Scholar
Emil Carlsson
Google Scholar ID: VZhBQWQAAAAJ
Research Scientist
Citations & Impact
Citations
102
H-index
6
i10-index
5
Publications
18
Co-authors
13
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple research papers in leading AI/ML conferences such as NeurIPS and AISTATS. Some of the publications include:
- - Active preference learning for ordering items in- and out-of-sample (NeurIPS 2024)
- - Pure exploration in bandits with linear constraints (AISTATS 2024)
- - Cultural evolution via iterated learning and communication explains efficient color naming systems (Journal of Language Evolution, 2024)
- - Variational Quantum Optimization with Continuous Bandits (Under Submission, 2025)
- - Identifiable latent bandits: Combining observational data and exploration for personalized healthcare (ICML Workshop, 2024)
- - Learning Efficient Recursive Numeral Systems via Reinforcement Learning (AI for Math Workshop @ ICML, 2024)
- - Fast Treatment Personalization with Latent Bandits in Fixed-Confidence Pure Exploration (TMLR, 2023)
- - Towards Learning Abstractions via Reinforcement Learning (AIC, 2022)
- - Pragmatic reasoning in structured signaling games (CogSci, 2022)
- - Thompson sampling for bandits with clustered arms (IJCAI, 2021)
Research Experience
- Working at Sleep Cycle, focusing on the development of data-driven decision-making systems.
Education
- Ph.D. in Computer Science from Chalmers University of Technology.
Background
- Currently working as a Research Scientist at Sleep Cycle, focusing on developing reliable data-driven decision-making systems. Primary research interests are reinforcement learning and bandit algorithms, particularly in improving the efficiency and effectiveness of sequential decision processes.
Miscellany
- Can be reached at emil(at)sleepcycle(dot)com or on LinkedIn.
