Rafael Stekolshchik
Machine Learning Algorithms Engineer at LikeAGlove LTD
Petah Tikva, Center District, Israel
Summary
🤩
Rockstar🎓
Top SchoolRafael Stekolshchik is a veteran Machine Learning Algorithms Engineer with a Ph.D. in Mathematics and over 35 years of experience designing and implementing algorithms and software systems across communications, computer vision, 3D geometry and network management. He combines deep theoretical expertise—author of 40 articles and a book—with hands-on development in C++, Python, Matlab and R, recently focusing on 3D geometric ML and deep reinforcement learning using PyTorch. His career spans embedded and distributed systems (NMS/EMS, SDH, MPLS, SNMP), real-time signal and image processing, and advanced algorithmic work such as SLAM, Kalman/Particle filters, and skeletal animation for 3D prototyping. Notably, he has repeatedly bridged academic research and product engineering, turning mathematical methods (PCA/SVD, Kolmogorov–Smirnov tests, MST clustering) into production-ready code and protocols. Based in Petah Tikva, Israel, Rafael brings rare breadth from low-level IPC and protocol gateways to modern ML pipelines, with a consistent record of shipping complex, performance-sensitive systems.
10 years of coding experience
40 years of employment as a software developer
Nanodegree Program, Deep Reinforcement Learning, Nanodegree Program, Deep Reinforcement Learning at UdacityPh.D., Mathematics, Ph.D., Mathematics at Kiev UniversityM.Sc., Mathematics, M.Sc., Mathematics at Voronež UniversityMath School 34, Chisinau (Kishinev)
Hebrew, English, Russian
Github Skills (13)
computer-vision10
algorithms10
dqn10
deep-reinforcement-learning10
sac10
lstm10
q-learning10
slam10
classifier10
ddpg10
machine-learning7
deep-learning6
caffe5
Programming languages (3)
Github contributions (5)
Rafael1s/Weyl-Group-Algorithms
Nov 2023 - Dec 2024
Contributions:16 PRs, 89 pushes, 4 branches in 1 year 1 month
Rafael1s/Deep-Reinforcement-Learning-Algorithms
Apr 2019 - Jun 2021
32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
Contributions:995 commits, 889 pushes, 1 branch in 2 years 2 months
ddpgdeep-reinforcement-learningdqnq-learningdeep-rl-algorithms
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