Name: ANURAG SHARMA
Type: User
Company: Punjab Engineering College (deemed to be university)
Bio: I am currently pursuing my Doctoral degree of in the field of Nano-photonics, Optical Engineering Intern, OPTICA, INDIA
Location: Chandigarh, INDIA
Blog: https://www.linkedin.com/in/anurag-sharma-488351a2/
ANURAG SHARMA's Projects
Config files for my GitHub profile.
Frequency-domain photonic simulation and inverse design optimization for linear and nonlinear devices
Interactive Web Plotting with Bokeh in IPython notebook
Data and simulations files for the tutorial article "Brillouin optomechanics in nanophotonic structures"
This is the companion repository of the Cloud Academy Webinar Series on Pandas.
Python-based electromagnetic simulator and mode solver for nanophotonics applications, using the Eigenmode Expansion (EME) method.
:shrimp: Electromagnetic Simulation + Automatic Differentiation
an IOT based application to detect covid-19 symptoms, though its not very efficient----
Deep Learning Specialization by Andrew Ng on Coursera.
An Open Source Deep Learning Framework for Solving Inverse Optimization Problem
A python script for the calculation of the effective dielectric constant for a mixture of two phases
README for my Github Profile
Global optimization based on generative neural networks
Config files for my GitHub profile.
SDK for FPGA / Linux Instruments
Band diagram and Field of 2D photonic cristal
Python based continuous adjoint optimization wrapper for Lumerical
free finite-difference time-domain (FDTD) software for electromagnetic simulations
Learn and design nanophotonic structures, surface plasmon devices... Using powerful machine learning algorithms(CNN, GBRT, differentiable forest...)
Multilayer perceptron has been implemented using PyTorch framework to compute various optical properties of a photonic crystal fiber (PCF).
MIT Photonic-Bands: computation of photonic band structures in periodic media
Plot photonic dispersion curves with mode shapes (a frontend to MIT Photonic bands)
Here, we use a conditional deep convolutional generative adversarial network (cDCGAN) to inverse design across multiple classes of metasurfaces. Reference: https://onlinelibrary.wiley.com/doi/10.1002/adom.202100548