Tatiana Gaintseva
Head, Main Methodologist And Lecturer at Deep Learning School
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolTatiana Gaintseva is a PhD candidate in AI and Head Methodologist at Deep Learning School with over a decade of experience bridging research and teaching in computer vision, diffusion models, explainability and knowledge extraction. Supported by a DeepMind studentship at Queen Mary University of London, she combines industrial R&D roles at Huawei and Philips with hands-on academic instruction at MIPT, Yandex School of Data Analysis and Moscow State University. Her work has produced applied advances—from improving face-recognition pipelines to novel generative-model pipelines for physics—and she has led collaborative projects and reading groups that translate research into product-ready solutions. Comfortable across theory and engineering, she explores fundamental deep learning topics like optimization, structural representations and robustness while mentoring the next generation of ML practitioners. An avid interdisciplinary thinker, she draws on interests in neurobiology and psychology to inform interpretable AI and knowledge-extraction research.
10 years of coding experience
5 years of employment as a software developer
Master of Science - MS, Marine Learning, Data Analysis, Master of Science - MS, Marine Learning, Data Analysis at Moscow Institute of Physics and Technology (State University) (MIPT)Doctor of Philosophy - PhD, AI in Computer Vision, Knowledge Extraction, Doctor of Philosophy - PhD, AI in Computer Vision, Knowledge Extraction at Queen Mary University of LondonMaster's degree, Big Data, Master's degree, Big Data at Yandex School of Data Analysis
Russian, English, German, Spanish
Github Skills (55)
computer-vision10
reinforcement-learning9
pytorch9
python9
lasagne9
svm9
machine-learning9
natural-language-processing9
deep-learning8
convolutional-neural-networks8
theano8
data-science7
economy7
discord-bot7
visual-recognition7
Programming languages (2)
Github contributions (5)
Atmyre/ml-dl-resources-rus
Feb 2022 - Feb 2022
Contributions:20 commits, 18 pushes, 1 branch in 1 day
Atmyre/LHCb_PID_Compression
Aug 2018 - Sep 2020
A benchmark to the challenge of compressing an obscured dataset containing Particle Identification
Contributions:2 PRs, 44 pushes in 2 years 1 month
benchmarkparticledatasetidentification
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