Summary
Kateryna Chumachenko is a PhD-level machine learning researcher and applied deep learning engineer based in Helsinki, currently interning at NVIDIA with a strong track record in computer vision and multimodal methods. Over a decade of experience spans academic research roles at Tampere University and industry internships at Meta and Huawei, blending theory (subspace learning, dimensionality reduction) with practical system-building. She graduated with distinction in Data Engineering and Machine Learning and has taught image and video processing, demonstrating both technical depth and communication skills. Her work is notable for bridging academic research and industry collaboration, repeatedly moving prototypes toward applied settings. Kateryna’s background in security and network engineering gives her an uncommon systems-aware perspective on ML problems. She focuses on multimodal approaches that connect signal processing roots to modern deep learning pipelines.
10 years of coding experience
5 years of employment as a software developer
Exchange student, Security, 8.6/10, Exchange student, Security, 8.6/10 at Amsterdam University of Applied Sciences
Bachelor of Engineering (BEng), Information Technology, 4.92/5, Bachelor of Engineering (BEng), Information Technology, 4.92/5 at Xamk - South-Eastern Finland University of Applied Sciences
Master of Science (Technology), Data Engineering and Machine Learning, 4.64/5, Master of Science (Technology), Data Engineering and Machine Learning, 4.64/5 at Tampere University
English, Ukrainian, Russian, German, Finnish