller synthesis for timed games, probabilistic model checking, and SMT-based analysis of Petri nets, reflecting a consistent focus on scalable verification techniques. She teaches undergraduate and master's courses in networks, databases, and programming at IUT Villetaneuse (France) and the University of Science and Technology of Hanoi (Vietnam).

• Concurrency Theory
• Process Algebra
• Trustworthy Systems
• +7 more

Alessandro Aldini is an Associate Professor in the Section of Informatics and Mathematics within the Department of Pure and Applied Sciences (DiSPeA) at the University of Urbino Carlo Bo. His academic work focuses on theoretical computer science with applications to security and verification of complex systems. His research interests span several key areas: Design and verification of concurrent and distributed computer, network, and software systems Trust models and trustworthy systems Concurrency theory and (nondeterministic, probabilistic, and Markovian) process algebra Exact and approximate behavioral equivalences and equivalence checking Exact and approximate noninterference approach to information flow analysis Modal logics and model checking Security, dependability, and performability analysis Professor Aldini serves as the UNIURB research unit leader for the PRIN project AsCoT-SCE (Assessing Compliance of IoT API for Security Critical Environments) and participates in other significant research initiatives including DeKLA (Developing Kleene Logics and their Applications) and NiRvAna (Noninterference and Reversibility Analysis in Private Blockchains). He is actively involved in the academic community through the Italian Chapter of the EATCS and IFIP WG 11.14 Secure Engineering. His teaching responsibilities include Programming Languages and Software Verification and Cybersecurity courses across multiple Informatics degree programs. Professor Aldini has supervised numerous PhD students and postdoctoral researchers. His academic contributions include the book "A Process Algebraic Approach to Software Architecture Design" and his PhD thesis "Security and Performance Analyses in Distributed Systems."

Xiang GaoView profile

Associate Professor

• Program Analysis
• Software Security
• Automated Program Repair
• +4 more

Xiang Gao is a Pre-tenure Associate Professor in the School of Software at Beihang University, China. His research focuses on applying program analysis, test generation, and formal methods to improve software quality through automated bug fixing and program synthesis. He has established significant collaborations with Fujitsu Laboratories of America, Microsoft Research, and other leading institutions in the software engineering field, demonstrating strong industry-academia connections. Dr. Gao received his Bachelor's degree in Computer Science (Elite Class) from Shandong University in 2016, followed by a Ph.D. from the School of Computing at the National University of Singapore, where he also served as a Postdoctoral Fellow until December 2021. His educational background spans both Chinese and Singaporean academic institutions, providing him with a global perspective on software engineering research. His primary research interests span multiple cutting-edge areas of software engineering: Program Analysis techniques for detecting and fixing software bugs with formal methods Software Security vulnerabilities with focus on automated repair methods Automated Program Repair systems that generate high-quality patches without overfitting Program Synthesis for creating transformation rules from examples Software Engineering for Artificial Intelligence (SE4AI) to improve AI model reliability and security Mobile Software Engineering with particular attention to UI testing and automation Deep Learning Security including model protection and obfuscation techniques Dr. Gao's recent publication trajectory shows a strategic evolution toward integrating large language models with traditional software engineering approaches, particularly in test generation and program repair. His work on DNN modularization (NeMo, CNNSpliter, SeaM) represents an innovative approach to enhancing model reusability and security in resource-constrained mobile environments, addressing critical challenges in deploying AI on edge devices. His scientific contributions have been recognized with multiple prestigious awards: ACM SIGSOFT Distinguished Paper Award for "ProveNFix: Temporal Property guided Program Repair" at FSE'24 IEEE TCSE Distinguished Paper Award for "Investigating and Detecting Silent Bugs in PyTorch Programs" at SANER'24 ACM SIGSOFT Distinguished Paper Award for "Modularizing while Training: A New Paradigm for Modularizing DNN Models" at ICSE'24 Distinguished Artifact Award for "Automated Patch Backporting in Linux (Experience Paper)" at ISSTA'21 Dr. Gao actively mentors students at various levels, seeking "self-motivated Ph.D, master, undergraduate students and interns with strong programming skills" for his research projects. He serves on numerous program committees for top software engineering conferences including ICSE, ASE, ISSTA, and FSE, demonstrating his growing influence in the academic community. His research has been supported through collaborations with industry partners including Microsoft Research and Fujitsu Laboratories of America, translating theoretical advances into practical applications. His laboratory focuses on several key research projects including Automated Software Vulnerability Repair (with techniques like Fix2Fit, VulnFix, and ExtractFix that address the overfitting problem in program repair), Program Synthesis for Program Transformation (including Semi-supervised synthesis and FixMorph for automated patch backporting in Linux), and Software Engineering for Artificial Intelligence (with projects like CNNSpliter, SeaM, and Sensei that apply software engineering principles to improve AI model usability and robustness). These projects represent cutting-edge work at the intersection of traditional software engineering and modern AI techniques, addressing critical challenges in software reliability and security.

