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 Research Associate at Mila, Québec AI Institute/Université of Montréal statistical inference & decision-making in human & machine learning PhD, Physics (IMPRS Physics of biological and complex systems), University of Göttingen MSc, Physics, University of Toronto BSc, Physics & Mathematics, University of Toronto |
 cebeuq [tod] alim [ta] mtamleup |
| Aug/Sept 2023 | Gave a 2-part talk on Transition Narratives and complex coordination problems at the ClimateMatchAcademy Monthly Seminar. (Part 1; Part 2). |
| July 2023 | Climate Match Academy is alive and running! Delivered a day of socioeconomic curriculum and organized our Discord server of 100s of students from over 100 countries! Check out our always-accessible-from-anywhere Jupyter Book. | June 2023 | Presented game theory of social norms work to Joel Leibo's group at Deepmind. |
| Dec 2022 | Presenting topic modelling at NeurIPS Workshop Tackling Climate Change with Machine Learning. |
| Nov 2022 | Giving a talk (open to the public) at University of Washington's data science seminar (recording). |
| Oct 2022 | Attended the IBM/DIMACS Workshop on Bridging Game Theory and Machine Learning for Multi-party Decision Making at Rutgers. |
| Sept 2022 | Giving a talk at the Montreal Computational & Quantitative Linguistics Lab . |
| Sept 2022 | Presenting carbon tax work for the first time at the Montreal AI Symposium! |
| Sept 2022 | Meriem's NoisET paper got accepted in Physical Chemistry A! |
| Sept 2022 | Our mixing times paper was accepted to NeurIPS! |
| June 2022 | RLDM2022 was great! Presented urgency work and ran our workshop on social alignment in human and machines. Workshop recording available on workshop website. |
| May 2022 | Urgency work published in PLoS Computational Biology. |
| Apr. 2022 | Presented our agent abstraction paper at ICLR workshop: From cells to societies: learning across scales. |
| Mar. 2022 | Gave a couple guest lectures in graduate-level math course on dynamical systems at UdeM. So nice to have the time in a talk to spell things out and discuss with students! |
| Feb. 2022 | Lyapunov spectra for RNNs paper accepted to Frontiers in Applied Mathematics & Statistics |
| Jan. 2022 | 2 accepted submissions to COSYNE: the neurodata validation of our decision-making model; and new work on noise robustness in recurrent neural nets with Colin Bredenberg. |
| Jan. 2022 | Gave a talk on computing with transients at the Banff workshop on Dynamical Principles of Biological and Artificial Neural Networks. |
| Dec. 2021 | Presented polynomial mixing times work at EcoRL workshop at NeurIPS. See the preprint. |
| Nov. 2021 | Participated in Montreal's MAIN neuroAI conference. |
| Oct. 2021 | Presented poster at Montreal's AI Symposium. |
| Sept. 2021 | post on Mila blog post on our NeuroAI reading group. |
| Aug. 2021 | Urgency work out as a preprint! Twitter summary thread here. |
| May 2021 | Gave a talk on Stochastic Thermodynamics of learning to the Physics of Machine learning reading group at Mila. |
| Jan. 2021 | Urgency work peer-reviewed and accepted at COSYNE. |
| Feb. 2021 | Join us for a exciting day of talks and a panel of top experts on the goals and challenges for robust scientific explanations in neural and artificial intelligence systems. |
| Dec. 2020 | Urgency work peer-reviewed and accepted at the Biological and Artificial Reinforcement Learning workshop at NeurIPS. |
| Dec. 2020 | Montreal Artificial Intelligence and Neuroscience 2020 conference. |
| Nov. 2020 | Presented urgency work at the inaugural NeuroAI conference, NAISYS, at Cold Spring Harbor Labs. |
| May 2020 | Happy to lead the breakout session on higher cognition at UNIQUE's inaugural NeuroAI symposium. |
| Apr. 2020 | Check out our preprint on Lyapunov spectra for RNN training. |
| Apr. 2020 | Our work on inferring population dynamics from intrinsically variable, vastly subsampled, and indirectly accessed genetic sequences is published in PLoS Computational Biology. |
| Mar. 2020 | We are presenting our decision-making work in collaboration with the Cisek Lab at COSYNE. |
| Dec. 2019 | We are organizing a NeuroAI workshop at NeurIPS2019. |
| Dec. 2019 | nnRNN paper presented in main track of NeurIPS. |
| Nov. 2019 | With yet another wonderful edition of the Montreal Artificial Intelligence and Neuroscience (MAIN) conference, Montreal is further establishing itself as the hotbed for incisive NeuroAI research. Honoured to have my new postdoc work recognized with two awards here. |
| May 2019 | We are organizing a Physics and AI Workshop in Montreal. |
| Jan 2019 | family_size+=1! |
Summary
I am a computational modeller, theory-builder & data scientist/machine learning researcher interested in
- how formed beliefs and incentives shape decision-making at the individual level and
- how public opinion and social norms impact social dilemmas and alignment problems.
Towards these ends, I coordinate interdisciplinary collaborations with domain experts in which I also contribute technical mathematical and computational expertise (theory and models/algorithms for decision-making agent learning, statistical inference, data analysis).
Trained in the theoretical biophysics community, I worked in computational neuroscience for some time, most recently on the science of decision-making in NeuroAI. Now, it's typically social scientists (social psychologists/ sociologists/ political scientists/ economists) who have identified the problems I work on. My approach to these problems stems from my expertise in machine-learning and system modelling. Here's an high-level depiction that motivates some current work:
In addition to supporting applications, I see these approaches as part of a modernized computational social science grounded in large-scale, quantitative approaches. See Research and Publications sections for more details.