Probabilistic Programming Languages Professors and Supervisors in Sweden | ApplySharif

Active facets:

Find Academic Supervisors

Find and connect with academic supervisors, professors, and scholars for your research journey.

Showing 1-15 of 18 supervisors

Profile data may be stale. It is sourced from public faculty pages.

Pontus JohnsonView profile

Professor

KTH Royal Institute of TechnologySweden

Pontus Johnson is a Professor at the KTH Royal Institute of Technology in Stockholm, Sweden. He leads the Center for Cyber Defense and Information Security (collaborating with Swedish Armed Forces, FRA, MSB, FOI, FHS) and serves as vice director of Cybercampus Sweden since 2024. His research focuses on cybersecurity , enterprise architecture analysis , and probabilistic threat modeling , particularly through his development of the Meta Attack Language (MAL) for simulating cyber attacks on networked systems. Education: MSc in Computer Science, Lund Institute of Technology (1997) PhD in Computer Science, KTH (2002) Docent title, KTH (2007) Leadership Roles: Director, Center for Cyber Defense and Information Security (2013–present) Vice Director, Cybercampus Sweden (2024–present) Board Member, Swedish Research Council (2025–present) Deputy Chair, Swedish Royal Academy of Engineering Sciences (IVA) Board (2024–present) His work spans cybersecurity research , attack simulation methodologies , and enterprise architecture frameworks . He has developed tools like securiCAD (acquired by Google) and pwnPr3d for probabilistic threat modeling. His 15 most recent publications highlight advancements in graph-based attack simulations , automated security assessments , and AI applications in cyber defense . Scientific recognition includes: Listed among Tech Awards Sweden's 50 Most Influential People in Swedish Tech (2022, 2023) Discovery of vulnerability in the Universal Turing Machine (2021) He supervises 16 PhD students and alumni (2005–2024), including Simon Gökstorp , Jakob Nyberg , and Sotirios Katsikeas . His academic service includes over 50 program committee roles and leadership positions in international conferences. He contributes to both academic and public domains through media appearances (SVT, Aftonbladet), courses in ethical hacking , and industry collaboration via his role at Google (20% of his time). His research group Software Systems Architecture and Security (SSAS) focuses on predictive security frameworks and system-of-systems analysis.

Official University Profile

Hedvig KjellströmView profile

Professor

KTH Royal Institute of TechnologySweden

Hedvig Kjellström is a Professor at the Division of Robotics, Perception and Learning within the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology. She holds significant affiliations with the Swedish e-Science Research Centre and the Max Planck Institute for Intelligent Systems in Germany. Her work spans multiple interdisciplinary domains and she serves as Editor-in-Chief for CVIU and was Program Chair for CVPR 2025. Her research centers on Computer Vision as a sub-field of AI, with three interconnected themes: Computational Aesthetics (exploring aesthetic aspects of human communicative behavior), Communicative Behavior (developing models of how humans and animals perceive and produce non-verbal communication), and Embodied Artificial Intelligence (creating methodologies for robots and autonomous agents to perceive the world through sensors, primarily vision). Her work has significant applications in medical diagnostics, animal welfare, human-robot interaction, and creative arts. Analysis of her recent publications reveals a strong trend toward multimodal AI systems that integrate vision, language, and action understanding. Her research increasingly focuses on animal-centered applications, particularly equine pain detection and behavior analysis, while maintaining strong foundations in human communication modeling, gesture recognition, and 3D reconstruction techniques. The interdisciplinary nature of her work bridges computer science with veterinary medicine, neuroscience, and performing arts. Hedvig Kjellström actively supervises numerous PhD and Master's students across various projects and maintains extensive collaborations with institutions including Karolinska Institutet, Swedish University of Agricultural Sciences, and international partners. Her research is supported by major funding bodies including WASP, VR, and SeRC. She leads or participates in several notable projects including OrchestrAI (communication between conductor and orchestra), ANITA (Animal Translator), MARTHA (3D horse motion analysis), and STING (synthesis and analysis with transducers and invertible neural generators). Her work with ACAI (Animal Centered Artificial Intelligence), which she co-founded and directs, demonstrates her commitment to applying AI for animal welfare.

