Find Academic Supervisors

Roberto GiacobazziView profile

Professor

• Theory of computation
• Programming languages
• Abstract interpretation
• +3 more

Roberto Giacobazzi is a Professor at the University of Arizona specializing in theoretical computer science with a focus on abstract interpretation, program analysis, and verification. His research bridges theoretical foundations with practical applications in software security and verification systems. Dr. Giacobazzi received his Ph.D. from the University of Pisa in Italy in 1993, establishing a long-standing academic career focused on the theoretical underpinnings of program analysis. His educational background forms the foundation for his contributions to abstract interpretation theory. His primary research interests center around abstract interpretation, a theoretical framework for approximating program semantics. This work spans theory of computation , programming languages , program analysis and verification , and logic in computer science . Giacobazzi has made significant contributions to understanding completeness and precision in abstract interpretation, with applications extending to code obfuscation, security analysis, and more recently, AI fairness in legal contexts. His work demonstrates how theoretical computer science concepts can address practical software engineering challenges. An analysis of his recent publications (2022-2025) reveals a consistent research trajectory with increasing sophistication in abstract interpretation theory. His work shows a growing emphasis on completeness properties, precision limitations, and security applications. Notably, his 2024 publication on "Fairness of AI Systems in the Legal Context" indicates an expansion of his theoretical expertise into AI ethics and regulatory compliance, demonstrating the versatility of abstract interpretation frameworks. Dr. Giacobazzi has contributed extensively to major conferences in programming languages and verification, including SAS (Static Analysis Symposium), POPL (Principles of Programming Languages), and VMCAI (Verification, Model Checking, and Abstract Interpretation). His publications reflect deep theoretical insights while maintaining relevance to practical software analysis challenges. His research has significant implications for software security, particularly in code obfuscation techniques based on abstract interpretation. The systematic approach to measuring incompleteness in abstract interpretations has provided new frameworks for understanding and improving program analysis tools. His work continues to influence both academic research and practical applications in program verification and security.

Heather MillerView profile

Assistant Professor

• Distributed Systems
• Concurrent Programming
• Programming Languages
• +4 more

Heather Miller is a tenure-track Assistant Professor in the Software and Societal Systems Department within Carnegie Mellon University's School of Computer Science. Her academic journey includes prior roles as an Assistant Clinical Professor at Northeastern University's College of Computer and Information Science and as Executive Director of the Scala Center at EPFL. Miller's research centers on distributed and concurrent computation through the lens of programming languages, with particular emphasis on data-centric systems, big data processing, and edge computing. A defining theme throughout her work is composability - enabling construction of complex distributed systems through composition of components that are correct by construction. Her projects span distributable closures, flexible serialization techniques, futures and promises for asynchronous programming, and deterministic concurrent dataflow models. Her recent publications demonstrate strong trends in applying programming language theory to practical distributed systems challenges, with increasing focus on WebAssembly instrumentation, microservice resilience, and language model pipelines. This evolution reflects her commitment to bridging theoretical foundations with real-world system requirements. Dahl-Nygaard Junior Prize (2023) Mentorship forms a significant component of Miller's academic work. She actively supervises multiple PhD, MS, and undergraduate researchers at CMU, including Christopher Meiklejohn, Matthew Weidner, Huairui Qui, Ria Pradeep, and Luke Dramko. Her service contributions span numerous top-tier conferences including PLDI, SPLASH, ECOOP, and ICSE where she has served as committee member, chair, and keynote speaker. Miller co-founded the Curry On conference to foster industry-academia dialogue, hosting successful editions in Prague, Rome, Barcelona, Amsterdam, and London. She leads research groups focused on distributed programming models and maintains strong industry connections through Two Sigma, where she holds an affiliation. Her work consistently emphasizes practical open-source implementations, primarily within the Scala ecosystem where she's been a core contributor since 2011.

