Oleg Zabluda
Senior Staff AI Researcher at Volkswagen Group of America Innovation and Engineering Center California (IECC)
Redwood City, California, United States
Summary
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Senior🎓
Top SchoolOleg Zabluda is a Senior Staff AI Researcher and longtime software engineer with over two decades of systems and C/C++ expertise and a decade of deep learning experience, now applying that breadth to autonomous-vehicle perception and sequence modeling at Volkswagen IECC. He designs and trains state-of-the-art CNNs, Transformers and GANs for depth, superresolution, detection, tracking and anomaly/corner-case discovery, and has led production-caliber research spanning PyTorch, TensorFlow and Keras. His background includes leadership roles at AMD (where he produced top-tier CIFAR-10 results and 9x superresolution work), Visa, HP Labs and Yahoo, combining low-level performance engineering, SIMD/assembly optimization and large-scale distributed system design. A practical generalist, he pairs rigorous mathematical training with hands-on implementations—from x86 assembly and kernel-level tuning to self-supervised depth and seq-to-seq velocity prediction—and even contributed accuracy fixes to the popular Keras examples for MNIST. Based in Redwood City and a US citizen, he runs his own software consultancy (ObjectSourcery) alongside research roles, making him equally comfortable mentoring students, shipping prototypes, and optimizing production systems.
10 years of coding experience
21 years of employment as a software developer
Ph.D. Candidacy, Mathematics, Ph.D. Candidacy, Mathematics at Penn State UniversityMS, Mathematics, MS, Mathematics at Kyiv National Taras Shevchenko Universityhigh school diploma, physics/mathematics, high school diploma, physics/mathematics at Kiev Physics and Mathematics School 145
Stackoverflow
1reputation
0reached
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Github Skills (8)
neural-network10
keras10
machine-learning10
deep-learning10
tensorflow10
python10
data-science9
pytorch4
Programming languages (3)
Github contributions (5)
keras-team/keras
Sep 2017 - Aug 2018
Deep Learning for humans
Role in this project:
Data Scientist
Data ScientistContributions:107 commits, 142 PRs, 333 comments in 11 months
Contributions summary:Oleg primarily contributed to the `mnist_siamese_graph.py` example by correcting accuracy calculations, enabling accuracy reporting during training, and simplifying the compute_accuracy() function. They also worked on the `mnist_acgan.py` example, replacing a literal constant with a variable. Further contributions included fixing an off-by-one bug in the progress bar and modifying the `compute_accuracy()` function argument order. These changes indicate a focus on refining and improving the accuracy and functionality of deep learning models within the Keras framework.
deep-learningtensorflowneural-networksmachine-learningdata-science
ozabluda/keras
Sep 2017 - Mar 2019
Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.
Contributions:4 PRs, 223 pushes, 215 branches in 1 year 5 months
cntkdeep-learningpythontensorflowtheano
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