Official University Profile

Gustav HenterView profile

Assistant Professor

KTH Royal Institute of TechnologySweden

Gustav Henter is an Assistant Professor in Intelligent Systems at KTH Royal Institute of Technology, specializing in Machine Learning. He is affiliated with the Division of Speech, Music and Hearing (TMH) within the School of Electrical Engineering and Computer Science. His research focuses on deep generative models for applications like speech synthesis, 3D character animation, and human-computer interaction. He holds a Docent degree from KTH and has held post-doctoral positions at the University of Edinburgh and the National Institute of Informatics in Tokyo. Education: PhD in Electrical Engineering (KTH, 2013), MSc in Engineering Physics (KTH, 2007). He supervises doctoral students in areas like gesture synthesis and multimodal interaction. His work is supported by grants from the Wallenberg AI, Autonomous Systems, and Software Program (WASP) and South Korea's MOTIE. He co-founded Motorica AB to commercialize motion synthesis research. Awards include Best Paper Awards at ICMI 2020 and IVA 2020, and recognition for student theses. His research spans generative AI, perceptual evaluation, and robust statistical models. He organizes the GENEA Challenge and Workshop series for gesture generation benchmarking.

Official University Profile

Alejandro RussoView profile

Professor

Chalmers University of TechnologySweden

Alejandro Russo is a Professor at Chalmers University of Technology , specializing in Information Flow Control (IFC) , Secure Programming Languages , and Functional Programming . His research bridges theoretical foundations and practical implementations, focusing on mitigating timing channels , covert channels , and data leakage in concurrent systems. Developed novel frameworks for Differential Privacy with provable accuracy bounds Pioneered COWL integration for browser security and instruction-based scheduling to prevent cache timing attacks Led major projects like HIPSTER (hybrid static/dynamic IFC) and AppFlow (practical IFC deployment) His publications reveal expertise in security libraries for Haskell and Python , with a focus on faceted execution , label manipulation , and mechanized security proofs . Students under his supervision have explored topics ranging from secure eDSLs to privacy-preserving compilation techniques . Scientific awards : Google Research Award (2011) for Python taint analysis Advising and grants : Principal Investigator for VR , STINT , and Google Research Award Supervised 12+ PhD and Master’s students in security and functional programming research

Official University Profile

Måns MagnussonView profile

Associate Professor

Uppsala UniversitySweden

Måns Magnusson is an Associate Professor at the Department of Statistics, Uppsala University, with affiliations at the Institute for Analytical Sociology (Linköping University) and the Institute for Future Studies. His work bridges Bayesian statistics, probabilistic machine learning, and textual analysis, focusing on model evaluation, diagnostics, and inference algorithms. He contributes to computational social science and digital humanities through text-as-data methods. Research Themes: Bayesian inference, probabilistic machine learning, statistical inference from textual data Key Applications: Sociology, political science, law, education statistics, public health Current Projects: Improving probabilistic programming generalizability (Swedish Research Council grant), SWERIK research infrastructure (Riksbankens jubileumsfond) His recent publications emphasize text mining, model comparison, and legal data challenges. He has developed tools for national ID number validation, hate crime estimation, and parliamentary corpus construction. Notable awards include the Cramér Prize (2018), Statistician of the Year (2023), and membership in the Swedish Young Academy (2023) and ELLIS (2024). Scientific Contributions: Botten Ada Bayesian election model, 'loo' package for cross-validation Collaborative Work: AI4Research sabbatical (2024), Riksbankens jubileumsfond funding Industry Background: Statistician roles at Swedish Agency for Education, Crime Prevention, and Public Health

Official University Profile

Mohamed Faouzi AtigView profile

Professor

Uppsala UniversitySweden

Mohamed Faouzi Atig is a Professor in Computer Systems at the Department of Information Technology, Uppsala University. His career spans roles as Senior Lecturer (2018-2021), Associate Senior Lecturer (2014-2018), and Researcher (2012-2018) at the same institution. He obtained his Doctoral Degree in Computer Science from the University of Paris Diderot-Paris 7 (2010) and a Master in Engineering from Tunisia Polytechnic School (2005). Current Role: Professor in Computer Systems Institution: Uppsala University Research Focus: Model checking, verification of infinite-state systems, weak memory models, automata theory, string constraints, concurrent program analysis His research explores formal methods for concurrent programs, weak memory models (TSO/PSO/POWER), automata theory for verification, and SMT solvers for string constraints. Recent work integrates graph neural networks with word equation solving and advances stateless model checking techniques. Key article trends include Weak Memory Model Verification (TSO, PSO, POWER) Stateless Model Checking Algorithms String Constraint Solvers (TRAU, Norn) Timed Automata and Multi-Pushdown Systems Mohamed Faouzi Atig has led collaborations on fence insertion procedures, timed pushdown automata, and database-driven system verification. His contributions are recognized through publications in top-tier conferences and journals.