Gerhard FriedrichView profile

Professor

• Artificial Intelligence
• Knowledge-Based Systems
• Recommender Systems
• +10 more

Gerhard Friedrich is a Full Professor at the University of Klagenfurt, leading the Institute for Artificial Intelligence and Cybersecurity. He previously served as Dean of the Faculty of Technical Sciences (2013–2021). His roles include Coordinator for International Relations of the Faculty of Engineering and Member of the Faculty Conference of Technical Sciences. He holds a PhD in Computer Science from Vienna University of Technology and has extensive industry experience, including heading departments at Siemens Austria and research roles at Siemens Corporate Research and Stanford Research Institute. Research focuses on knowledge-based systems, recommender systems, configuration and planning, and production informatics. His work bridges theoretical AI with practical applications in manufacturing, software development, and business processes. He has authored a book on recommender systems (translated into Japanese and Chinese) and contributed to prestigious journals like Artificial Intelligence and IEEE Transactions . He has organized major conferences such as the German Conference on Artificial Intelligence (2016) and served as editor and program committee member for leading venues. His awards include Fellowships from the European and Asia-Pacific AI Associations (2012, 2023). His advising and grants include leadership in applied AI projects and international collaborations. He directs the Intelligent Systems and Business Informatics research group, emphasizing interdisciplinary innovation.

Kristopher MicinskiView profile

Assistant Professor

• Programming Languages
• Static Analysis
• Formal Methods
• +4 more

Kristopher Micinski is an Assistant Professor in the Electrical Engineering and Computer Science Department at Syracuse University. His research focuses on scalable program analysis, static analysis, and formal methods applied to computer security and privacy. He holds a PhD in Computer Science from the University of Maryland and a BS in Computer Engineering from Michigan State University. Education: PhD, Computer Science, University of Maryland at College Park BS, Computer Engineering, Michigan State University Research Interests: His work bridges theory and application of program analyses, emphasizing scalable static analysis frameworks, Datalog optimization for distributed systems, and security applications. Recent efforts include GPU-accelerated Datalog engines and large-scale malware analysis pipelines like Assemblage. Grants & Projects: NSF PPoSS Large: $1M grant for declarative analytics DARPA V-SPELLS: $400K for legacy software optimization Assemblage: $350K DoD grant for malware classification Teaching: He teaches undergraduate and graduate courses on programming languages (CIS352) and formal methods (CIS700), with materials publicly available on YouTube.

• Logic Programming
• Knowledge Representation
• Artificial Intelligence
• +6 more

Bart Bogaerts is an Associate Professor in the Department of Computer Science at KU Leuven's Faculty of Engineering Science. He is affiliated with the Declarative Languages and Artificial Intelligence (DTAI) research unit and is a member of Leuven.AI - KU Leuven Institute for Artificial Intelligence. Bogaerts serves on the Council of the Faculty of Engineering Science as senior academic staff and participates in the Programme Committee for Artificial Intelligence curriculum development. His research focuses on foundational aspects of logic programming and knowledge representation, with particular expertise in approximation fixpoint theory, higher-order logic programming, and non-monotonic reasoning. Bogaerts investigates the theoretical underpinnings of stable model semantics, justification frameworks, and executable query languages. His work bridges theoretical computer science with practical applications in artificial intelligence and knowledge-based systems. Bogaerts' publication record demonstrates consistent contributions to top venues in logic programming and artificial intelligence. His recent work shows increasing focus on category-theoretic approaches to approximation theory, distributed web traversal specifications, and certified model expansion techniques. The publications reveal a strong emphasis on formal methods with applications spanning from theoretical mathematics to practical AI systems. As a promotor for multiple significant research projects, Bogaerts leads investigations into certified answer set programming (CertifASP), first-order model expansion (CertiFOX), proof generation for combinatorial optimization, distributed configuration problems, and knowledge integration paradigms. These projects, funded through 2028-2029, demonstrate his leadership in advancing the theoretical foundations of AI and logic programming. Bogaerts is actively involved in teaching courses on knowledge representation and reasoning, contributing to the development of next-generation AI researchers. His work within the DTAI research unit positions him at the forefront of declarative AI approaches in Belgium's leading research university.

