Fedor Getman

PhD Student

Fedor completed his bachelor and master degree at Pisa University with a thesis on THz Near-field microscopy at National Enterprise for Nano-Science and Nano-Technology (NEST) of Pisa. He participated in organizing and teaching multiple stages addressed to high school students for preparation of the math and physics Olympiads.

Fedor joined primalight in January 2018. Fedor’s research focuses on fabrication of nanostructures for wavefront engineering and optical neural networks

email: fedor.getman@kaust.edu.sa

location: building 1, level 4, 4200-SW38

Fedor’s research projects

Silicon on insulator nanofabrication technology

Inverse designed ultra-flat optics via artificial intelligence

Fedor’s publications

Arrays Asymptotic stability; Computer simulation; Electron tunneling; Mathematical models; Nonlinear systems; Parameter estimation Au dimer Commercial applications; Ellipsometry measurements; Fabrication technique; Mechanical resistance; Plasmonics; Printing technologies; Structural color; Sub-wavelength structures complex systems Computer simulation; Diffraction; Electric potential; Light propagation; Optical beam splitters; Oscillations; Solitons; Waveguides Condensed matter physics; Infrared devices; Light; Nonlinear optics; Optical pumping; Optical resonators; Photonic devices; Photonics; Probes; Resonators; Statistical optics; Ultrafast lasers Dynamics Electron optics Finite difference time domain method hyperuniform Light propagation Maxwell equations Maxwell–Bloch simulation Nematic liquid crystals Nonlinear equations Optical switches Optical waveguides Perovskite Phase transitions Photonic crystals Photonics plasmonic plasmonics Plasmons Quantum theory rotating dipole semiconductor nanolasers solar cells Solitons

2019

Fratalocchi, Andrea; Lopez, Arturo Burguete; Makarenko, Maxsim; Getman, Fedor

Flat optics polarizing beam splitter Miscellaneous

App. No. 62/799,324 (Pending), 2019, (50 nm thin metasurface technology for controlling vectorial light beams with 99% experimental efficiency across all the visible and made from inexpensive material with CMOS compatible large scale manufacturing. (App. No. 62/799,324)).

BibTeX | Tags: AI photonics