Meisam Razaviyayn

Meisam Razaviyayn is an Associate Professor at the University of Southern California (USC) with joint appointments in the Department of Industrial and Systems Engineering, Computer Science, Quantitative and Computational Biology, and Electrical Engineering. He serves as the Associate Director of the USC-Meta Center for Research and Education in AI and Learning and holds the Andrew and Erna Viterbi Early Career Chair. His academic background includes a Ph.D. in Electrical Engineering with a minor in Computer Science from the University of Minnesota, followed by a postdoctoral fellowship at Stanford University. Razaviyayn maintains active collaborations with industry partners like Google Research and Amazon.

• Current Roles: Faculty Visitor at Google Research
• Editorial Roles: Associate Editor for SIAM Journal on Optimization and IEEE Transactions on Signal Processing

His research focuses on optimization algorithms for modern data science problems, particularly addressing privacy, fairness, and scalability in machine learning systems. Recent work includes differentally private optimization frameworks and fair learning algorithms applicable to large-scale and decentralized data scenarios.

Key scientific awards include:

• 2022 NSF CAREER Award
• 2022 Northrop Grumman Excellence in Teaching Award
• 2021 AFOSR Young Investigator Award
• 2021 3M Nontenured Faculty Award
• 2020 ICCM Best Paper Award in Mathematics
• 2019 IEEE Data Science Workshop Best Paper Award

He actively advises Ph.D. students and leads research initiatives in robust and private machine learning. His group has received funding from NSF, Google Research, and Amazon for projects related to generative AI training, differentially private algorithms, and distributed optimization. Razaviyayn also contributes to academic service as a conference chair and workshop organizer.