November 1, 2026, I start as a Tenure-Track Professor in Computational Statistics and Data Analysis at the University of Vienna, Department of Statistics and Operations Research (ISOR).
September 7–11, 2026, at Machine Learning in Nonstandard Settings, in Fréjus, France, I give an invited talk.
August 12-14, 2026, I give an invited tutorial at the Uncertainty Quantification Summer School, at USC.
August 4-7, 2026, I attend ILIAD 2026 at Berkeley.
August 1-3, 2026, at JSM invited paper session 1220 - Bridging Statistics and Modern AI: Foundations for Deep Learning and Generative Models, in Boston, I give an invited talk on "Complexity measures and generalization in deep learning".
April 23, 2026, at ICLR 2026 in Rio, we present a poster on "CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk" and on April 26 at AIMS@ICLR2026, I give an oral presentation on "Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All".
April 10-12, 206, we co-organize an AI Safety Retreat at Pacific Grove, led by Bi Yu, sponsored by Coefficient Giving.
March 26-27 Postponed to fall, 2026, at the Workshop on Trustworthy and Ethical AI at MBZUAI, in Abu Dhabi, I give an invited talk on "CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk".
December 17, 2025, at INCHER & Zell Colloquium, I give an invited online lecture on "The inductive bias of deep neural networks toward feature learning".
October 13, 2025, at the World Leading Scientists 2025 Conference 2025 at Berkeley, I present a poster on Uncertainty Quantification.
October 3-4, 2025, at the Berkeley–Columbia Meeting in Engineering and Statistics at Berkeley, I give an invited talk on "Machine Learning for Preference Elicitation in Combinatorial Auction Design" (October 4)
September 25-26, 2025, at MoDL in New York, I present a poster on Deep Learning Theory
July 17, 2025, at ICML 2025 in Vancouver, I give an oral presentation (top 1%) of our paper "Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All". [12' presentation] [5' video]
February 16-21, 2025, I participate in the workshop on Uncertainty Quantification in Neural Network Models at BIRS in Banff (Canada), giving an invited talk and leading a discussion on "Inductive Bias of Neural Networks" and presenting a poster on Uncertainty Quantification.
October 1, 2024, I start my postdoc with Prof. Bin Yu in the Yu group at UC Berkeley on Deep Learning Theory and Uncertainty Quantification.
July 26, 2024, I defend my PhD thesis on "Inductive bias of neural networks and selected applications".
July 8-12, 2024, I am at the 12th Bachelier World Congress of the Bachelier Finance Society in Rio de Janeiro, giving a talk on "Path-dependent Neural Jump ODEs and their Application to Stochastic Filtering".
June 17-20, 2024, I am at the ETH – Hong Kong – Imperial Mathematical Finance Workshop at Imperial College London, giving an invited talk on "Deep Learning Theory on Multi-task Learning".
On March 25, 2024, I am at AMLD EPFL 2024 in Lausanne to give an invited talk on "NOMU: Neural Optimization-based Model Uncertainty"
From Feb 19-26, 2024, I am at AAAI 2024 in Vancouver for our paper "Machine Learning-powered Combinatorial Clock Auction".
From Jun 25-28, 2023, I am at the University of Oxford.
From Feb 15-28, 2023, I am visiting Bin Yu's research group at UC Berkeley.
From Feb 6-15, 2023, I am at AAAI 2023 in Washington, DC, to give an oral presentation of our paper "Bayesian Optimization-based Combinatorial Assignment". A pre-recorded video of the talk is on YouTube: https://youtu.be/6YH9K6LDHPY.