Official University Profile

Sonia-Florina HorchidanView profile

Researcher

KTH Royal Institute of TechnologySweden

Sonia-Florina Horchidan is a doctoral researcher at the KTH Royal Institute of Technology in Stockholm, Sweden. She is affiliated with the Division of Software and Computer Systems within the School of Electrical Engineering and Computer Science (EECS), working under the supervision of Associate Professor Paris Carbone in the Data Systems Lab . Her academic activities include teaching assistant roles for courses in distributed systems and data storage paradigms. Research Focus: Graph Databases Machine Learning on Graphs Stream Processing Federated Learning with Privacy Guarantees Approximate Query Processing via ML Serverless Streaming Graph Analytics Scientific Contributions: Her recent publications at venues like EDBT, VLDB, and AI4DB explore intersections between graph data management and machine learning. Key themes include ML inference optimization in streaming systems, privacy-preserving health data forecasting, and innovative graph query execution models. Honors & Service: Co-authored Best Paper at DEEM 2022 Best Paper Award at VLDB 2023 PhD Workshop Program Committee Member, aiDM 2024 Reproducibility Committee Member, ACM SIGMOD/PODS

Official University Profile

Parosh AbdullaView profile

Professor

Uppsala UniversitySweden

Parosh Abdulla is a Professor in the Division of Computer Systems within the Department of Information Technology at Uppsala University, Sweden. His research focuses on formal methods and program verification with emphasis on concurrent systems, memory models, and verification techniques. With an extensive publication record spanning over three decades, he has established himself as a leading researcher in his field. His primary research interests include formal verification, model checking, concurrent systems analysis, memory models (particularly TSO and PSO), string constraints, timed automata, parameterized verification, and program analysis. His work addresses fundamental challenges in verifying complex software systems, especially those involving concurrency and weak memory models. In recent years, he has expanded his research to include quantum systems verification and the application of machine learning techniques to formal methods. Analysis of his recent publications (2023-2025) reveals a continued focus on advancing verification techniques for concurrent systems, with growing interest in quantum computing verification and the integration of graph neural networks with traditional formal methods. His work demonstrates consistent innovation in reducing the state space explosion problem while maintaining verification completeness. Professor Abdulla has established significant collaborations with researchers including Mohamed Faouzi Atig, Bengt Jonsson, and others, resulting in numerous high-impact publications in top-tier venues. His research has practical implications for developing reliable concurrent software systems and advancing formal verification methodologies. While specific details about his advising activities and grants aren't explicitly mentioned in the available information, his extensive publication record suggests active supervision of graduate students and involvement in multiple research projects. His work likely contributes to formal methods research groups at Uppsala University, focusing on verification tools and theoretical foundations of program analysis.

Official University Profile

Philipp RümmerView profile

Professor

Uppsala UniversitySweden

Philipp Rümmer is a Professor of Theoretical Computer Science at the University of Regensburg and a Senior Lecturer/Associate Professor at the Department of Information Technology , Uppsala University. His career spans over two decades of academic and industrial collaboration in formal verification, SMT solvers, and program analysis. Professor (2022–present), Faculty of Informatics and Data Science, University of Regensburg Senior Lecturer/Associate Professor (2018–present), Department of Information Technology, Uppsala University His research focuses on formal verification of software and embedded systems, SMT solvers (e.g., Princess, Norn), model checking (Eldarica), and integrating machine learning with verification techniques. He has pioneered tools like JayHorn for Java verification and Sloth for string constraint solving. Recent publications emphasize probabilistic verification of parameterized systems, timing analysis in embedded updates, heap invariants via Horn clauses, and graph neural networks in solving word equations. These works reflect his commitment to advancing formal methods through interdisciplinary approaches. Awards include: Oscarspris (2013), Uppsala University SAP Award for top Computer Science graduate (2005) Bosch Telecom Award for natural science excellence (1998) He has secured significant grants from the Swedish Research Council , Knut and Alice Wallenberg Foundation , and Microsoft Research , supporting projects like UPDATE (2020–2024) and WebSec (2018–2023). His leadership in tools such as Princess and Eldarica underscores his influence in automated reasoning and verification.

Official University Profile

Josephine SullivanView profile

Associate Professor

KTH Royal Institute of TechnologySweden

Josephine Sullivan is an Associate Professor at KTH Royal Institute of Technology, affiliated with the Division of Robotics, Perception and Learning. She is a core faculty member of Digital Futures, a cross-disciplinary research center addressing global challenges through digital technologies. Her research focuses on AI-driven environmental monitoring, disaster management, and deep learning applications in computer vision and remote sensing. She has supervised projects such as the fusion of radar and optical remote sensing for wildfire monitoring and contributes to initiatives like EO-AI4GlobalChange. Sullivan teaches advanced courses in deep learning, generative models, and machine learning at KTH, emphasizing hands-on training and research integration. Her work bridges theoretical advancements in neural networks with practical solutions for climate-related disasters, leveraging satellite imagery and time-series data. Recent projects highlight innovations in wildfire prediction datasets (Wildfirespreadts) and robust networks for disaster damage assessment (DisasterAdaptiveNet). She collaborates across disciplines at Digital Futures, contributing to labs and teams focused on AI ethics, sustainable technologies, and global change mitigation. Sullivan’s academic leadership includes roles as course examiner and responsible for multiple graduate programs in computer science and engineering.