• Answer Set Programming
• Artificial Intelligence
• Logic Programming
• +4 more

Torsten Schaub is a Professor at the Institute of Computer Science , University of Potsdam. His research focuses on Answer Set Programming (ASP) , constraint solving, temporal reasoning, and combinatorial optimization, with applications in multi-agent pathfinding, product configuration, and course timetabling. Key contributions include ASP-based tools for industrial-scale optimization problems, metric temporal logic implementations, and frameworks for dynamic equilibrium logic. Recent work explores efficient design space exploration, stream reasoning, and multi-shot ASP solving for complex domains. His publications emphasize hybrid ASP systems , integrating constraints and temporal logic, with co-authors across Europe and Asia. He actively develops tools like clingo and Clingraph for practical ASP applications in logistics, bioinformatics, and robotics. The articles reveal a trend toward multi-agent systems (e.g., pathfinding algorithms) and temporal extensions in ASP, combining formal logic with real-world problem-solving. Sub-fields include constraint satisfaction, logical abduction, and declarative modeling for optimization tasks.

Siegfried NijssenView profile

Assistant Professor

• Data Mining
• Pattern Mining
• Exploratory Data Analysis
• +5 more

Siegfried Nijssen is an Assistant Professor of Data Mining and Artificial Intelligence at the Catholic University of Louvain (UCLouvain) in Belgium, working within the ICTEAM research institute's Artificial Intelligence and Algorithms group. He has been at UCLouvain since 2016, previously serving as an Assistant Professor at University Leiden (2012-2016) and completing postdoctoral work at KU Leuven (2006-2015). He earned his PhD in Computer Science from University Leiden in 2006. His research focuses on making data analysis simpler through intersections between pattern mining, exploratory data analysis, and programming paradigms in Artificial Intelligence, particularly constraint programming and probabilistic programming. He has developed techniques for analyzing diverse data types including graphs, networks, and multi-relational data. His work bridges theoretical foundations with practical applications in decision tree learning, probabilistic networks, and source code analysis. Nijssen's recent publications demonstrate a strong focus on optimal decision trees, constraint-based pattern mining, and applications in bioinformatics and education. His research shows consistent evolution from foundational graph mining work (including the Gaston algorithm developed in 2004) to current work integrating machine learning with constraint programming for interpretable AI solutions. As an educator, he teaches courses including Mining Patterns in Data, Databases, and Artificial Intelligence and Machine Learning seminars at UCLouvain. He has advised numerous PhD students and postdocs, primarily in collaboration with Pierre Schaus, with former students like Tias Guns now holding professorships.

• Theoretical Linguistics
• Formal Semantics
• Formal Pragmatics
• +6 more

Sophia A. Malamud is an Associate Professor in the Department of Computer Science at Brandeis University, where she directs the Meaning In Language Research Group (MILa) and is affiliated with the Language & Linguistics Program. Her research specializes in theoretical linguistics with a focus on formal semantics, formal pragmatics, discourse-syntax interactions, and semantics-pragmatics interface. Her educational background includes a Ph.D. in Linguistics with a dissertation on Semantics and pragmatics of arbitrariness and an M.A. in Mathematics exploring statistical decision theory in Entropy as relevance: maximizing entropy and minimizing loss . Malamud's research investigates discourse coherence, word order variations, indexicality, semantics of impersonals/plurals, speech acts, and utterance modifiers. She leads NSF-funded projects creating annotated corpora of spoken Russian (including the BiRCh Corpus), examining bilingual acquisition and heritage language phenomena. Her work employs corpus linguistics, experimental methods, and formal modeling. Her publications demonstrate consistent focus on pragmatic computation models, conversational dynamics, and cross-linguistic semantics, with frequent examination of Russian, Mandarin, and Greek data. Key themes include commitment avoidance strategies, conversational scoreboard modeling, and formal analyses of particles/pronouns. Awards include: NSF Grant BCS-1651083 for BiRCh Corpus development Mandel Foundation Faculty Grant for heritage language research Theodore and Jane Norman Award (2018) Multiple Brandeis Provost Research Grants Malamud has advised 8+ graduate/undergraduate theses on topics including heritage Russian pragmatics, utterance particles, reduplication, and distributivity. She collaborates internationally on corpus projects and directs research teams at Brandeis' Laboratory for Linguistics and Computation.

