Scholar
Amir Yazdanbakhsh
Google Scholar ID: Vdu_sqwAAAAJ
Research Scientist at Google DeepMind
Citations & Impact
Citations
5,555
H-index
27
i10-index
44
Publications
20
Co-authors
82
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Published multiple papers covering areas such as generative AI, sparsity, quantization, linearization, and parallelization strategies. Some of his papers have been accepted at top conferences like ICML, ICLR, and NeurIPS, and have received Spotlight and Oral Presentation recognitions.
Research Experience
- Joined Google Research as a Research Scientist in 2019, following a one-year AI residency. He is the co-founder and co-lead of the Machine Learning for Computer Architecture team. He also led the development of a massively large-scale distributed reinforcement learning system that efficiently manages thousands of actors to solve complex, real-world tasks.
Education
- Received a Ph.D. in Computer Science from the Georgia Institute of Technology in 2019. His Ph.D. work has been recognized by various awards, including the Microsoft PhD Fellowship and Qualcomm Innovation Fellowship.
Background
- Research interests include leveraging machine learning methods to innovate and design better hardware accelerators, as well as designing large-scale distributed systems for training machine learning applications.
Miscellany
- The work of his team has been covered by media outlets including WIRED, ZDNet, AnalyticsInsight, and InfoQ.
