Scholar
Miguel Vasco
Google Scholar ID: Of2hDmMAAAAJ
Postdoctoral Researcher KTH Royal Institute of Technology
Citations & Impact
Citations
272
H-index
7
i10-index
6
Publications
20
Co-authors
9
list available
Publications
Resume (English only)
Academic Achievements
- 1. Paper 'Human-Aligned Image Models Improve Visual Decoding from the Brain' accepted at ICML 2025.
- 2. Preprint 'Humans Co-exist, So Must Embodied Artificial Agents' on arXiv.
- 3. Paper on super-human autonomous racing won Outstanding Paper Award at RLC 2024.
- 4. Two papers accepted at NeurIPS 2024, one exploring foundation models of chemical data for human olfaction and another on test-time compute for agents with arbitrarily large observations.
Research Experience
- Currently a Postdoctoral Researcher at KTH Royal Institute of Technology, advised by Danica Kragic. Former RSS Pioneer and research intern at Sony AI.
Education
- Ph.D. from Instituto Superior Tecnico (Lisbon, Portugal), advisor unknown. Awarded Best PhD Thesis in AI in Portugal by the Portuguese Association for Artificial Intelligence (APPIA).
Background
- Research Interests: Multimodal reinforcement learning, human-robot coexistence. Professional Field: Artificial Intelligence. Brief Introduction: Currently a Postdoctoral Researcher at KTH Royal Institute of Technology, with a long-term goal to build multimodal artificial agents that naturally coexist with humans in real and virtual environments.
Miscellany
- Organizing the Reinforcement Learning and Video Games workshop at RLC 2025.
