Farid Alizadeh

Farid Alizadeh is a Professor at Rutgers Business School, Rutgers University, and serves as the Director of the Master of Information Technology and Analytics (MITA) program since 2018. His expertise lies in mathematical optimization, particularly semidefinite programming, with applications spanning quantitative finance, statistical learning theory, computer science, and engineering.

• Education: Ph.D. in Computer and Information Sciences from the University of Minnesota.

Professor Alizadeh's research focuses on advancing semidefinite programming techniques for shape-constrained approximation and regression. His work has been supported by the National Science Foundation (NSF) and Office of Naval Research (ONR), and he has pioneered significant methodologies like the Q method for symmetric and second-order cone programming.

He has received prestigious accolades, including the NSF CAREER award and the 2014 Farkas Prize from the INFORMS Optimization Society. His academic supervision includes notable advisees such as Yu Xia, Stefan Schmieta, and Reuben Settergren.