Yeskendir Koishekenov
Machine Learning Researcher at Meta
London, England, Netherlands
Summary
👤
Senior🎓
Top SchoolYeskendir Koishekenov is a machine learning researcher and engineer with eight years of experience spanning industry and academia, currently conducting fundamental AI research at Meta FAIR. He holds a PhD in Computer Science from UCL, an MSc in Artificial Intelligence (cum laude) from the University of Amsterdam, and a strong engineering foundation from KAIST. His work bridges geometric and graph representation learning, multilingual model compression, and practical ML deployment—papers from his internships and graduate research have appeared at ACL, ICLR, and ICCV. He has contributed both applied production systems (Naver, Allganize) and cutting-edge research (AMLab) that includes oral presentations and workshop-leading work on visual inductive priors. Based in London with a background across Europe and Asia, he blends rigorous theoretical training with hands-on model engineering and deployment experience. An interesting detail: alongside productionizing ML pipelines, he has explored conditioning methods in GNNs and language-specific expert pruning, demonstrating a knack for translating niche research ideas into scalable solutions.
8 years of coding experience
3 years of employment as a software developer
Aktobe Kazakh-Turkish High SchoolMaster's degree, Artificial Intelligence, Cum Laude, Master's degree, Artificial Intelligence, Cum Laude at University of AmsterdamBachelor's degree, Electrical Engineering, Bachelor's degree, Electrical Engineering at 한국과학기술원(KAIST)University College London
English, Kazakh, Russian, Korean, Turkish
Github Skills (26)
python9
machine-learning9
gpu9
deep-learning8
ai8
dvc8
model-management8
incremental-learning8
deploying8
apache-spark8
lifecycle8
neural-network7
numpy7
tensorflow7
mlflow7
Programming languages (2)
Github contributions (5)
YeskendirK/Reinforcement-Learning
Sep 2019 - Nov 2019
Contributions:12 commits, 17 pushes, 1 branch in 1 month
YeskendirK/uvadlc_practicals_2021
Nov 2021 - Dec 2021
Repository for the code assignment of the Deep Learning 1 course, Fall 2021 edition
Contributions:34 PRs, 54 pushes, 20 branches in 1 month
deep-learningfallmachine-learning
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