Looking for internship opportunities in the Aerospace/Machine Learning sectorMore About Me
I am an aerospace researcher, with expertise in the fields of Spacecraft guidance and control, Path Planning , Optimization, Astrodynamics, Data analysis, Artificial Intelligence and Machine learning. I am currently pursuing a PhD in Aerospace Engineering, with a focus on path planning under uncertainties, at the Carleton University, Canada. I have a good working knowledge of programming environments such as MATLAB, Python, R, Julia, C++ and simulation software including ANSYS, CATIA, Solid Edge and Simulink.
September 2020 – Present
May 2022 – September 2022
September 2017 – February 2020
This project uses reinforcement learning to train a deep neural network to act as the guidance strategy for spacecraft proximity operations. The project was submitted as the part of the course Applied Artificial Intelligence at Carleton University, Canada.
Deep learning project regarding the classification problem of the CIFAR-10 dataset using Convolutional Neural Networks. The project was for Applied Artificial Intelligence course at Carleton University.
This thesis proposes a new formulation that facilitates the application of reinforcement learning to the problem of orbit raising. A mathematical formulation for the orbit-raising problem is proposed in the framework of reinforcement learning to enable adaptive modification of the objective function weights during a transfer.
Function Approximation Technique (FAT) adaptive control scheme for 2-DOF robot arm carrying uncertain time-varying payload is implemented and also tested for different desired trajectories and cases to check the tracking performance of the controller.
Project based on the graduate employee turnover dataset which consists of HR information collected at the time of recruitment process which contains scores and ratings. Predicted graduate turnover based on their personal traits and other assessment scores using Logistic regression and Decision trees in R programming language.
A complete end-to-end project to predict the domestic flight prices in India depending on various features using Random Forest Regressor and XGBoost Regressor which is then deployed as a Flask Web Application on Render.
September 2020 - Present
Wichita State University
August 2017 - May 2020
Manipal Institute of Technology
August 2013 - May 2017