About
About Serhii Barskyi
Serhii Barskyi is a data scientist specializing in spectral methods, Fourier-based machine learning, and quantum optimization, with applications to smart grid energy systems planning and BESS placement. He is the author of Quantum Annealing Trigonometrization via Aizenberg MVN Theory: Applications to BESS Placement.
He teaches a structured, year-long programme in quantum optimization and data science and mentors learners on Preply. His teaching covers Aizenberg MVN/MLMVN networks, QAOA, D-Wave quantum annealing, QUBO/BQM, Ocean SDK, Pegasus embedding, and hybrid solvers. He connects least squares, SVD, the Moore-Penrose pseudoinverse, and harmonic analysis with practical Python and AI projects, helping learners build and present DeepTech portfolios. His technical toolkit also includes Qiskit and Django REST.
He has more than nine years of experience in DeepTech startup development and international business incubators. His experience includes Technovation Challenge semifinal appearances in 2017 and 2021, the Social Impact Award final in 2021, and Global Industry Challenge finals in 2025 and 2026.
Books
Books by Serhii Barskyi
1 book by Serhii Barskyi on Leanpub
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