Find Academic Supervisors

Magnus MyreenView profile

Professor

• Program Verification
• Interactive Theorem Proving
• Formal Methods
• +8 more

Magnus Myreen is a Professor in the Department of Computer Science and Engineering at Chalmers University of Technology, where he leads research in program verification, interactive theorem proving, and verified software systems. He previously held a prestigious Royal Society University Research Fellowship at the University of Cambridge. Chalmers University of Technology — Professor (2023–present), Associate Professor (2015–2023) University of Cambridge — Royal Society Research Fellow (2012–2018) His research focuses on making formal verification practical and scalable, particularly through the CakeML project—a fully verified ML-style language with a bootstrapped compiler. He develops techniques in decompilation into logic, proof-producing synthesis, and verified runtimes for theorem provers like Milawa and HOL Light. His recent publications span top venues such as POPL, PLDI, ITP, and CAV, with a strong emphasis on verified compilation, compiler optimizations, and connecting verified components into larger systems (e.g., seL4 + CakeML). The work consistently targets real-world applicability and reduction of trusted computing bases. ACM SIGPLAN Most Influential POPL Paper Award (2014) BCS Distinguished Dissertation Competition Winner (2010) Amazon Research Award (2023) Royal Society University Research Fellowship Magnus has advised several PhD students including Oskar Abrahamsson, Alejandro Gomez, and Andreas Loow. His research has been funded by the Swedish Research Council and EPSRC. He is currently chair of the ITP steering committee and frequently serves on program committees for ITP, CPP, PLDI, and related conferences. He has led major collaborative efforts to connect verified systems, such as extending the seL4 microkernel verification down to machine code and proving the soundness of the Milawa theorem prover down to x86 machine code. He also works on verified synthesis of hardware and formal semantics of multiprocessor architectures.

Per-Henning OlssonView profile

Senior Lecturer

• Swedish music history (18th century)
• Swedish music history (20th century)
• Music analysis of pop music
• +3 more

Per-Henning Olsson is a Senior Lecturer at Uppsala University's Department of Musicology, where he has served as Director of Studies for Advanced Level since July 2025. Previously, he held significant administrative roles including Director of Studies for the undergraduate program (2013-2018) and Head of Department (2018-2024). He earned his doctorate in 2013 with a dissertation titled A Symphonic Oddity: A Study in Allan Pettersson's Symphony Composition , establishing his expertise in Scandinavian musical traditions. His research encompasses two primary domains: Swedish music history spanning the 18th and 20th centuries, and analytical methodologies applied to popular music—particularly tempo and rhythm structures in rock and pop genres. A dominant focus of his scholarship involves the comprehensive study of Swedish composer Allan Pettersson, resulting in extensive critical editions of his orchestral works. Olsson's publications demonstrate sustained scholarly engagement with Pettersson's oeuvre, including critical editions of 15 symphonies, multiple concertos, and a complete works compilation. His analytical work extends to biographical studies of Swedish composers like David Wikander and Anders Eliasson. The publications reflect consistent methodological approaches in music editing, historical contextualization, and structural analysis of large-scale compositions.

David BromanView profile

Professor

• Programming Languages and Compilers
• Real-Time Systems and Cyber-Physical Systems
• Probabilistic Machine Learning
• +2 more

David Broman is a Professor at KTH Royal Institute of Technology in Sweden, leading the Division of Software and Computer Systems (SCS) and serving as Associate Director Faculty for Digital Futures. He holds a Ph.D. in Computer Science from Linköping University (2010), with visiting roles at UC Berkeley (2012–2016) and Stanford University (2023–2024). His research spans programming languages, real-time systems, and probabilistic machine learning, emphasizing secure and efficient compilation techniques. Education: Ph.D. in Computer Science (Linköping University, 2010) Visiting Roles: UC Berkeley (2012–2014 part-time), Stanford University (2023–2024) Research Interests: David focuses on advancing programming language theory, compilers, and probabilistic methods. Key areas include transformer-based compilation, cyber-physical systems, and formal verification. His work bridges theory and practice, addressing challenges in software reliability and efficiency. Awards: Notable recognitions include the Best ETAPS Paper Award (2023), Distinguished Artifact Award (ESOP 2022), and Teacher of the Year (KTH 2017). His contributions also include grants from the Swedish Foundation for Strategic Research and Wallenberg AI, Autonomous Systems and Software Program (WASP). Advising & Grants: David mentors graduate students (e.g., Gizem Caylak, Viktor Palmkvist) and leads projects funded by WASP, focusing on next-generation compilation techniques. He also contributed to tools like Miking, Timed C, and FlexPRET. Labs & Teams: His team develops frameworks for probabilistic programming and real-time systems, emphasizing collaboration with industry and academia through initiatives like Digital Futures at KTH.

