David Broman

News and Events

• Paper accepted to the Forty-Third International Conference on Machine Learning (ICML). Paper title: Adaptive Reinforcement Learning for Unobservable Random Delays, 2026.

• Paper accepted to the 24th European Control Conference (ECC). Paper title: Advantage-Guided Diffusion for Model-Based Reinforcement Learning, 2026.

• On February 10, we celebrated the inauguration of our new Department, named the Department of Computing and Learning Systems (CLS). Deputy President Mikael E. Lindström cut the rope, and we had a very nice day with talks, panels, and poster sessions. Please see the group photo of the event here (cred. photo Dejan Kostic).

• Paper accepted to the journal Artificial Intelligence in Medicine. Paper title: Reinforcement learning for real-time adaptive radiotherapy, 2026.

• Paper accepted to the IEEE/ACM International Symposium on Code Generation and Optimization (CGO). Paper title: Fast Autoscheduling for Sparse ML Frameworks, 2026.

• We have formed a new department at EECS, called the Department of Computing and Learning Systems (CLS). I am very humbled and proud to be starting as the first head of department of this new organization. We just moved in to a newly renovated building at the KTH main campus, at Lindstedsvägen 30. Welcome!

• I would like to welcome our new postdoc, Viktor Palmkvist, who will work in our cross-disciplinary project DarkTree. The work concerns compiler techiques for probabilistic programming languages in general, and for domain-specific optimizations for phyologenetic applications in particular. Welcome Viktor!

• Welcome Xaver Davey, a new PhD student in our group, who started in the fall of 2025. Xaver recently graduated from Georgia Institute of Technology in the US and will work on the foundations of language models and their use within safety-critical software development.

• Paper accepted to the Journal of Systems Architecture. Paper title: Real-time probabilistic programming, 2025.

• Welcome Shubhra Mishra, a new PhD student in our group, who started in the fall of 2025. Shubhra recently graduated from Stanford University and is a WASP PhD student who will work on the foundations of language models, abstractions in programming languages, and new techniques for software and math development.

• Paper accepted to the ACM Transactions on Probabilistic Machine Learning. Paper title: Annotated Automatic Pruning of Universal Probabilistic Programming Languages, 2025.

• Paper accepted to the ACM International Conference on Architectural Support for Programming Languages and Operating (ASPLOS 2025). Paper title: Automatic Tracing in Task-Based Runtime Systems.