Konstantin Golobokov
Research Intern @ Meta FAIR | PhD Student @ UW Applied Math | ex-Senior Applied Researcher @ Microsoft | Researching efficient methods for deep learning.
- Role
- Research Scientist Intern, Fair at Meta
- Location
- Seattle, WA, US
- LinkedIn followers
- 500 followers
About Konstantin Golobokov
I am an applied mathematician and ML researcher focusing on the theoretical foundations of deep learning and large-scale model efficiency. Currently, I am a PhD Student in Applied Mathematics at the University of Washington and a Research Intern at Meta FAIR, working with Lin Xiao on stochastic optimization and proximal algorithms for sparse training.Prior to my PhD, I served as a Senior Applied Researcher at Microsoft working on large-scale Code Generation and RAG architectures alongside Weizhu Chen. My background bridges the gap between rigorous mathematical proofs and the engineering requirements of deploying foundation models at scale.Research Interests: Convex/Non-Convex Optimization, Stochastic Methods, Proximal Algorithms, Foundation Model Architecture, Distributed Systems.
Experience
Research Scientist Intern, Fair
Jul 2025 — Present · Seattle, WA, US
Education
University of Washington
Doctor of Philosophy - PhD, Applied Mathematics
University of Michigan College of Engineering
Bachelor of Science in Engineering (B.Sc.Eng.), Computer Science Engineering
2015 — 2018
University of Washington
Master of Science - MS, Computational and Applied Mathematics
Skills
- C++
- Java
- Matlab
- Software Development
- Leadership
- Microsoft Office
- Training
- Microsoft Word
- Microsoft Excel
- Powerpoint
- Research
- Machine Learning
- Computer Vision
- Python
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