August ErnstssonView profile

Lecturer

• Parallel Programming
• Heterogeneous Computing Systems
• High-Performance Computing
• +3 more

August Ernstsson is a Lecturer at Linköping University’s Department of Computer and Information Science (IDA). He is affiliated with the Graduate School in Computer Science (CUGS) and research groups Programming Environments (PELAB) and Software and Systems (SAS). His research focuses on parallel programming models, heterogeneous computing systems, and optimizing software for FPGA and GPU architectures. Notable contributions include frameworks for high development productivity (EXA2PRO) and deterministic parallel algorithms. Ernstsson’s work emphasizes performance portability, compiler design, and abstraction layers for heterogeneous systems. He collaborates with international teams on projects like pattern-based programming abstractions and FPGA-accelerated systems.

• Programming Languages
• Type Systems
• Compiler Optimization
• +2 more

Lars Hummelgren is a doctoral student at the Royal Institute of Technology , affiliated with the Division of Software and Computer Systems. His research focuses on programming languages, type systems, and efficient compilation techniques for CPUs and GPUs. He is supervised by David Broman, with co-supervision from Philipp Haller and Matthias Becker. Lars serves as an assistant for courses including Compilers and Execution Environments (ID2202), Computer Technology and Components (IS1500), and Computer Technology, Basic Course (IS1200). Email: larshum@kth.se

Martin BerglundView profile

Associate Professor

• Fundamental Algorithms
• Automata Theory
• Machine Learning Theory
• +3 more

Martin Berglund is an Associate Professor at the Department of Computing Science, Umeå University. His research focuses on fundamental algorithms, automata theory, and machine learning theory, with applications in parsing, tokenization, and regular expression semantics. Research Interests : Automata theory, formal languages, parsing techniques, and computational complexity. Teaching : Courses in programming, theory of computation, and computational complexity. Leadership : Head of the Foundations of Language Processing research group.

• Children's and Young Adult Literature
• Literary Didactics
• Fiction and Health
• +2 more

Helen Asklund is a Senior Lecturer in Literary Studies at Mid Sweden University's Department of Humanities and Social Sciences (HSV), where she teaches literary studies, literary didactics, and creative writing across teacher training programs. Since 2022, she serves as Deputy Dean for English linguistics, literary studies, and Swedish language programs. Concurrently, Asklund works as a university pedagogical developer in the Division for Research and Educational Support, teaching higher education pedagogy courses and mentoring for the national course 'Assessing Pedagogical Skills.' She represents HSV in Mid Sweden University's ULF group, fostering university-school collaborations, and co-edits the report series Educational Studies at Mid Sweden University . Her research explores four interconnected domains: Children's and young adult literature, with specialization in horse books and reading practices Literary didactics and educational methodologies Therapeutic applications of fiction in health contexts Higher education pedagogy and faculty development Current projects include an anthology on horse book readers' experiences (2026) and a historical overview of Swedish horse literature. Asklund's publications (2017–2025) demonstrate strong interdisciplinary focus, with 67% analyzing children's literature (particularly equine narratives and mother-daughter dynamics), 20% addressing higher education pedagogy, and 13% examining fiction's role in health and society. Her work frequently employs reader-response theory, feminist analysis, and didactic frameworks. Awards & Recognition: Meritorious Teacher (Swedish: Meriterad Lärare ) for outstanding pedagogical contributions. Academic Service: Editorial board member for pedagogical publication series Committee for Pedagogical Qualifications member Pedagogical expert for faculty assessments Education & Credentials: PhD in Literary Studies (Uppsala University, 2008) Teaching Qualification for Upper Secondary Schools (2012) Master in Library and Information Science (University of Borås, 2013) Upper Secondary Teaching Degree in Swedish/English (Malmö University, 2000)

• Cybersecurity
• Network Science
• Modeling and Simulation
• +7 more

Viktor Engström is a doctoral student at the Kungliga Tekniska Högskolan (KTH Royal Institute of Technology) , affiliated with the Center for Cyber Defense and Information Security (CDIS) and the Division of Network and Systems Engineering (NSE) . His research focuses on dynamic cyber attack simulations using attack graphs, particularly through the development of the Dynamic Meta Attack Language (DynaMAL) .

