Patrik Jansson
Professor of Computer Science
Contact
Patrik Jansson
Professor of Computer Science
+46317725415
Computer Science and Engineering
Chalmers University of Technology
Room number: EDIT-6452
My office is in the EDIT building of campus Johanneberg, near Rännvägen 6.
Patrik Jansson (PhD, Chalmers 2000), Professor of Computer Science since 2011 at Chalmers U. of Tech. and Gothenburg U. in Sweden. His main research areas are Programming Languages, Functional Programming, Domain-Specific Languages, and their application to climate, physics, etc.
Google Scholar Profile
DBLP publication list
Mastodon: @[email protected]
Google Scholar Profile
DBLP publication list
Mastodon: @[email protected]
Publications
Domain-specific tensor languages
Jean-Philippe Bernardy, Patrik Jansson
J. Funct. Prog., vol. 35, Cambridge University Press (CUP), 2025
Fluid and kinetic studies of tokamak disruptions using Bayesian optimization
Ida Ekmark, Mattias Hoppe, Tünde Fülöp, Patrik Jansson, Liam Antonsson, Oskar Vallhagen, István Pusztai
Journal of Plasma Physics, 2024-06, 2024
Bayesian optimization of massive material injection for disruption mitigation in tokamaks
I. Pusztai, I. Ekmark, H. Bergström, P. Halldestam, P. Jansson, M. Hoppe, O. Vallhagen, T. Fülöp
Journal of Plasma Physics, vol. 89(2), 2023
Level-p-complexity of Boolean functions using thinning, memoization, and polynomials
Julia Jansson, Patrik Jansson
Journal of Functional Programming, vol. 33, 2023
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Projects
OptiFun: Optimising fusion with generative programming
The aim of this project is to combine numeric and symbolic methods to accelerate first-principles simulations and enable optimisation of fusion confinement designs. PIs: Tünde Fülöp (Physics) and Patrik Jansson (CSE) 2022-2023
GRACeFUL: Global systems Rapid Assessment tools through Constraint FUnctional Languages
I was site- and workpackage leader in the EU-project (GRACeFUL, 2015-18) granted from the FETPROACT1 call with a budget of 2.4M EUR over three years.
DSLsofMath: Domain-Specific Languages of Mathematics
The project has resulted in a BSc level course, a textbook, a GitHub repository and a few other publications.
Posts
Optimization under uncertainty
A new preprint is now up on arXiv dealing with opimization under uncertainty (Nicola Botta, Patrik Jansson, Tim Richter) PDF: arxiv.org/pdf/2503.18561 Link: arXiv:2503.18561 Abstract: One of the most ubiquitous problems in optimization is that of fi... (Link)
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Exploring level-p-complexity for subclasses of Boolean functions
In their MSc thesis [1], Arvid Rydberg and Selina Sand Engberg explored the complexity of Boolean functions (functions from n bits to one bit). Measuring their evaluation cost, especially using the probabilistic level-p-complexity (D_p(f)), is an inte... (Link)
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Theories and Tools for Climate Policy Exploration
I've just submitted a grant proposal about "Theories and Tools for Climate Policy Exploration" to FORMAS (a government research council for sustainable development). If funded, it would mean a team consisting of me, Nicola Botta, a post-doc, and two st...
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Functional multi-objective optimization under uncertainty
I have just submitted a grant application to the Swedish Science Council with the title "Functional multi-objective optimization under uncertainty". If granted it would pay for a PhD student + supervision time. The topic is an update on the series of ...
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Cambridge visit
I've just given a talk in Cambridge on "Optimising Sustainable Energy with Functional Programming" and the recording is available on YouTube: https://youtu.be/NhFhJS4NHDM?si=HlRyz0BdXUdgLvNO as part of the Cambridge Energy and Environment Group talks...
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Courses
Domain-Specific Languages of Mathematics
BSc level course Domain-Specific Languages of Mathematics (course code DAT326 at Chalmers and DIT982 at UGOT).
BSc projects on "DSLsofMath for other courses"
A recurring BSc project theme for the last few years: develop you own DSLsofMath-inspired material for a topic of your choice.
Functional Programming and Climate Impact Research
This is a course aimed at PhD students or MSc students interested in the application of functional programming, domain-specific languages, and dependent types to climate impact research.