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