| Sep 01, 2026 | I’m excited to share that I’ll be joining Columbia University’s Zuckerman Institute and Center for Theoretical Neuroscience as a postdoctoral researcher, working with Ken Miller and Kim Stachenfeld. My research will explore learning, memory, and decision-making at the intersection of computational neuroscience, reinforcement learning and NeuroAI. |
| Jul 06, 2026 | Presented our work, “Balancing Plasticity and Stability with Fast and Slow Successor Features,” at International Conference on Machine Learning (ICML) in Seoul, South Korea! The work studies how learning across multiple timescales using a neuro-inspired synaptic consolidation mechanism can help RL agents retain useful predictive representations while adapting to continuously changing environments. |
| Jun 01, 2026 | Joined Natural Intelligence in Frankfurt as a Research Scientist Intern, working on biologically inspired recurrent models for Reinforcement Learning. |
| May 30, 2026 | Graduated with a PhD in Computer Science from McGill University and Mila, advised by Prof. Doina Precup and Prof. Blake Richards. My dissertation explored how principles inspired by biological learning and memory can be used to develop more adaptive Continual Reinforcement Learning systems. In particular, I studied predictive representations — Successor Representations and Successor Features — together with neuro-inspired synaptic consolidation mechanisms to better balance plasticity and stability in continually learning agents. |
| Apr 30, 2026 | Our latest work (together with Doina Precup and Blake Richards) on continual reinforcement learning and biologically inspired memory systems, “Balancing Plasticity and Stability with Fast and Slow Successor Features,” has been accepted to International Conference on Machine Learning (ICML) 2026. See you in Seoul, Korea! 🇰🇷🧠🚀 |
| Apr 23, 2026 | Gave an invited research talk at New York University in Marcelo Mattar’s lab on continual reinforcement learning, predictive representations, and biologically inspired learning systems. |
| Apr 21, 2026 | Visited the Zuckerman Institute at Columbia University to discuss recent work on continual reinforcement learning and computational neuroscience. |
| Mar 24, 2026 | Participated in the Foundation Models Winter School in Amsterdam, exploring recent advances in foundation models. Hosted by Ellis unit Amsterdam 🇳🇱 |
| Feb 20, 2026 | Excited to share that I have successfully defended my PhD thesis! Thank you to my examiners, Prof. Mark Crowley (University of Waterloo), Prof. Ross Otto (McGill) and my advisors Blake and Doina! |
| Jan 17, 2026 | Excited to kickstart the new year to share that our work on “Do Successor Features resemble Hippocampal Place Cells?” has been accepted at Cosyne 2026! See you all in Portugal! 🇵🇹🧠🚀 |
| Nov 24, 2025 | Announcement_11 |
| Nov 20, 2025 | Announcement_10 |
| Nov 13, 2025 | Announcement_9 |
| Nov 12, 2025 | Announcement_8 |
| Oct 20, 2025 | Announcement_7 |
| Sep 28, 2025 | Announcement_6 |
| Mar 10, 2025 | Invited by the Integrate and Fire Seminar organisers at McGill University to share my perspective on the discussion theme of the night, “How Intelligent is AI?” Through sharing my own work on reinforcement learning, I presented some evidence which showed that agents learned solely on rewards can obtain some form of intelligence. |
| Jan 30, 2025 | Announcement_4 |
| Sep 28, 2024 | Announcement_1 |
| Sep 25, 2024 | My first research paper titled “Learning Successor Features the Simple Way,” on which I am the primary first author, co-authored with Arna Ghosh, Christos Kaplanis, Blake Richards and Doina Precup, has been accepted to the Neural Information Processing Systems conference (NeurIPS) a top-tier machine learning conference with a very selective 25.8% acceptance rate. Check out the blogpost and the paper! 🎉 |
| Feb 29, 2024 | Presented our recent work on Continual RL using Successor Features @ Computational and Systems Neuroscience (COSYNE) in Lisbon, Portugal, with a selective 51.6% acceptance rate. 🇵🇹🧠 |