Official University Profile

David BromanView profile

Professor

KTH Royal Institute of TechnologySweden

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.

Official University Profile

Sasikumar PunnekkatView profile

Professor

Dalarna UniversitySweden

Roles & Affiliations: Professor in Dependable Software Engineering at Mälardalen University (MDU), leading the Dependable Software Engineering research group. Former Head of Software Test & Reliability Engineering at Indian Space Research Organization (ISRO), Director of BITS Pilani KK Birla Goa Campus (Mar 2015–Aug 2016), and Visiting Researcher at Ericsson since 2022 (funded by SSF's strategic mobility program). Education: PhD in Computer Science from University of York, UK (1997), focusing on schedulability analysis of fault-tolerant systems (awarded Commonwealth Scholarship). Research Interests: Real-time systems, dependability, software engineering, safety-critical systems, cybersecurity, and industrial IoT. Key focus areas include fault-tolerant scheduling, safety-critical software design, and system-of-systems analysis. Funding & Projects: Led major EU projects (InSecTT, SUCCESS, DAIS, EUROWEB series) and national initiatives. Coordinated large EU educational collaborations with Western Balkans/Asia. Active in projects like FORA fog computing platform and TSN networks. Awards & Recognition: 6 Best Paper Awards, Senior Member of IEEE, and frequent contributor to conference program committees (ETFA, HASE, DATE, etc.). Grants & Labs: Recipient of SSF strategic mobility funding. Research group develops solutions for automotive systems, industrial automation, and safety-critical infrastructure.

Official University Profile

Gizem ÇaylakView profile

Researcher

KTH Royal Institute of TechnologySweden

Gizem Çaylak is a doctoral researcher at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Division of Software and Computer Systems. She is supervised by David Broman (principal) and Magnus Boman (co-supervisor). B.S. in Computer Engineering, Bilkent University (2012-2017) M.S. in Computer Engineering, Bilkent University (2017-2019) Ph.D. in Computer Science, KTH Royal Institute of Technology (2019-present) Her research focuses on deep probabilistic programming languages and their applications in clinical data analysis . She has contributed to bioinformatics research through her work on epistasis test prioritization using diverse SNP selection algorithms. Notable teaching experiences include workshops and courses in Computer Hardware Engineering , Computer Organization and Components , and Algorithms & Programming at KTH and Bilkent University. Her 2020 publication at the International Conference on Research in Computational Molecular Biology demonstrates her interdisciplinary work bridging computer science and computational biology.

Official University Profile

Sandro StuckiView profile

Lecturer

Chalmers University of TechnologySweden

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.

Official University Profile

Hazem TorfahView profile

Assistant Professor

Chalmers University of TechnologySweden

Hazem Torfah is a tenure-track Assistant Professor at the Computer Science and Engineering Department at Chalmers University of Technology, where he leads the Safe and Trustworthy Autonomous Reasoning lab (STARlab). Previously, he was a postdoctoral researcher in the EECS Department at UC Berkeley, USA, and obtained his Ph.D. in 2019 from Saarland University, Germany. His research focuses on developing theoretical foundations and techniques for constructing safe and reliable autonomous cyber-physical systems. Hazem earned his Ph.D. from Saarland University in 2019, followed by postdoctoral research at UC Berkeley. His educational background has positioned him at the forefront of formal methods research for autonomous systems. His research interests center on the formal specification, verification, and synthesis of cyber-physical systems, with a particular focus on quantitative approaches for verifying and explaining system behavior. He investigates methods to ensure safety and reliability in autonomous systems through runtime monitoring, specification mining, and assurance frameworks. His work bridges theoretical computer science with practical applications in autonomous driving and robotics. An analysis of his recent publications reveals a strong focus on runtime monitoring techniques for operational design domains, specification mining for predictive safety, and frameworks for runtime assurance of cyber-physical systems. His work frequently combines formal methods with machine learning to address safety challenges in autonomous systems, with applications primarily in autonomous driving. Hazem's research is funded by the Wallenberg AI, Autonomous Systems, and Software Program, reflecting the significance and potential impact of his work in the field of assured autonomy. He has supervised several Master's students, including Samuel Collier Ryder and Johannes Holmgren (2025), and Lucas Karlsson and George Kayembe (2024). His teaching includes courses on Formal Methods for Security, Oracle-Guided Inductive Synthesis, and Data Structures and Algorithms. As the leader of STARlab, Hazem directs research on safe and trustworthy autonomous reasoning, focusing on developing methods to ensure the reliability and explainability of autonomous cyber-physical systems through formal verification techniques.

Official University Profile