| Dec 2024 | I co-presented the tutorial on Cross disciplinary Insights into Alignment in Humans and Machines at NeurIPS 2024. |
| Dec 2024 | Co-organized the NeurIPS 2024 Concordia Contest in collaboration with Google Deepmind and Cooperative AI foundation. This contest challenged participants to advance the cooperative intelligence of language model (LM) agents in rich, text-based environments, based on the recently released Concordia framework which uses language models to create open-ended worlds similar to tabletop role-playing games. |
| Nov 2024 | Our preliminary investigation into design of normative frameworks to ensure sociotechnical AI safety was accepted at Knight Symposium on Artificial Intelligence and Democratic Freedoms. |
| Aug 2024 | Our report on the Melting Pot contest: Charting the Future of Generalized Cooperative Intelligence” was accepted at Neurips 2024 Dataset and Benchmark Track. |
| Jul 2024 | Our works at the intersection of AI alignment, normative infrastructure and normative reasoning in AI agents were accepted in the Agentic Markets Workshop at ICML 2024 (this work focuses reinforcement learning agents) and the Workshop on Foundation Models and Game Theory at EC 2024 (this work focuses on language agents). |
| Jul 2024 | Our work on “Diffuse, Sample, Project: Plug-and-Play Controllable Graph Generation” was accepted in ICML 2024. |
| Mar 2024 | I was selected as a Kavli Fellow at the 34th Annual Kavli Frontiers of Science Symposium by the US National Academy of Sciences |
| Dec 2023 | Organized the NeurIPS 2023 Melting Pot Contest in collaboration with Google Deepmind and Cooperative AI foundation. This contest challenged researchers to push the boundaries of multi-agent reinforcement learning for mixed-motive cooperation by evaluating how well agents can adapt their cooperative skills to interact with novel partners in unforeseen situations. |
| Jun 2023 | Our work on “Plug-and-Play Controllable Graph Generation with Diffusion Models” was accepted in ICML 2023 Workshop on Structured Probabilistic Inference & Generative Modeling. |
| May 2023 | Our work on “Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models” was accepted at KDD 2023 |
| Apr 2023 | I gave an invited talk on “Foundations for Learning in Multi-agent Ecosystems: Modeling, Imitation and Equilibria” at University of Southern California. |
| Dec 2022 | Our work on “Imperceptible Adversarial Attacks on Discrete-Time Dynamic Graph Models” was accepted at Neurips Temporal Graph Learning Workshop |
| Aug 2022 | I gave an invited talk on “Learning from Interactions in Networked Systems” as a part of Beneficial AI seminar series at the Center for Human-Compatible Artificial Intelligence (CHAI), UC Berkeley |
| May 2022 | Our work on “Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning” was accepted at AAMAS 2022. |
| Apr 2022 | Our work on “CrowdPlay: Crowdsourcing human demonstration data for offline learning” was accepted at ICLR 2022. |