Scholar
David Broman
Google Scholar ID: Jvtpzw8AAAAJ
Professor, KTH Royal Institute of Technology
Citations & Impact
Citations
1,979
H-index
21
i10-index
35
Publications
20
Co-authors
60
list available
Publications
Resume (English only)
Academic Achievements
- 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.
- Paper accepted to The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024). Paper title: Learning Formal Mathematics From Intrinsic Motivation (Oral Presentation).
- Paper accepted to the Conference on Empirical Methods in Natural Language Processing (EMNLP 2024). Paper title: Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs (Oral Presentation).
- Paper accepted to the ACM SIGPLAN International Conference on Software Language Engineering (SLE 2024). Paper title: Trellis: A Domain-Specific Language for Hidden Markov Models with Sparse Transitions.
- Paper accepted to the ACM SIGPLAN International Conference on Software Language Engineering (SLE 2024). Paper title: Statically and Dynamically Delayed Sampling for Typed Probabilistic Programming Languages.
- PhD student Gizem Caylak successfully defended her Licentiate thesis on October 14, 2024. Title: Automated Optimizations for Inference in Probabilistic Programming Languages.
- PhD student Viktor Palmkvist successfully defended his PhD thesis on October 8, 2024. Title: Abstraction, Composition, and Resolvable Ambiguity in Programming Language Implementation.
- General Chair for the Forum on Specification & Design Languages (FDL), Stockholm, September, 2024.
- Paper accepted to the IEEE Transactions on Automatic Control. Paper title: Exact Worst-Case Execution-Time Analysis for Implicit Model Predictive Control, 2024.
- Paper accepted to the 33rd European Symposium on Programming (ESOP 2024). Paper title: Suspension Analysis and Selective Continuation-Passing Style for Universal Probabilistic Programming Languages.
Research Experience
- Professor at KTH Royal Institute of Technology, Head of Division for Software and Computer Systems (SCS), Associate Director Faculty for Digital Futures.
Background
- Research interests include programming languages and compilers, real-time and cyber-physical systems, and probabilistic machine learning.
Miscellany
- Contact: dbro@kth.se; Office: +46 8 790 42 74; Cellular: +46 73 765 20 44, +1 650 304 4777; Social media: Twitter, LinkedIn
