Soheil Kolouri
Assistant Professor of Computer Science
Research Focus
Soheil Kolouri's broad research interest lies in mathematical machine learning, computational optimal transport, and geometric deep learning. Kolouri leads Machine Intelligence and Neural Technologies (MINT) laboratory at Vanderbilt. His lab strives for developing Next-Generation Machine Learning algorithms (Next-Gen ML) that address current deficiencies in our technologies regarding sample/label efficiency, explainability, brittleness, and lifelong/continual learning.
Biography
Assistant Professor Soheil Kolouri joins Vanderbilt from HRL Laboratories in Malibu, California, where he was a Principal Machine Learning Scientist focusing on various aspects of deep learning. He received his Ph.D. in biomedical engineering in 2015 from Carnegie Mellon University. Kolouri also was a postdoctoral scholar at CMU focusing on transport-based pattern recognition and image modeling approaches for automated analysis of histopathology, MRI, and fMRI images. He develops practical machine learning and computer vision solutions for challenging problems in biomedical signal and image analysis. Kolouri has more than 40 full-length publications, including 13 journal articles and 25 conference papers at top-tier venues. He has contributed to numerous DARPA proposals in machine learning and has successfully secured a total of nearly $15 million in funding as a PI, including three large DARPA projects. At HRL Laboratories, he mentored Ph.D. students from top universities during their internships. Kolouri’s accomplishments include six patents issues in 2020 and 12 patent applications pending.