Philipp HallerView profile

Associate Professor

• Programming Languages
• Type Systems
• Concurrency
• +11 more

Philipp Haller is an Associate Professor in the Department of Computer Science at KTH Royal Institute of Technology, affiliated with the Theoretical Computer Science Group, Digital Futures, and WASP. He holds a PhD from EPFL (2010) and has held research positions at Stanford and EPFL, and industry roles at Typesafe Inc. Research Interests: His work centers on programming language design, concurrency (especially actor and futures models), distributed programming, type systems, and serverless computing. He is a leading contributor to the Scala language, having co-created its async/await syntax and futures library. His recent research includes the Portals framework for stateful serverless applications and formal models for consistency and concurrency safety. Publication Trends: His recent work (2020–2024) shows a strong focus on safe and scalable concurrency, stateful serverless systems, formal verification of language features, and distributed data consistency. He frequently publishes in top venues like ECOOP, OOPSLA, and PLDI, often combining theory with practical implementations in Scala. 2019 ACM SIGPLAN Programming Languages Software Award (for Scala) 2017 Teacher of the Year, EECS, KTH Advising and Grants: He supervises PhD students including Jonas Spenger, Xin Zhao, and Viktor Palmkvist. He led the Software Development Academy, a reskilling program for immigrants funded by the Wallenberg Foundations. He actively participates in academic service, co-chairing workshops like PLACES and AGERE!, and serving on program committees for OOPSLA, ECOOP, and POPL. Labs and Teams: He is part of the Theoretical Computer Science Group at KTH and leads research related to the Portals framework, which unifies dataflow and actor models for edge and serverless computing.

• Functional Programming
• Domain-Specific Languages
• Climate Impact Research
• +7 more

Patrik Jansson is a Professor of Computer Science at Chalmers University of Technology since 2011, with joint affiliation to Gothenburg University. His work bridges Functional Programming, Domain-Specific Languages (DSLs), and applications to Climate Impact Research, Fusion, and Physics.

Yi WangView profile

Professor

• Embedded Systems
• Real-Time Systems
• Real-Time Scheduling
• +7 more

Yi Wang is a Professor of Embedded Systems at the Department of Information Technology, Uppsala University , Sweden. He leads research in real-time and embedded systems with a focus on modeling, analysis, and implementation of safety-critical applications. He is affiliated with the Embedded Systems Group and serves as a Principal Investigator (PI) in major research centers such as UPMARC and projects like CUSTOMER (ERC Advanced Grant), CoDeR-MP, and CERTAINTY. Research Interests: Yi Wang’s work centers on Embedded Systems Design, Real-Time Scheduling, Multicore Programming, and Model-Checking of Real-Time Systems . His research addresses fundamental challenges in timing predictability, schedulability analysis, and the verification of complex real-time systems. He has made significant contributions to the digraph real-time task model, mixed-criticality systems, and timing analysis of ROS 2 systems. His work bridges theory and practice, often resulting in deployable tools and formal methods for industrial applications. Recent Research Trends: His most recent publications (2023–2025) focus on optimizing real-time performance in ROS 2, managing parallel task graphs with resource contention, improving GPU-based inference on embedded platforms, and enhancing timing predictability in multithreaded executors. These works reflect a strong trend toward applying formal real-time theory to modern robotics, AI integration, and multicore embedded architectures. Scientific Tools and Leadership: He is a key contributor to foundational tools in real-time systems: UPPAAL – Model checking for timed automata TIMES – Schedulability analysis and code generation CATS – Compositional analysis of timed systems TIMES-Pro – Based on the digraph real-time task model Advising and Research Funding: Yi Wang has supervised numerous PhD students and postdocs. He has led or participated in multiple large-scale funded projects supported by the Swedish Research Council (VR), the Swedish Foundation for Strategic Research (SSF), and the European Commission (FP7, ERC). These include UPMARC (10-year Linnaeus center), CoDeR-MP (with ABB and SAAB), SAVE++ (with VOLVO), and CREDO. Laboratories and Research Groups: He is a core member of the Embedded Systems Group at Uppsala University and leads research within the UPMARC center, which focuses on programming models and analysis techniques for multicore architectures. His lab develops formal methods and tools to ensure correctness and timing guarantees in embedded and cyber-physical systems.

• Computer Science
• Concurrency
• Programming Languages
• +7 more

Konstantinos Sagonas is a Senior Lecturer/Associate Professor at Uppsala University's Department of Information Technology. His work bridges theoretical and practical aspects of computer science, focusing on concurrency, formal verification, and functional programming in Erlang. Despite his self-identification as a "terrible e-mail responder," he encourages phone contact for direct communication. University: Uppsala University Department: Department of Information Technology Academic Rank: Senior Lecturer/Associate Professor His research spans from stateless model checking and dynamic partial order reduction for concurrent systems to static analysis and type systems in functional programming. Recent work explores IoT protocol testing via fuzzing and symbolic execution, fine-grain memory coherence for security, and automated detection of state machine bugs in network protocols. Key publication trends include formal methods (2024: "Testing IoT Protocol Requirements"; 2023: "Tailoring Stateless Model Checking for Event-Driven Programs") and concurrent data structures (2021: "Lock-free Contention Adapting Search Trees"). Earlier contributions focus on Erlang optimization (2002-2018) and logic programming tabling (1999-2006).

