Behnam Tayebi

Behnam Tayebi has a diverse work experience in the fields of optical engineering, neuroscience, ophthalmology, biomedical engineering, brain and cognitive engineering, semiconductor physics, and physics. In 2021, they were appointed Optical Engineering Lead at Inscopix, Inc. and Associate Research Scientist-Neuroscience at New York University. From 2019 to 2021, they held two postdoctoral positions at New York University in Ophthalmology and Neuroscience. In 2018, they were a Postdoctoral Fellow at Vanderbilt University's Department of Biomedical Engineering, where they developed a head-mounted swept-source OCT prototype, a compact polarization-sensitive OCT, and designed an OCT spectrometer by Zemax. From 2015 to 2012, they were a Research Professor at Korea University's Department of Brain and Cognitive Engineering, where they developed a smart phase unwrapping algorithm, a practical technique to measure the dispersion of the refractive index of axons, holographic lithography monitoring with nanoscale, and a large field of view 3D phase imaging system beyond the Nyquist frequency. From 2012 to 2008, they were a Research Assistant at Yonsei University, where they developed compact multicolor quantitative phase microscopy, a single exposure and large dynamic range holography by single wavelength, and dual-wavelength DPM. Finally, from 2008 to 2006, they were a Graduate Research Assistant at IUST Semiconductor Physics, where they conducted XRD Crystallography and line broadening analysis, fabrication of conductive thin films for solar cell applications, microstructure characterization of ZnO thin films using x-ray broadening theorem, and investigation of optical and electrical properties of thin films.

Behnam Tayebi received their Doctor of Philosophy (PhD) in Physics from Yonsei University in 2015. Behnam also holds certifications in Convolutional Neural Networks in TensorFlow, Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, Machine Learning, Natural Language Processing in TensorFlow, Sequences, Time Series and Prediction, and TensorFlow Specialization from deeplearning.ai and Stanford Online.