Mher Safaryan

Dr. Mher Safaryan is a postdoctoral researcher at the Institute of Science and Technology Austria (ISTA), affiliated with Prof. Dan Alistarh's research group since 2022. Previously, he held postdoctoral positions at King Abdullah University of Science and Technology (KAUST) from 2019-2022 and served as a research technician there from 2016-2019. He earned his Ph.D. in Mathematics from Yerevan State University in 2018 under Prof. Grigori Karagulyan's supervision.

• Education: Ph.D. in Mathematics (2018, YSU)
• Past Affiliations: KAUST (2016-2022), Neural Magic/Red Hat (industrial secondment)

His research focuses on optimization theory and algorithms for machine learning, particularly in developing communication/computation/memory-efficient methods for large-scale training and federated learning. Key contributions include LDAdam (low-dimensional gradient statistics optimization), GradSkip (accelerated local gradient methods), and Unified Scaling Laws for compressed representations. He has published in top venues like NeurIPS, ICML, ICLR, TMLR, and The Journal of Geometric Analysis.

Scientific Awards:

• Marie Skłodowska-Curie Fellowship (MSCA COFUND IST-BRIDGE)

His work bridges machine learning optimization with mathematical foundations from his earlier research in real harmonic analysis. Current collaborations include Prof. Dan Alistarh (ISTA), Dr. Alexandre Marques (Neural Magic), and Prof. Peter Richtárik (KAUST).