Robert B GardnerView profile

Professor

• Real Analysis
• Wavelets
• Markov-Bernstein Inequalities
• +3 more

Robert B Gardner is a Professor in the Department of Mathematics and Statistics at East Tennessee State University's School of Science, Engineering, and Math. He serves as the Mathematics and Statistics Undergraduate Research Honors Program Coordinator and is actively involved in both research and innovative teaching methods. Dr. Gardner's research focuses on real analysis, wavelets, and Markov-Bernstein inequalities for polynomials. His scholarly work includes co-authoring significant texts such as Real Analysis with an Introduction to Wavelets (2005) and Extremal Problems and Inequalities of Markov-Bernstein Type for Algebraic Polynomials (2022). He has also co-edited Logic, Probability and Science (2000) with Niall Shanks. Known for his creative teaching approaches, Dr. Gardner developed the S.H.E.M.P. Seminar (Seminar on the History and Exploration of Math Problems), which uses references to the Three Stooges to make mathematics more engaging. His teaching resources include 'Dr. Bob's Online University' with video lectures and extensive course materials available on his website. Dr. Gardner maintains active involvement in undergraduate education through the Mathematics and Statistics Undergraduate Research Honors Program. His website shows ongoing activities through 2025, including celebrations of his vintage Volkswagen vehicles, indicating his continued active engagement with students and the academic community.

• Operations Research
• Scheduling Algorithms
• Discrete-Continuous Scheduling
• +6 more

Professor Joanna Józefowska is a distinguished academic at Poznań University of Technology, where she serves as a full professor in the Faculty of Computing and Telecommunications, Institute of Computer Science. With a career spanning over three decades since completing her doctoral dissertation in 1990, she has established herself as a leading expert in operations research and scheduling algorithms. Her research spans several key areas within operations research, with particular emphasis on: Discrete-continuous scheduling problems Resource allocation and optimization Just-in-time scheduling models Applications of apportionment theory Energy-efficient computing systems Quantum approaches to transportation problems Professor Józefowska's recent work demonstrates her ability to adapt traditional operations research methods to address contemporary technological challenges, with publications in 2022-2023 focusing on energy-efficient computing systems and quantum approaches to electric vehicle charging infrastructure. Her research output shows consistent productivity throughout her career, with publications appearing in reputable journals such as European Journal of Operational Research, Annals of Operations Research, and Computers and Operations Research. As an academic mentor, Professor Józefowska has successfully guided multiple doctoral students to completion, with dissertations covering topics ranging from ontology enrichment to discrete resource allocation. Her supervision has helped develop the next generation of researchers in operations research and computer science, contributing to the academic ecosystem at Poznań University of Technology and beyond. Her scholarly contributions extend beyond research and supervision to include editorial roles for significant publications in her field, demonstrating recognition of her expertise by the broader academic community. Professor Józefowska continues to actively contribute to the advancement of knowledge in operations research while maintaining her position as a respected academic at one of Poland's leading technical universities.

• Bayesian Networks
• Probabilistic Graphical Models
• Machine Learning
• +5 more

Antonio Salmerón Cerdán is a Professor in the Mathematics Department at the University of Almería, where he has established himself as a leading researcher in probabilistic artificial intelligence and Bayesian networks. With over 25 years of academic experience, he leads the 'Análisis de datos' research group and serves as Principal Investigator for multiple nationally and internationally funded projects, including the current 'Hacia una Inteligencia Artificial Probabilística Confiable (TOPAI-UAL)' project (2023-2026). His research expertise spans theoretical and applied aspects of probabilistic graphical models, with particular focus on Bayesian networks, causal inference, and their applications across diverse domains. His work demonstrates a consistent trajectory from foundational theoretical contributions to practical implementations in software engineering, genomics, sports analytics, and trustworthy autonomous systems. Professor Salmerón's publication portfolio reveals a strong emphasis on methodological innovations in probabilistic reasoning, with recent work exploring divide-and-conquer approaches for causal computation, noise-robust classification methods, and the integration of observational and randomized data sources. His research shows increasing interdisciplinary reach, connecting computer science methodologies with applications in plant genomics, software maintenance, and healthcare. Journal Publications: 105 articles in high-impact venues including Ecological Informatics (Q1), International Journal of Approximate Reasoning (Q2), and ACM Transactions Research Funding: Principal Investigator for 9 major projects since 2001 totaling over €800,000 in funding Thesis Supervision: Director of 7 doctoral theses on probabilistic graphical models and their applications Metrics: h-index 22 (Web of Science), i10 index 59 His research program demonstrates a unique combination of theoretical rigor in probabilistic reasoning with practical applications across diverse scientific domains, positioning him at the forefront of reliable probabilistic AI development.

