Dr. Fedor Getman Profile

Dr. Fedor Getman

at King Abdullah Univ of Science and Technology

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Author

Publications (6)

Proceedings Article | 30 May 2022 Poster

Neural network-aided design and fabrication of deformation robust flexible flat optics

Arturo Burguete-Lopez, Maksim Makarenko, Fedor Getman, Qizhou Wang, Andrea Fratalocchi

Proceedings Volume PC12130, PC121301D (2022) https://doi.org/10.1117/12.2621246

KEYWORDS: Neural networks, Optics manufacturing, Biomedical optics, Tissue optics, Polarization, Optical design, Nanolithography, Sensors, Polarizers, Optoelectronics

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Proceedings Article | 5 March 2022 Presentation

Robust and scalable flat-optics on flexible substrates through evolutionary neural networks

Fedor Getman, Andrea Fratalocchi, Maksim Makarenko, Arturo Burguete-Lopez

Proceedings Volume PC12010, PC120100Y (2022) https://doi.org/10.1117/12.2609805

KEYWORDS: Neural networks, Imaging devices, Polarizers, Polarization, Optics manufacturing, Mechanical efficiency, Fabrication, Biosensing

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Proceedings Article | 3 March 2022 Presentation

Cellular refractive index and thickness recovery via unsupervised learning framework.

Arturo Burguete-Lopez, Maksim Makarenko, Fedor Getman, Andrea Fratalocchi

Proceedings Volume PC11976, PC1197602 (2022) https://doi.org/10.1117/12.2608574

KEYWORDS: Refractive index, Machine learning, Photography, CCD cameras, Algorithm development, Thin films, RGB color model, Palladium, Modulation, Microscopes

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Proceedings Article | 19 November 2021 Paper

Highly-efficient flat-optics inverse design platform via fast trained neural predictors

Maksim Makarenko, Arturo Burguete-Lopez, Fedor Getman, Andrea Fratalocchi

Proceedings Volume 12078, 120781Y (2021) https://doi.org/10.1117/12.2603689

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Proceedings Article | 5 March 2021 Poster

Broadband ultra-flat optics with experimental efficiency up to 99% in the visible via convolutional neural network

Fedor Getman, Maksim Makarenko, Arturo Burguete-Lopez, Andrea Fratalocchi

Proceedings Volume 11703, 117031P (2021) https://doi.org/10.1117/12.2582787

KEYWORDS: Particles, Convolutional neural networks, Broadband telecommunications, Finite-difference time-domain method, Silicon, Resonators, Optical design, Optical components, Optical arrays, Neural networks

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Showing 5 of 6 publications

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