About me

I’m a PhD student in the Zenke Lab at the Friedrich Miescher Institute in Basel, Switzerland. I work on understanding the mathematical principles behind predictive self-supervised learning in order to see if and how the brain could be learning in a similar way.

In the past, I studied Electrical Engineering at the Indian Institute of Technology in Madras, and Robotics at the École polytechnique fédérale de Lausanne. I also spent a fun half year interning with the Robotics AI team in Amazon, Berlin.

Publications

Implicit variance regularization in non-contrastive SSL
Implicit variance regularization in non-contrastive SSL
Halvagal, M. S.*, Laborieux, A.*, & Zenke, F.
Advances in Neural Information Processing Systems 36 (NeurIPS 2023)
[Paper] [Code]
The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks
The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks
Halvagal, M. S., & Zenke, F.
Nature Neuroscience
[Paper] [Code]
Inferring subjective preferences on robot trajectories using EEG signals
Inferring subjective preferences on robot trajectories using EEG signals
Iwane, F., Halvagal, M. S., Iturrate, I., Batzianoulis, I., Chavarriaga, R., Billard, A., & Millán, J. D. R.
2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)
[Paper]

Talks and Poster Presentations

  • (Upcoming) Will be presenting a poster at Bernstein 2024
  • Presented a talk and tutorial at the Janelia Junior Scientist Workshop for Theoretical Neuroscience 2023
  • Presented a poster at NeurIPS 2023 (main conference)
  • Presented a poster at the Self-Supervised Learning Workshop at NeurIPS 2022
  • Presented a poster at Bernstein 2022
  • Presented a poster at Cosyne 2022
  • Gave an online talk in the SNUFA Seminar Series