Michael KiferView profile

Professor

• Declarative Languages for Data and Knowledge Manipulation
• The Semantic Web
• Integration of Object-oriented and Deductive Paradigms
• +4 more

Michael Kifer is a Professor in the Department of Computer Science at Stony Brook University . His research focuses on declarative languages, logic programming, semantic web, and integration of object-oriented and deductive paradigms. He has received multiple prestigious awards including three ACM-SIGMOD 'Test of Time' awards, SUNY Chancellor's Award, and Stony Brook's Research Excellence Award. Ph.D. in Computer Science, Hebrew University of Jerusalem (1985) M.S. in Mathematics, Moscow University (1976) Dr. Kifer's research interests span over 30 years, with major contributions to databases, knowledge representation, and semantic web technologies. He co-invented F-logic, HiLog, Annotated Logic, and Transaction Logic, which are widely cited in computer science literature. His recent publications focus on hybrid logic programming, multilevel modeling (MLM), and knowledge authoring systems like Flora-2. These works bridge rule-based reasoning, controlled natural language, and semantic web technologies. Scientific Awards : Department Research Excellence Award (2014) ACM-SIGMOD 'Test of Time' Awards (1999, 2002) SUNY Chancellor's & Stony Brook President's Awards (2008) Association for Logic Programming 'Test of Time' Award (2013) Plumer Fellowship at Oxford (2006) Dr. Kifer has served on editorial boards and chaired conferences in logic programming and semantic web. He developed the Flora-2 knowledge representation system and contributed to standards like RIF (Rule Interchange Format).

Tiark RompfView profile

Assistant Professor

• Compiler Design
• Programming Languages
• Runtime Code Generation
• +8 more

Tiark Rompf is an Assistant Professor at Purdue University , with research spanning programming languages, compilers, and systems. His work bridges domains including architecture, databases, machine learning, and AI through projects like Reachability Types and Rhyme. Co-director of the Purdue Center for Programming Principles and Software Systems (PurPL) Scientific Advisor at SambaNova Systems Previously a member of the Scala team at EPFL His research focuses on: Runtime code generation and advanced compiler technology Expressive data-centric query languages (Rhyme, Datalog) Reachability type systems for memory safety and effect handling Metaprogramming and logical relations for formal verification Recent publications highlight contributions to Datalog compilation (Flan), nested data structures (Rhyme), and polymorphic reachability types. He leads projects exploring: Compiler optimizations for emerging architectures (GPU, TPU, FPGA) ML-driven compiler improvements Secure multi-party computation via metaprogramming Scientific awards include: NSF CAREER Award (2016) Google Faculty Research Awards (2017, 2018) DOE Early Career Research Award (2017) ACM SIGPLAN PL Software Award (2019) GPCE Test of Time Award (2020) Students and alumni from his group have joined institutions like Databricks, DeepMind, Galois, and Meta. He teaches advanced compiler courses including: CS 590 - Advanced Topics in Compilers CS 352 - Compilers CS 502 - Graduate Compilers

