Biography

I am a Staff Scientist at Lawrence Berkeley National Laboratory. I also lead the Deep Learning Group at the International Computer Science Institute (ICSI), an affiliated institute of UC Berkeley. Prior to this role, I was an Assistant Professor (Tenure-Track) in Data-driven Modeling and Artificial Intelligence in the Department of Mechanical Engineering and Materials Science at the University of Pittsburgh. Before joining Pitt, I was a postdoctoral researcher in the Department of Statistics at UC Berkeley, where I worked with Michael Mahoney. I was also part of the RISELab in the Department of Electrical Engineering and Computer Sciences (EECS) at UC Berkeley. Before that, I was a postdoc in the Department of Applied Mathematics at the University of Washington (UW), working with Nathan Kutz and Steven Brunton. I earned my PhD in Statistics at the University of St Andrews in December 2017. My MSc. in Applied Statistics is also from the University of St Andrews.

My research broadly focuses on deep learning, with particular interests in generative AI, sequential models, and AI safety. Many problems in science are fundamentally sequential or dynamical, from forecasting physical systems to reasoning over complex scientific processes, which motivates much of my work on sequence-modeling methods. I use generative models to learn, predict, and control high-dimensional systems, with a particular interest in uncertainty and reliable inference. As these models become more capable and integrated into scientific workflows, AI safety is also becoming an important part of AI for science: we need systems that are not only accurate, but also robust to perturbations, misuse, and adversarial manipulation.

News

Two papers accepted in ICML 2026
- PRISM: Distribution-free Adaptive Computation of Matrix Functions for Accelerating Neural Network Training (preprint).
- D-Judge: Disrupting Multi-Turn Jailbreaks using Semantics-Preserving Output Rewriting (preprint).
Two papers accepted in AISTATS 2026
- Recency Biased Causal Attention for Time-series Forecasting (preprint).
- Quantifying Epistemic Uncertainty in Diffusion Models (preprint)
I am co-organizing the Deep Learning for Science Summer School (DL4Sci 26)
I will serve as an area chair @ ICLR 2026, @ ICML 2026, and @ NeurIPS 2026.
One paper accepted in NeurIPS 2025
- Block-Biased Mamba for Long-Range Sequence Processing (preprint)
One paper accepted in ICML 2025
- Emoji Attack: Enhancing Jailbreak Attacks Against Judge LLM Detection (preprint)
Two papers accepted in ICLR 2025 (one as spotlight)
- Tuning Frequency Bias of State Space Models (preprint).
- HOPE for a Robust Parameterization of Long-memory State Space Models (preprint).
I will serve as an area chair @ ICLR 2025, @ ICML 2025, and @ NeurIPS 2025.
One paper accepted in AISTATS 2025
- Gated Recurrent Neural Networks with Weighted Time-Delay Feedback (preprint).
Two papers accepted in ICLR 2024 (one as spotlight)
- Robustifying State-space Models for Long Sequences via Approximate Diagonalization.
- Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs.

Current Group Members

Minseon Gwak, Postdoc

Zhipeng Wei, Postdoc

Yihan Wang, Postdoc

Yang Wang, Postdoc

Aditi Gupta, ML Engineer

Maria Franz, Postdoc

Dongwei Lyu, PhD Student

Katie Keegan, Visiting PhD Student

Shreenidhi Srinivasan, Visiting PhD Student

Ben Hung, Undergrad Researcher

Ananya Gupta, Undergrad Researcher

Alumni

Annan Yu (Visiting PhD student 2024-26; now Research Scientist at Amazon)
Huanli Gong (UC Berkeley MSc Capstone Student 2025-26; now ML Engineer at ByteDance)
Yotam Yaniv (Postdoc 2024-26; now ML Engineer at Google).
Cici Wang (Undergraduate research intern 2023-25; now graduate student at U Chicago).
Garry Gao (Graduate researcher 2023-24; now Software Engineer at Amazon).
Junyi Guo (Graduate researcher 2022-24; now PhD student at University of Notre Dame).
Jialin Song (Graduate researcher 2021-24; now PhD student at Simon Fraser University).
Yixiao Kang (Graduate researcher 2023-24; now ML Engineer at Meta).
Daniel Barron (Graduate researcher 2023-24; now Software Engineer at Amazon).
Olina Mukherjee (High School student researcher, 2021-22; now undergraduate student at CMU).
Ziang Cao (Undergraduate research intern 2020-21; now graduate student at Stanford).
Francisco Utrera (Graduate researcher 2019-22; now Senior ML Engineer at Erithmitic) .
Evan Kravitz (Graduate researcher 2019-20; now Software Engineer at Amazon) .
Vanessa Lin (Undergraduate research intern 2018-19; now at Google).
Qixuan Wu (Undergraduate research intern 2018-19; now at Goldman Sachs).

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