Nicolas Lanzetti
postdoctoral researcher
Computing and Mathematical Sciences
Caltech
Annenberg 203, Caltech
Pasadena, CA, USA
postdoctoral researcher
Computing and Mathematical Sciences
Caltech
Annenberg 203, Caltech
Pasadena, CA, USA
Artificial intelligence is rapidly evolving into a decision-maker in a wide range of critical business and societal infrastructures, such as energy markets and autonomous mobility. However, while these domains are strategic, uncertain, and dynamic, AI systems are still largely designed in static and controlled environments. With my research, I address this fundamental tension and enable AI-driven decision-making by developing the mathematical and algorithmic foundations for strategic dynamic decision-making under uncertainty. To do so, I leverage and enhance techniques from operations research, artificial intelligence, and control theory.
I am a postdoctoral researcher in the department of Computing and Mathematical Sciences at Caltech, hosted by Prof. Adam Wierman, Prof. Eric Mazumdar, and Prof. Steven Low. Previously, I was a PhD Student at the Automatic Control Laboratory at ETH Zürich under the supervision of Prof. Florian Dörfler (main advisor) and Prof. Alessio Figalli (second advisor). I was part of NCCR Automation. I received my BSc. and MSc. from ETH Zürich in 2016 and 2019, respectively. During my studies, I visited the Massachusetts Institute of Technology and wrote my Master's thesis at Stanford University, in Prof. Marco Pavone's Autonomous Systems Lab. In summer 2024, I was an intern in quantitative research at Citadel GQS.
| March 2026 | Together with Riccardo Bonalli and Thomas Lew, I am co-organizing a workshop on uncertainty-aware control at ECC 2026. Join us in Reykjavík in July! |
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| March 2026 | How to optimally steer a distribution with only a few controllable agents? Check out our new preprint. |
| February 2026 | In our new preprint, we use strategic risk aversion/robustness to train AI agents in collaborative multi-agent settings. |
| February 2026 | I received the SAND Award at the Information Theory and Applications Workshop. |
| January 2026 | Our paper on the identification of gradient-flow SDEs was accepted at AISTATS 2026. |
| January 2026 | Our paper on hedging against black swans in day-ahead energy markets using distributionally robust optimization was accepted at PSCC 2026. |
| October 2025 | I was selected as one of the NeurIPS top reviewers! |
| October 2025 | New preprint on hedging against black swans in day-ahead energy markets, using distributionally robust optimization. |
| October 2025 | I have started my postdoc at Caltech! |
| August 2025 | I successfully defended my PhD! |
| July 2025 | New preprint on strategically robust game theory. In multi-agent decision-making settings, how can agents be robust to one another's strategies? |
| February 2025 | Our paper Distributional Uncertainty Propagation via Optimal Transport has been accepted for publication in the IEEE Transactions on Automatic Control. |