Summary
Kush Hari is a PhD student and Graduate Student Researcher at UC Berkeley with 8 years of engineering and research experience focused on surgical robotics, policy learning, active vision, and cloud robotics. He combines hands-on systems work—building simulations, mixed-reality surgical apps, and robotics perception/control pipelines—with machine learning research that accelerates optimization and control. His background spans biomedical engineering, electrical engineering, and computer science from Vanderbilt, and includes published work on neurosurgical mixed-reality and brain-shift simulation. Kush has applied ML outside academia too, from sleep-tracking classifiers at Cigna to neural-network–driven MPC speedups for quadrupeds, showing a knack for translating research into practical tools. Based in Columbus, OH, he brings interdisciplinary fluency across software, hardware, and clinical collaboration to automate delicate surgical tasks.
8 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of California, Berkeley
High School Diploma General Studies, High School Diploma General Studies at Upper Arlington High School
Bachelor's degree Biomedical/Medical Engineering Electrical Engineering Computer Science, Bachelor's degree Biomedical/Medical Engineering Electrical Engineering Computer Science at Vanderbilt University