Marie-Christine ROUSSETView profile

Professor

• Knowledge Representation
• Information Integration
• Ontology-based data access
• +7 more

Marie-Christine ROUSSET is a Professor of Computer Science at the University of Grenoble Alpes (UGA) in France, where she is a member of the LIG (Laboratoire d'Informatique de Grenoble) in the SLIDE group. Previously affiliated with Paris-Saclay (LRI), she has established herself as a leading researcher in Knowledge Representation and Information Integration. She holds the distinguished position of Senior member of the Institut Universitaire de France (IUF) (2011-2016, renewed for 2016-2021) and serves as co-responsible for the chair Explainable and Responsible AI within MIAI Grenoble Alpes. Her research focuses on ontology-based data access, logic-based mediation between distributed data sources, query rewriting using views, data linkage, and distributed reasoning for the Semantic Web. She skillfully combines artificial intelligence and database techniques to address complex information integration challenges, with applications spanning biomedical informatics, educational technology, and trustworthy AI. Her work demonstrates consistent innovation from foundational research to practical implementations, as evidenced by her co-authorship of the book 'Web Data Management' published by Cambridge University Press. Professor ROUSSET's recent publications (2019-2022) reveal a growing emphasis on data privacy, RDF graph anonymization, and interactive ontology engineering, while maintaining her strong contributions to semantic web technologies and knowledge representation. Her research shows increasing attention to trustworthy AI concerns, aligning with her leadership roles in relevant projects. Scientific Recognition Senior member of Institut Universitaire de France (IUF) (2011-2016, renewed for 2016-2021) Junior member of Institut Universitaire de France (IUF) from 1997 to 2002 Chevalier de l'Ordre National du Merite (July 11, 2011) EurAI Fellow (nominated ECCAI Fellow in 2005) Best Paper Award at AAAI'96 for 'Verification of Knowledge Bases based on Containment Checking' Professor ROUSSET maintains an active role in the scientific community through editorial work and organizational leadership. She serves on the Editorial Board of Communications of the ACM (CACM) and has held significant roles including PC chair of EGC 2019, Workshops co-Chair of WWW 2018, and Area Chair of IJCAI 2017. Her consistent service on program committees of major international conferences demonstrates her standing in the field. Her laboratory, the SLIDE group within LIG, focuses on semantic web technologies, knowledge representation, and data integration. The group maintains strong connections with the international research community and participates in collaborative projects addressing cutting-edge challenges in artificial intelligence and data management, with particular emphasis on trustworthy and explainable AI systems.

Olivier SerreView profile

Professor

• theoretical computer science
• automata theory
• formal languages
• +7 more

Olivier Serre is a CNRS Research Director working at the Institute for Research in Fundamental Computer Science (IRIF), a joint research unit of CNRS and University of Paris. Since September 2021, he serves as Deputy Scientific Director at the Institute for Information Sciences and Technologies (INS2I) at CNRS. His research focuses on theoretical computer science with particular emphasis on automata theory and formal verification frameworks. Dr. Serre completed his education at ENS Cachan (1999-2003) and earned his PhD in Computer Science from Paris-Diderot University (now University of Paris) in 2004. Following a postdoctoral position at RWTH Aachen, he joined LIAFA (now IRIF) as a research fellow in 2005 and became a CNRS Research Director in 2016. His academic journey reflects deep engagement with foundational theoretical problems and their practical verification applications. His research centers on automata theory and formal languages, with particular expertise in games and logic, infinite structures, and verification of higher-order functional programs. Dr. Serre has made significant contributions to collapsible pushdown systems, recursion schemes, and parity games, bridging theoretical foundations with practical applications in program verification. His work demonstrates exceptional depth in developing decision procedures for complex verification problems previously considered intractable. Dr. Serre's extensive publication record in premier theoretical venues shows consistent contribution to advancing the state of the art. His research trajectory reveals a clear evolution from foundational automata theory toward increasingly sophisticated systems involving higher-order computation and imperfect information, with notable breakthroughs in establishing decidability results for complex verification problems.