Konstantin Burlachenko is a fifth-year Computer Science Ph.D. candidate and a member of Peter Richtárik’s Optimization and Machine Learning Lab, part of the KAUST AI Initiative, led by Jürgen Schmidhuber.
He earned his M.S. degree in Computer Science and Control Systems from Bauman Moscow State University in 2009. After graduation, he worked as a Senior Engineer for Acronis, Yandex, NVIDIA, and later as a Principal Engineer for HUAWEI. Between 2015 and 2019, Konstantin participated in the Non-Degree Option Program at Stanford University, earning two graduate certificates:
Research Focus
Konstantin’s current research centers on Distributed Stochastic Optimization and Federated Learning. It turns out that his algorithmic tools and methodologies have broader applicability beyond Federated Learning, covering areas such as:
Konstantin aims for either significant practical improvements over status quo solutions or bringing new perspectives on theoretical optimal algorithms.
Conferences
Konstantin’s work has been presented and accepted at prestigious venues, including:
- Neural Information Processing Systems (NeurIPS)
- International Conference on Machine Learning (ICML)
- International Conference on Learning Representations (ICLR)
- Transactions on Machine Learning Research (TMLR)
- SIAM Journal on Mathematics of Data Science (SIAM SIMODS)
- ACM International Workshop on Distributed Machine Learning (ACM CoNext)
Awards
- Dean’s Award, KAUST, 2020
- Grant from Saudi Authority for Data and Artificial Intelligence, 2022
- AMD Radeon Instinct MI50 from AMD Inc., 2022
- Dean’s List Award 2023, KAUST
- One of his sports achievements is the title of candidate Master of Sport in Chess which is assigned by the International Chess Federation FIDE.
Additional Interests
His broader areas of interest include:
- Scientific Software Development
- GPGPU and Compute Performance Optimization
- System Programming
- Computer Graphics and Computer Vision
- Physics-Based Simulation