Grigorii Vydrevich

Skills

Quantum Algorithms, Quantum Annealing, Probabilistic Computing, Machine Learning, Artificial Intelligence, Optimization Algorithms, Generative Models, Deep Learning, Mathematical Modeling, Numerical Analysis, Physics-Informed Neural Networks, Quantum Mechanics, Photonic Integrated Circuits, Nanophotonics, Quantum Technology, Integrated Photonics, Photonics Simulation, COMSOL Multiphysics, Python, Data Analysis, Research and Development, Problem Solving

About

Physicist and Machine Learning Engineer completing an M.Sc. in Physics at RWTH Aachen University, specializing in quantum technology, nanophotonics, and generative algorithms. Proven track record in developing physics-based optimizations and stochastic software algorithms, including thesis research on quantum annealing and probabilistic computing. Combines rigorous theoretical knowledge with practical software engineering experience from industry roles and award-winning performances at quantum and AI hackathons. Adept at translating complex physical concepts into scalable algorithmic solutions to solve high-impact, real-world optimization problems.