Liubov Talamanova
AI Research Engineer Scientist at Intel Corporation
Dublin, Ireland
Summary
🤩
Rockstar🎓
Top SchoolLiubov Talamanova is an AI Research Engineer with 9 years of experience specializing in deep learning, model optimization, and production-focused inference tooling at Intel, where she advanced OpenVINO’s Post-Training Optimization Toolkit and NNCF quantization. She has strong hands-on expertise in computer vision and DNN modules, contributing layers, backend support, and ONNX interoperability to OpenCV and OpenVINO, and implemented MobileNetV3 variants and CLIP quantization to speed real-world models. Based in Dublin, she blends research rigor (Master’s in Computer Science) with practical engineering—shipping tests, refactors, and bug fixes that improve robustness and deployability. An active open-source contributor, she favors performance-driven improvements and quietly elevates tooling quality across widely used repositories.
9 years of coding experience
3 years of employment as a software developer
Master's degree, Computer Science, 4.9, Master's degree, Computer Science, 4.9 at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)Data science, Data science at Yandex school of data analysis
Github Skills (29)
pytorch10
opencv10
python10
image-processing10
model-driven10
machine-learning10
inference10
onnx10
openvino10
model-building10
deeplearning-ai10
deep-learning10
tensorflow10
cplus10
model-optimization10
Programming languages (5)
Github contributions (5)
openvinotoolkit/nncf
Apr 2021 - Jan 2023
Neural Network Compression Framework for enhanced OpenVINO™ inference
Role in this project:
ML Engineer
ML EngineerContributions:368 reviews, 36 commits, 104 PRs in 1 year 9 months
Contributions summary:Liubov primarily contributed to the development of new model architectures and the expansion of existing model support within the NNCF framework. They implemented MobileNetV3Small and MobileNetV3Large models, including the necessary code for model definition and weight loading. The user also addressed code quality issues by removing duplicate dependencies and maintained the codebase by updating test configurations and example code.
bertsemantic-segmentationmixed-precision-trainingtensorflowclassification
opencv/opencv_extra
Sep 2018 - Feb 2021
OpenCV extra data
Role in this project:ML Engineer
ML EngineerContributions:4 reviews, 45 commits, 44 PRs in 2 years 5 months
Contributions summary:Liubov primarily contributed to adding test data for various ONNX models within the `opencv_extra` repository. These contributions focused on generating test cases for layers such as Shufflenet, transpose, deconvolution, pooling, batch normalization, and slicing. The user's work involved creating and integrating model data for different ONNX-related operations, effectively expanding the repository's testing capabilities for neural network models.
pythoncomputer-visionextra-data
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