Bobak Mortazavi

Bobak Mortazavi is an Associate Professor in the Department of Computer Science & Engineering at Texas A&M University. His research focuses on systems and analytics for personalized health, emphasizing machine learning methods that enhance clinical outcomes through multimodal modeling and dynamic risk prediction. His work has pioneered the integration of machine learning and embedded systems with clinical outcomes research, including clinical risk prediction models and models for individual monitoring through passive sensing in remote, free-living environments. Before joining Texas A&M, he completed his postdoctoral fellowship at Yale under supervision of Prof. Harlan Krumholz at the Center for Outcomes Research and Evaluation (CORE) and Prof. Sahand Negahban in the Department of Statistics (2014-2016). He received his Ph.D. in C.S. under the supervision of Prof. Majid Sarrafzadeh at the Wireless Health Institute at UCLA (2014). He also received his B.A. in Applied Mathematics and B.S. in Electrical Engineering and Computer Science from the University of California, Berkeley (2007) and M.S. in Electrical and Computer Engineering from the University of California, Irvine (2009).