Baharan Mirzasoleiman


Engineering VI - 397B

404 Westwood Plaza

Los Angeles, CA 90095

I am an Assistant Professor in Computer Science Department at UCLA, where I lead the BigML research group.

My research aims to address sustainability, reliability, and efficiency of machine learning. I am mainly working on improving the big data quality, by developing theoretically rigorous methods to select the most beneficial data for efficient and robust learning. Besides, I am also interested in improving the models and learning algorithms. The resulting methods are broadly applicable for learning from massive datasets across a wide range of applications, such as medical diagnosis and environment sensing.

Before joining UCLA, I was a postdoctoral research fellow in Computer Science at Stanford University working with Jure Leskovec. I received my Ph.D. in Computer Science from ETH Zurich advised by Andreas Krause. I received an ETH medal for Outstanding Doctoral Thesis, was selected as a Rising Star in EECS by MIT, and received an NSF Career Award.


Aug 7, 2023 Upcoming keynote at KDD’23 resource-efficient learning workshop
Jul 1, 2023 Co-organizing the 2nd New Frontiers in Adversarial Machine Learning, Join us in Hawaii!
Jun 15, 2023 I received a Hellman Fellows Award :sparkles:
May 1, 2023 Co-organizing the 3rd Sparsity in Neural Network Workshop at ICLR, continuing our efforts at
2nd Sparsity in Neural Network Workshop, and 1st Sparsity in Neural Network Workshop
Sep 7, 2022 Invited talks at IFML workshop, UAI tractable probabilistic modelling workshop (TPM), Vanderbilt University Machine Learning Seminar, ICML DataPerf Workshop, UT Austin ECE Colloquia Seminar, Stanfod MLSys seminar, and ICML SubsetML Workshop summarizing our efforts on data selection for efficient and robust learning. You can watch some here Watch
Sep 7, 2022 Yu Yang received Amazon Doctoral Student Fellowship :sparkles:
Aug 15, 2022 I received an NSF Career Award :sparkles:
May 27, 2022 I received Amazon Research Award :sparkles: