Scholar
Javad Lavaei
Google Scholar ID: fVo3u5wAAAAJ
Associate Professor, UC Berkeley
Citations & Impact
Citations
4,930
H-index
30
i10-index
80
Publications
20
Co-authors
44
list available
Contact
Publications
Resume (English only)
Academic Achievements
- September 2025: New paper 'StyleBench: Evaluating thinking styles in Large Language Models'
- September 2025: The paper 'Don’t Trade Off Safety: Diffusion Regularization for Constrained Offline RL' to appear in Conference on Neural Information Processing Systems (NeurIPS)
- September 2025: New paper 'Bridging Batch and Streaming Estimations to System Identification under Adversarial Attacks'
- August 2025: The paper 'Distributed Optimization and Distributed Learning: A Paradigm Shift for Power Systems' to appear in IEEE Systems Journal
- July 2025: The paper 'Exact Recovery Guarantees for Parameterized Nonlinear System Identification Problem under Sparse Disturbances or Semi-Oblivious Attacks' to appear in Transactions on Machine Learning Research
- July 2025: The paper 'System Identification from Partial Observations under Adversarial Attacks' to appear in 64th IEEE Conference on Decision and Control
- July 2025: The paper 'Coordinating Distributed Energy Resources with Nodal Pricing in Distribution Networks: a Game-Theoretic Approach' to appear in 64th IEEE Conference on Decision and Control
- June 2025: The paper 'Policy-based Primal-Dual Methods for Concave CMDP with Variance Reduction' to appear in Journal of Artificial Intelligence Research
- May 2025: New paper 'On the Sharp Input-Output Analysis of Nonlinear Systems under Adversarial Attacks'
- May 2025: New paper 'Understanding SAM through Minimax Perspective'
- April 2025: Donghao Ying defended his PhD dissertation.
- April 2025: Baturalp Yalcin defended his PhD dissertation.
- March 2025: Yuchen Fang has joined my group as a PhD student.
Research Experience
- Associate Professor at the Department of Industrial Engineering and Operations Research, University of California, Berkeley.
Background
- Works on various interdisciplinary problems in control theory, optimization theory, power systems, and machine learning.