Max WillseyView profile

Assistant Professor

• Program Optimization
• Programming Languages
• Databases
• +5 more

Max Willsey is an Assistant Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, since 2024. He specializes in program optimization, leveraging techniques from programming languages, databases, and systems to develop robust and accessible compiler frameworks. His research focuses on equality saturation, E-Graphs, and the integration of Datalog with compiler optimizations. He has contributed to advancements in unifying algorithmic approaches, enabling faster and more extensible program analysis. Teaching: CS 164 (Programming Languages and Compilers, Spring 2025), CS 265 (Compiler Optimization, Fall 2024), and CS 294-260 (Declarative Program Analysis and Optimization, Spring 2024). Research Highlights: Development of the egg and egglog projects, co-organizing the EGRAPHS workshop, and leading the EGRAPHS Community for e-graphs researchers. His recent articles highlight trends in unifying traditional hash joins with worst-case optimal joins, applying equality saturation to diverse domains like Datalog and tensor graph optimization, and advancing E-Graphs for program synthesis and formal verification. Scientific Awards: SIGMOD Record Research Highlight, 2024 MIT PL Review Selection, 2024 Distinguished Paper, OOPSLA 2021 and POPL 2021 NSF Graduate Research Fellowship Honorable Mention, 2018 Qualcomm Innovation Fellow, 2019 Service: Committee Member, PLDI 2025, POPL 2025, ASPLOS 2025 Co-organizer, EGRAPHS 2024 and 2023 workshops Interviewer, UC Berkeley Graduate Admissions Committee, 2024

Elena ZuccaView profile

Associate Professor

• Programming Languages
• Type Systems
• Formal Semantics
• +6 more

Elena Zucca is an Associate Professor in the Department of Computer Science, Bioengineering, Robotics and Systems Engineering (DIBRIS) at the University of Genoa, Italy. She has a strong research focus on programming languages, particularly in the areas of type systems, formal semantics, and coinduction. Her work bridges theoretical foundations with practical implementations, as evidenced by her publications on topics like Featherweight Java, corecursion, and soundness proofs for programming language features. Her research interests span the theoretical and practical aspects of programming languages. She investigates the formal semantics of programming constructs, particularly focusing on the boundaries between finite and infinite computations. Her work on coinduction and corecursion explores how to safely handle infinite data structures and computations. She has made significant contributions to understanding soundness in programming language features, especially in relation to resource-aware semantics. Her research often combines theoretical foundations with practical implementations, as seen in her work on Featherweight Java extensions and effect systems. Analysis of her recent publications reveals a consistent focus on advanced type systems and semantics. Her work explores the theoretical boundaries of programming language features while maintaining practical relevance. A recurring theme is the relationship between finite and infinite computations, with particular attention to soundness guarantees. Her research has evolved from foundational work on lambda calculus and object-oriented programming toward more specialized topics like graded types, coeffects, and resource-aware semantics. Elena Zucca has been actively involved in the programming languages research community, serving on program committees for major conferences including SPLASH, ECOOP, and POPL. She has mentored students through doctoral courses on Declarative Programming and (Co)Induction. Her research has been supported through participation in various academic programs, including the SEPL research program mentioned in her course materials. She teaches a diverse range of courses at the University of Genoa, from undergraduate to doctoral levels. Her teaching portfolio includes Automata Theory and Computability, Algorithms Analysis and Design, Principles and Paradigms of Programming Languages, and specialized doctoral courses on Declarative Programming and (Co)Induction. Her courses often reflect her research interests, covering theoretical foundations of programming languages, formal methods, and advanced programming paradigms.