Sandro StuckiView profile

Lecturer

• Programming Languages
• Formal Methods
• Type Systems
• +4 more

Sandro Stucki is a Lecturer in the Department of Computer Science and Engineering at Chalmers University of Technology. He has previously worked as an applied scientist at Amazon and as a postdoctoral researcher at Chalmers University of Technology and the University of Gothenburg. He completed his doctoral studies at the Programming Methods Laboratory (LAMP) at EPFL under the supervision of Professor Martin Odersky. His research focuses on programming languages, with particular interest in formal methods, type systems and theory, and the semantics and implementation of domain-specific languages. He applies formal methods and type theory to problems in privacy and security, investigates type safety of Scala and related type systems, and develops type soundness proofs using Agda. His work also includes designing domain-specific languages for modeling probabilistic and stochastic systems, especially biochemical systems. He has contributed to the Scala ecosystem by developing a GNU/Emacs mode for Kappa, a modeling language for systems biology. His recent publications demonstrate strong expertise across programming language theory, formal verification, privacy-preserving systems, and applications in systems biology. His work bridges theoretical foundations with practical applications, particularly in the Scala programming language ecosystem. Stucki is actively involved in academic service, having served on program committees for numerous conferences including ECAI, GPCE, NWPT, and as a steering committee member for the Scala Symposium series. He has also organized several academic events, including the Scala Symposium 2016. He currently teaches courses on Data Science and AI, Fundamentals of Program Development, and Neuro-symbolic AI at Chalmers/Gothenburg University, and has previously taught courses on Parallel Functional Programming, Principles of Concurrent Programming, and Types and Programming Languages.

Jonas LundbergView profile

Senior Lecturer

• Machine Learning
• Program Analysis
• Software Engineering
• +3 more

Jonas Lundberg is a Senior Lecturer in Computer Science at Linnaeus University since 2000, holding a Ph.D. in Theoretical Physics (Umeå University, 1994) and a second Ph.D. in Computer Science (Linnaeus University, 2012). He teaches foundational and advanced courses in programming, machine learning, and compiler design. His research focuses on data-intensive computing, program analysis, and cross-disciplinary projects like the Nordic Tweet Stream (NTS), analyzing social media data from Nordic countries. He leads the Computer Engineering program and participates in CDIO initiatives. Education: Ph.D. in Theoretical Physics, Umeå University (1994) Ph.D. in Computer Science, Linnaeus University (2012) Research interests include machine learning applications in software engineering, program analysis techniques for large codebases, and digital humanities projects leveraging big data. He co-founded the DISA research center (2016) to address challenges in data collection, analysis, and utilization. Recent work involves developing memory-efficient program analysis frameworks and detecting anti-democratic discourse in social media. Key projects include managing the Master's program in Computer Science and advancing self-adaptive systems engineering. His contributions span 70+ publications in venues like IEEE Transactions, Journal of Systems and Software, and conferences such as SAC and DHN. He is affiliated with research groups like Data Intensive Software Technologies (DISTA) and co-leads the Nordic Tweet Stream initiative. His work bridges computational methods with humanities, emphasizing real-time data analysis and cross-disciplinary collaboration.

Alexandru DuraView profile

Researcher

• Programming Languages
• Software Engineering
• Static Program Analysis
• +3 more

Alexandru Dura is a Doctoral Student and Researcher at the Department of Computer Science, Faculty of Engineering, Lund University. He is affiliated with the ELLIIT initiative (Linköping-Lund) on IT and mobile communication and serves as a Profile Area Member for AI and Digitalization at LTH. His work bridges theoretical program analysis with practical software development needs through declarative approaches. His research focuses on static program analysis, bug pattern detection, and declarative specification languages, with emphasis on incremental evaluation techniques. Key contributions include developing Clog for C static code checkers and JavaDL for Java bug pattern detection, which optimize analysis efficiency through automatic incrementalization. His fingerprint highlights expertise in Syntactics (100%), Pattern Matching (90%), and Specification Languages (50%). Recent publications demonstrate a clear trend toward fully declarative frameworks that simplify static analysis tool development while maintaining performance. His work addresses real-world challenges in program verification, particularly for performance-critical systems where traditional analysis methods become computationally prohibitive. Dura leads the active dissertation project "Performance bug detection through combined static and dynamic program analysis" (funded since October 2018), collaborating with Professor Carl Reichenbach. This research integrates multiple analysis techniques to identify subtle performance issues in software systems.