My name is Azalia Mirhoseini. I am a Staff Research Scientist at Google Brain and an Advisor at Cmorq. I have co-founded and currently lead Google Research's ML for Systems team, where we focus on transforming systems and chip design through novel deep learning based methods. I am a machine learning researcher with more than 40 peer reviewed papers at top venues including ICML, ICLR, NeurIPS, UAI, SIGMETRICS, DAC, DATE, and ICCAD. My research interests include deep reinforcement learning (RL), natural language processing (NLP), computer vision and large-scale systems for machine learning training. I have a Ph.D. in Computer Engineering from Rice University. I have received a number of awards, including the MIT Technology Review 35 Under 35 Award, the Best Ph.D. Thesis Award at Rice University and a Gold Medal in the National Math Olympiad in Iran. My work has been covered in various media outlets including MIT Technology Review, IEEE Spectrum, ZDNet, VentureBeat, and WIRED. Here are links to my Google Scholar, CVTwitter, and LinkedIn accounts.


For a complete list of my publications, visit my Google Scholar page.


I am currently working on deep reinforcement learning approaches to solve problems in computer systems and metalearning. My Ph.D. research focused on leveraging the interplay between systems and machine learning optimization.

    Awards and Honors

    • MIT Technology Review 35 Under 35 Award, 2019
    • William Marsh Rice Best Thesis Award, ECE Department, 2015
    • IBM Ph.D. Scholarship, 2012
    • Schlumberger Ph.D. Student Fellowship, 2012
    • Microsoft Research Graduate Women’s Scholarship, 2010
    • Iran's National Math Olympiad Gold Medal, 2004


info (at) azaliamirhoseini.com