I am interested in new technology in optics, photonics, and quantum systems. I am motivated to find new solutions and develop new applications, constantly learning and improving my skills. I have a strong background in Physics and experience solving Multiphysics problems numerically with commercial software and using in-house code. I have experience with experimental equipment and automation. • Optics and Photonics. Design, modeling, and theoretical simulations and experiments for photonics components from UV to IR (high-speed photodetectors, metasurface structures, APD, SPAD, laser, VCSEL, lenses, interconnectors, sensors, fibers) for communications, sensors, image sensors, and quantum applications. Signal and image processing, temporal and special noise, stochastic process, stochastic resonance. Digital holography, wavefront reconstruction. Digital holography. Multi-physics simulation, non-linear optics. • Numerical methods (Monte-Carlo, FDTD, FEM, FFT, RCWA, BPM, TMM) for modeling complex multi-physics simulations, sparse matrices, ordinary and partial differential equations. Signal processing algorithms, machine learning, optimization, modeling probability distribution, time-dependent density functional theory, non-equilibrium Green’s functions. C++, Python, Matlab , Commercial software: Lumerical, Comsol, Zemax, Silvaco, LabVIEW, computer clusters parallel coding with CPU, parallel programming with CUDA and GPU. • New materials: quantum dots, photonic crystals, 2D materials, negative index materials, chirality, broken RT-symmetry, and non-Hermitian structures. Si, Ge, and III-V semiconductors. Turbulence, Mie and Raman scattering. • Quantum communication and quantum computing. Quantum to a classical interface. Quantum networks and Quantum Key Distribution system with noise and crosstalk. Quantum communication protocoles. • Experience with optical lab equipment, experiment automation, experimental setup, and alignment, data processing. Electrical and optical testing and data analysis. • Automation of a variety of systems, optical, cryogenic fuel loading, and storage systems. Physics-based models for a variety of physical systems (optics, photonics, fluid and gas dynamics, two-phase flow, cavitation). Prognostics for automated systems for NASA, using machine learning in combination with physics-based models. • Patents and publications in peer-reviewed journals: over 150 publications, conferences presentations at IEEE, APS, Optics https://scholar.google.com/citations?user=wpEXwjwAAAAJ&hl=en • Supervising students