Maryam Fazel
Moorthy Family Inspiration Professor
Studies optimization for machine learning and control, including convex relaxations and low-rank matrix recovery.
Maryam Fazel's lab at UW works on learning theory & optimization. 23 papers since 2023, 6 at top venues, mostly NeurIPS and AISTATS. 17 alumni. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 26%
- PhD students
- 0
- MS students
- 0
- alumni listed
- 17
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 7 papers2025 · T1 0
- 10 papers2024 · T1 5
- 6 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, AISTATS, CDC, ICLR, L4DC
Research focuspaper titles that use each topic's words
- Learning theory & optimization5 papers
- low-rank2 papers
- recovery1 paper
- matrix1 paper
- convex0 papers
Paper list
From the lab homepage.
20257 papers
- COLM (Conf. of Language Modeling)Doomarena: A framework for testing ai agents against evolving security threats (opens in a new tab)
- COLM (Conf. of Language Modeling)Extragradient preference optimization (EGPO): Beyond last-iterate convergence for Nash learning from human feedback (opens in a new tab)
- Proc. of Learning for Decision and Control (L4DC) ConferenceFinite Sample Identification of Partially Observed Bilinear Dynamical Systems (opens in a new tab)
- COLM (Conf. of Language Modeling)Gating is Weighting: Understanding Gated Linear Attention through In-context Learning (opens in a new tab)
- Proc. of AI and Statistics Conference (AISTATS)Keeping up with dynamic attackers: Certifying robustness to adaptive online data poisoning (opens in a new tab)
- COLM (Conf. of Language Modeling)LoRe: Personalizing LLMs via Low-Rank Reward Modeling (opens in a new tab)
- CDCSub-optimality of the Separation Principle for Quadratic Control from Bilinear Observations (opens in a new tab)
202410 papers
- ICLR (T1)A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning (opens in a new tab)
- Proc. IntlA/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity (opens in a new tab)
- Proc. Uncertainty in AI ConfEfficient Interactive Maximization of BP and Weakly Submodular Objectives (opens in a new tab)
- AISTATS (T1)Emergent Segmentation from Participation Dynamics and Multi-learner Retraining (opens in a new tab)
- IMA J. on Information and InferenceFlat minima generalize for low-rank matrix recovery (opens in a new tab)
- INFORMS J. on OptimizationFunction Design for Improved Competitive Ratio in Online Resource Allocation with Procurement Costs (opens in a new tab)
- NeurIPS (T1)Initializing Services in Interactive ML Systems for Diverse Users (opens in a new tab)
- NeurIPS (T1)Optimal Tax Design in Nonatomic Congestion Games (opens in a new tab)
- AAAI Conf. on Artificial IntelligenceR. Raab, R. Boczar, M. Fazel, Y. Liu, Fair Participation via Sequential Policies, Proc
- NeurIPS (T1)Toward Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixture Models (opens in a new tab)
20236 papers
- ACDAFast First-Order Methods for Monotone Strongly DR-Submodular Maximization (opens in a new tab)
- J. of Machine Learning Research (JMLR)Multiplayer Performative Prediction: Learning in Decision-Dependent Games (opens in a new tab)
- NeurIPS (T1)No-Regret Online Prediction with Strategic Experts (opens in a new tab)
- L4DCOn Controller Reduction in Linear Gaussian Control with Performance Bounds (opens in a new tab)
- Proc. of AAAI Conf. on Artificial IntelligenceStochastic Contextual Bandits with Long Horizon Rewards (opens in a new tab)
- Annual Review of Control, Robotics, and Autonomous SystemsTowards a Theoretical Foundation of Policy Optimization for Learning Control Policies (opens in a new tab)
Where alumni went17 listed
Apply to UWFall 2027
UW Allen School Computer Science PhD
- Round
- Single round
- Opens
- GRE
- not required
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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