Arto Maranjyan

As I complete my PhD this year, I’m actively exploring postdoc and research scientist positions.
I’m a PhD student at KAUST, advised by Peter Richtárik. Recently, my focus has been on the theory and design of asynchronous optimization methods—developing efficient, scalable, and theoretically grounded algorithms. More broadly, I work on optimization for machine learning and federated learning.
Before starting my PhD, I earned my MSc and BSc from Yerevan State University. During my bachelor’s, I co-authored several papers in Harmonic Analysis under the guidance of Prof. Martin Grigoryan.
Outside of academics, I enjoy dancing bachata, playing board games, ultimate frisbee, and foosball.
Recent News
May 01, 2025 | Honored to receive the CEMSE Dean’s List Award for academic and research excellence at KAUST — with a $2,500 prize. |
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May 01, 2025 | A paper has been accepted to UAI 2025. MindFlayer SGD: Efficient Parallel SGD in the Presence of Heterogeneous and Random Worker Compute Times. |
May 01, 2025 | Two papers accepted to ICML
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Mar 23, 2025 | I spent two weeks visiting Yi-Shuai Niu at the Beijing Institute of Mathematical Sciences and Applications (BIMSA), collaborating on a project on Server-Assisted Federated Learning. During the visit, I also gave talks at three universities: PKU, BUAA, and BIMSA. |
Feb 10, 2025 | I’ll be giving a talk at the AMCS/STAT graduate seminar at KAUST on February 27, presenting our paper, Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity. |
Feb 04, 2025 | New paper out ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning. Co-authored with El Mehdi Saad, Peter Richtárik, Francesco Orabona. [LinkedIn post] |
Jan 28, 2025 | New paper out: Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity. Co-authored with Alexander Tyurin, Peter Richtárik. [LinkedIn post] |