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Maryam Fazel

Moorthy Family Professor
Data Science, Robotics and Controls
Room CSE230, Paul Allen Center
Campus Box 352500
University of Washington
Seattle, WA 98195


Bio: Maryam holds the Moorthy Family Inspiration Career Development Professorship, as well as adjunct appointments in the departments of Mathematics, Statistics, and the Allen School of Computer Science and Engineering at UW. Her current research interests are Optimization in Machine Learning and AI, Learning and Control, and Online/interactive and Reinforcement learning. Maryam is the director and lead PI of the Institute for Foundations of Data Science (IFDS), a multi-university research institute aiming to develop theoretical foundations for machine learning and data science, funded by a $12.5 million NSF TRIPODS Phase II grant, launched in September 2020. Previously, she co-directed the Algorithmic Foundations of Data Science Institute (ADSI), a TRIPODS Phase I institute that was a pre-cursor to IFDS. She is a recipient of the NSF CAREER Award (2009), UWEE Outstanding Teaching Award (2009), and UAI conference Best Student Paper Award (with her student K. Dvijotham, 2014), and coauthored a paper on low-rank matrix estimation selected by ScienceWatch as the “Fast Breaking Paper” (based on high number of citations) in the area of Mathematics (August 2011). Prior to joining UW, she was a postdoctoral scholar at Caltech; and received her PhD in EE from Stanford University where she was advised by Prof. Stephen Boyd. She received her BS in EE from Sharif University of Technology in Iran. Maryam serves as a Founding Associate Editor of the SIAM Journal on Mathematics of Data Science (SIMODS), Action Editor of J. of Machine Learning Research (JMLR), Steering Committee & Program Committee Member of ICCOPT 2022, Steering Committee member of the SPARS biannual conference, on the Editorial board of the MOS-SIAM Book Series on Optimization, and commonly as an Area Chair (and Senior Area Chair in 2023) for Neural Information Processing Systems (NeurIPS). She also serves on the Advisory board of the UW-Amazon Science Hub, and the executive committee of the eScience Institute.

Short Bio: Maryam Fazel is the Moorthy Family Professor of Electrical and Computer Engineering at the University of Washington, with adjunct appointments in Computer Science and Engineering, Mathematics, and Statistics. Maryam received her MS and PhD from Stanford University, her BS from Sharif University of Technology in Iran, and was a postdoctoral scholar at Caltech before joining UW. She is a recipient of the NSF Career Award, UWEE Outstanding Teaching Award, a UAI conference Best Student Paper Award with her student. She directs the Institute for Foundations of Data Science (IFDS), a multi-site NSF TRIPODS Institute. She serves on the Editorial board of the MOS-SIAM Book Series on Optimization, and as an Associate Editor of the SIAM Journal on Mathematics of Data Science. Her current research interests are in the area of optimization in machine learning and control.

Awards and Honors

Honors, Awards, Keynotes:

  • Plenary speaker (one of three), American Control Conference, 2025.
  • Keynote Speaker, SIAM Annual Meeting, July 8-12, 2024, Spokane, WA.
  • Keynote Speaker, Conf. on Parsimony and Learning (CPAL), Jan 2024, Hong Kong.
  • Keynote Speaker (one of three), Conf. on Learning Theory (COLT), July 2022, London, UK.
  • NSF TRIPODS Phase II (2020-2025). Director and lead principal investigator of IFDS (Inst. For Foundations of Data Science), a multi-site Institute with partners at Universities of Wisconsin, California at Santa Cruz, and Chicago.
  • Moorthy Family Professor in ECE, August 2020-present.
  • NSF TRIPODS (2017-2020): Co-director (with S. Kakade) of the Phase I NSF Institute: Algorithmic Foundations for Data Science Institute (ADSI). Co-PIs: Dmitriy Drusvyatskiy, Zaid Harchaoui, Yin Tat Lee. NSF announcement and press, also here.
  • Keynote Speaker, Intl. Symposium on Mathematical Programming (ISMP), July 2018, Bordeaux, France.
  • Simons Institute Open Lecture (one of three public lectures per semester, organized by the Simons Institute, UC Berkeley), November 2017, Berkeley, CA.
  • Plenary Speaker, SIAM Applied Linear Algebra Conference, October 26-30 2015, Atlanta, GA.
  • Plenary Speaker, SPARS Conference 2015 (Signal Processing with Adaptive Sparse Representations), July 2015, Cambridge, UK.
  • Best Student Paper Award, Uncertainty in Artificial Intelligence (UAI) 2014 (with K. Dvijotham and E. Todorov).
  • Plenary Speaker, 2013 International Linear Algebra Society Conference, June 3-7 2013, Providence, RI.
  • Coauthored paper selected by ScienceWatch as the “Fast Breaking Paper” in the area of Mathematics, August 2011.
  • NSF CAREER Award, National Science Foundation, 2009.
  • Outstanding Teaching Award, 2009, University of Washington Electrical Engineering Dept. (Annual department-level teaching award, nominated by students)
  • EE Dept. Award for ranking first among all freshmen, 1990, Electrical Engineering Dept., Sharif University of Technology, Tehran, Iran
  • Ranked first in the country in the Nationwide Entrance Examination to all Iranian Universities (among ~1 million applicants), 1990, Iran. Presidential Letter of Honor awarded by the Iranian President, 1990, Iran.

