I’m a Postdoctoral Research Fellow in the NeuroAI and Geometry Data Analysis Lab at Harvard University. I work on predictive representations in artificial and biological neural networks, understanding their geometry, and how they can be used as world models in RL.
I completed my PhD in the Zenke Lab at the Friedrich Miescher Institute in Basel, Switzerland. I worked on understanding mathematical principles behind predictive self-supervised learning to see whether and how the brain could learn in a similar way. You can read more about this in my dissertation. 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 playing with robotic arms as an intern with the Robotics AI team in Amazon, Berlin.
My non-research interests include rock climbing, hiking, and most things outdoors. I also enjoy reading about history and philosophy of science, economics, and am a big fan of science fiction.
Recent Publications
Mohammadi, A.G.*, Halvagal, M. S.*, & Zenke, F.
bioRxiv 2026
Halvagal, M. S.*, Laborieux, A.*, & Zenke, F.
Advances in Neural Information Processing Systems 36 (NeurIPS 2023)
News
- I’ll be presenting two posters at Cosyne! (March 2026)
- I was awarded a Swiss National Science Foundation (SNSF) Postdoc Mobility Fellowship (2026-2028)
- I started my postdoc at Harvard University (July 2025)
- I defended my PhD thesis titled “Predictive Self-Supervised Learning in Brains and Machines” (April 2025)
- I presented a talk and tutorial at the Janelia Junior Scientist Workshop for Theoretical Neuroscience 2023
- I presented a poster at NeurIPS 2023 (main conference)