Navid Azizan Ruhi

 

Navid Azizan
Esther & Harold E. Edgerton Career Development Assistant Professor
Massachusetts Institute of Technology (MIT)

Email: [last name]@mit.edu

News

Bio

Navid Azizan is the Esther & Harold E. Edgerton Career Development Assistant Professor at MIT, where he is a Principal Investigator in the Laboratory for Information & Decision Systems (LIDS) and holds dual appointments in the Department of Mechanical Engineering (Control, Instrumentation, & Robotics) and the Schwarzman College of Computing's Institute for Data, Systems, & Society (IDSS). He is also a Core Member of the MIT Statistics and Data Science Center and the Center for Computational Science and Engineering. His research interests broadly lie in machine learning, mathematical optimization, systems and control, and network science. His research lab focuses on various aspects of enabling large-scale intelligent systems, with an emphasis on principled learning and optimization algorithms, with applications in autonomous systems and societal networks. He obtained his PhD in Computing and Mathematical Sciences (CMS) from the California Institute of Technology (Caltech) in 2020, his MSc in electrical engineering from the University of Southern California in 2015, and his BSc in electrical engineering with a minor in physics from Sharif University of Technology in 2013. Prior to joining MIT, he completed a postdoc in the Autonomous Systems Laboratory (ASL) at Stanford University from December 2020 to August 2021. Additionally, he was a research scientist intern at Google DeepMind in 2019. His work has been recognized by several awards, including the 2020 Information Theory and Applications (ITA) Gold Graduation Award and the 2016 ACM GreenMetrics Best Student Paper Award. He was named an Amazon Fellow in Artificial Intelligence in 2017 and a PIMCO Fellow in Data Science in 2018. He was also the first-place winner and a gold medalist at the 2008 National Physics Olympiad in Iran.

Research Interests

  • Machine Learning

  • Mathematical Optimization

  • Systems and Control

  • Network Science

Education

  • Ph.D. in Computing and Mathematical Sciences
    California Institute of Technology (Caltech)
    Dissertation Title: Large-Scale Intelligent Systems: From Network Dynamics to Optimization Algorithms
    Advisors: Babak Hassibi and Adam Wierman
    Jun 2015 – Aug 2020

  • M.Sc. in Electrical Engineering
    University of Southern California
    Aug 2013 – May 2015

  • B.Sc. in Electrical Engineering with Minor in Physics
    Sharif University of Technology
    Sep 2009 – Jul 2013

Employment

 

Massachusetts Institute of Technology
Esther & Harold E. Edgerton Career Development Chair, Jul 2022 – Present
Assistant Professor, Jul 2021 – Present

Affiliations:
Laboratory for Information & Decision Systems (LIDS)
Department of Mechanical Engineering: Control, Instrumentation, & Robotics (CIR)
Schwarzman College of Computing's Institute for Data, Systems, & Society (IDSS)
Statistics and Data Science Center (SDSC) and Center for Computational Science and Engineering (CCSE)

 

Stanford University
Postdoctoral Fellow, Dec 2020 – Aug 2021
Autonomous Systems Laboratory (ASL)

 

California Institute of Technology
Graduate Research/Teaching Assistant, Jun 2015 – Aug 2020
Department of Computing and Mathematical Sciences (CMS)

 

Google DeepMind
Research Scientist Intern, Jun 2019 – Oct 2019

Representative Publications

Deep Learning and Autonomy

Foundations of Deep Learning

Markets for the Smart Grid

Algorithms for Distributed Computation

Spreading Processes in Complex Networks

[Full list of publications]