Lars-Henrik ErikssonView profile

Senior Lecturer

• Formal Methods
• Logic in Computer Science
• Programming Language Theory
• +7 more

Lars-Henrik Eriksson is a Senior Lecturer in the Department of Computer Science at Uppsala University, part of the Department of Information Technology. He holds a PhD and is recognized as an Excellent Teacher and educational mentor. He currently serves as the program director for the Master's program in Computer Science and has previously held leadership roles, including Head of the Department of Computer Science from 2004 to 2018. PhD in Computer Science Excellent Teacher Award Pedagogical Mentor at Uppsala University His research focuses on the applications of logic in computer science, particularly formal methods for software development. His work spans formal specification, verification, and synthesis, with strong emphasis on logic programming, interactive theorem proving, and logical frameworks. He has made significant contributions to the use of formal methods in safety-critical domains such as railway signaling. His current research includes modeling application domains within formal methods and formalizing concurrency theory using the Isabelle proof assistant. The recent publications reflect a sustained focus on modal logics for nominal transition systems, formal verification tools (e.g., GTO), and domain-specific applications of formal methods. These works demonstrate deep integration of theoretical logic and practical software engineering, especially in distributed and safety-critical systems. The recurring themes include concurrency, verification, and the use of domain models to enhance formal reasoning. Scientific Awards and Recognitions: Excellent Teacher Pedagogical Mentor Lars-Henrik Eriksson has advised numerous students through project supervision, thesis reviews, and course mentorship, though no formal list of advisees is provided. He has been involved in significant research management, including leading the department and directing a master’s program. He has also collaborated with industry, particularly in railway signaling, contributing to safety analysis and formal verification projects with Trafikverket and through companies he co-founded. He is a board member of Formal Methods Europe and served as program committee chair for the FME Symposium 2002 (part of FLoC’02). His work bridges academia and industry, especially in the application of formal methods to real-world engineering challenges.

Mario AlvianoView profile

Professor

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Combinatorial Search and Optimization
• +5 more

Mario Alviano is a Full Professor in Computer Science (INF/01) at the University of Calabria, Department of Mathematics and Computer Science. He leads the LAIA lab (Laboratorio di Applicazioni dell'Intelligenza Artificiale) and serves as co-PI in the PRIN project PRODE ('Probabilistic Declarative Process Mining'). Current projects: FAIR ('Future AI Research'), Tech4You ('Technologies for climate change adaptation'), SERICS ('SEcurity and RIghts in the CyberSpace'), CAL.HUB.RIA , RADIOAMICA , and STROKE 5.0 His research focuses on Answer Set Programming (ASP), particularly in optimization, nonmonotonic reasoning, and applications to logistics, healthcare, and cybersecurity. He has authored over 120 publications in top venues like AIJ, AAAI, and IJCAI. Recent academic contributions includes work on: Temporal Many-valued Conditional Logics Weighted Knowledge Bases with Typicality Explainable AI via xASP and ASP Chef Defeasible Reasoning Scalability Notable awards: Artificial Intelligence Award 'Marco Somalvico' (2017) ICLP Best Paper Awards (2015, 2016) LPNMR Best Paper Award (2022) CILC Best Paper Award (2023)

• Concurrency
• Real-Time Systems
• Distributed Systems
• +3 more

Lukasz Ziarek is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, and serves as the Associate Dean for Academic Affairs in the School of Engineering and Applied Sciences. His research focuses on concurrency, real-time systems, distributed systems, and formal verification. He holds a PhD from Purdue University (2011) and a BS from the University of Chicago (2003). His research explores topics such as real-time Java implementations, session types for distributed protocols, and visual debugging techniques. Recent work includes formal models for secure multiparty computation, IoT device validation, and optimizing visual SLAM systems for robotics applications. He has contributed to frameworks like Juav (a Java-based UAV autopilot) and RTDroid (a real-time Android extension). Ziarek has received notable awards including the 2023 IEEE Technological Innovation Award, 2022 Meyerson Teaching Award, and 2018 NSF CAREER Award. His grants include collaborative research on UAV software infrastructure and real-time communication protocols. He actively develops tools like PTDETECTOR for JavaScript library analysis and Anodize for mixed-criticality systems. His work integrates formal methods with practical systems, addressing challenges in embedded systems security, compiler optimization, and real-time programming language design. He maintains a lab focused on advancing reliable software for autonomous systems and distributed computing environments.