Arto Maranjyan
- Ph.D. Student, Computer Science
Biography
Arto Maranjyan is a PhD student at KAUST, advised by Peter Richtárik. Recently, his focus has been on the theory and design of asynchronous optimization methods—developing efficient, scalable, and theoretically grounded algorithms. More broadly, he works on optimization for machine learning and federated learning. Arto earned his M.s. and B.S. degrees from Yerevan State University. During my bachelor’s studies, he co-authored several papers in Harmonic Analysis under the guidance of Prof. Martin Grigoryan.
Research Interests
Arto's research focuses on the theory and design of asynchronous optimization methods—developing efficient, scalable, and theoretically grounded algorithms. More broadly, he works on optimization for machine learning and federated learning.
