Miguel Vasco

{mi-ghel v-ah-s-co}

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I am a Postdoctoral fellow at the Division of Robotics, Perception and Learning, at KTH Royal Institute of Technology, advised by Danica Kragic. My goal is to build inteligent agents that are multimodal (able to process different modalities), robust (to changes in their environment) and adaptable (to human preferences).

I am a former intern at Sony AI and RSS Pioneer. I am also the co-creator of the Talking Robotics podcast.

I have a PhD in Computer Science (summa cum laude) from Tecnico, University of Lisbon, where I was supervised by Ana Paiva and Francisco S. Melo. I have an MSc and BSc in Engineering Physics from Tecnico, University of Lisbon.

news

Oct 16, 2024 Paper accepted at TMLR and workshop paper in SciForDL at NeurIPS! Congrats to Alfredo and Nona!
Sep 26, 2024 Two Papers Accepted at NeurIPS 2024 (Spotlight, Poster). Congrats to Farzaneh and Bernardo!
Sep 04, 2024 Won the “Best PhD Thesis in AI in Portugal (2023)”, awarded by the Portuguese Association for Artificial Intelligence (APPIA).
Aug 10, 2024 Our paper “A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo” won an Outstanding Paper Award at RLC 2024!

selected publications

  1. Can Transformers Smell Like Humans?
    Farzaneh Taleb, Miguel Vasco, Antonio H. Ribeiro, and 2 more authors
    In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
  2. NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
    Bernardo Esteves, Miguel Vasco, and Francisco S. Melo
    In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024
  3. RLC
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    A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo
    Miguel Vasco*, Takuma Seno*, Kenta Kawamoto, and 3 more authors
    Reinforcement Learning Journal, 2024
  4. Geometric Multimodal Contrastive Representation Learning
    Petra Poklukar*Miguel Vasco*, Hang Yin, and 3 more authors
    In Proceedings of the 39th International Conference on Machine Learning, 2022
  5. How to Sense the World: Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning Agents
    Miguel Vasco, Hang Yin, Francisco S. Melo, and 1 more author
    In 21st International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2022
  6. Neural Networks
    nn_2022.png
    Leveraging hierarchy in multimodal generative models for effective cross-modality inference
    Miguel Vasco, Hang Yin, Francisco S. Melo, and 1 more author
    Neural Networks (2021 Special Issue on AI and Brain Science: Brain-inspired AI), 2022
  7. Playing Games in the Dark: An Approach for Cross-Modality Transfer in Reinforcement Learning
    Rui Silva, Miguel Vasco, Francisco S. Melo, and 2 more authors
    In 19th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2020