Research Projects

Some of our projects (also see recent publications):

  • Theory of Deep Learning (e.g., generalization properties of flat minima of training loss; theory for new deep architectures)
  • Theoretical Foundation for Policy Optimization for Designing Control Policies (Bridging control theory and RL)
  • Machine Learning Markets: Dynamics, Competition, and Interventions (NSF AF) (2023-2026). PIs: M. Fazel, J. Morgenstern, L. Ratliff, S. Dean (Cornell). (Multi-learner ML)
  • Toward a Mathematical Foundation of Deep Reinforcement Learning (NSF CIF) (2022-2026). PIs: S. Du, M. Fazel, T. Ma (Stanford), J. D. Lee (Princeton). (Reinforcement Learning theory)
  • Learning in Decision-dependent Games (Optimization, ML and game theory)
  • Learning and Optimal Experimental Design with a Budget (NSF CIF) (2020-2024). PIs: M. Fazel, K. Jamieson. (Active/Interactive Learning)
  • Institute for Foundations of Data Science (NSF TRIPODS Phase II Institute) (2020-2025)
  • Safe Imitation Learning for Robotics. NSF TRIPODS+X (2018-2022). PI: Z. Harchaoui; Co-PIs: M. Fazel, S. Kakade, S. Srinivasa
  • Algorithmic Foundations of Data Science Institute (NSF TRIPODS Phase I) (2017-2020)
  • Control and Learning of Dynamical Systems: Optimization, Sampling, and Regret (DARPA Lagrange, 2018-2019)
  • ADAPT: Analytical Framework for Actionable Defense against Advanced Persistent Threats (led by UW PI Radha Poovendran) (ONR MURI 2016-2021)

Recent Publications

Selected papers below. Please see my Google Scholar page for a complete list.  


I am fortunate to currently advise or co-advise these fantastic students:

As well as IFDS postdocs:

  • Natalie Frank, Incoming IFDS Postdoc (co-mentored with Bamdad Hosseini).


  • Ting Kei Pong, PhD in Mathematics, June 2011. Co-advised with Prof. Paul Tseng. Currently: Associate Professor, Dept. of Applied Mathematics, Hong Kong Polytechnic University.
  • Brian Hutchinson, PhD in EE, August 2013. Co-advised with Prof. Mari Ostendorf. Currently: Professor, Department of Computer Science, Western Washington University.
  • Dvijotham Krishnamurthy, PhD in Computer Science and Engineering, June 2014. Co-advised with Prof. Emo Todorov. Currently: Research Scientist at Google.
  • Palma London, BS in EE and Math, June 2014. Currently: Postdoc at UC San Diego.
  • Karthik Mohan, PhD in EE, December 2014. Ex-data Scientist at Amazon and Meta. Currently: ML educator, UW affiliate faculty.
  • James Saunderson, Postdoc (joint position with Caltech), Sep 2015-June 2016. Currently: Associate Professor, Dept of Electrical and Computer Systems Engineering, Monash Univ, Australia.
  • Amin Jalali, PhD in EE, August 2016. Postdoc at Univ. of Wisconsin; Researcher at Technicolor Research. Currently: Independent researcher.
  • Dennis Meng, PhD in EE, May 2017. Currently: Apple, Inc.
  • Reza Eghbali, PhD in EE, August 2017. Currently: Data Science Health Innovation Fellow at University of California, San Francisco & University of California, Berkeley.
  • Tyler Johnson, PhD in EE, October 2018. Co-advised with Prof. Carlos Guestrin. Currently: Machine Learning Research Engineer, Apple Inc.
  • Jingjing Bu, PhD in EE, 2020. Co-advised with Prof. Mehran Mesbahi. Currently: Software engineer at TikTok Inc.
  • Mitas Ray, MS in EE, 2021. Co-advised with Prof. Lillian Ratliff. Currently: ML Software engineer at
  • Yue Sun, PhD in ECE, March 2022. Currently: Data Scientist at Microsoft (Bing Ads team).
  • Lijun Ding, IFDS Postdoc (co-mentored with D. Drusvyatskiy). Currently: Assistant Professor in Operation Research, Texas A&M.
  • Omid Sadeghi, OhD in ECE, December 2023. Currently: Postdoc at MIT (OR Center).


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