About Me

I am a PhD candidate in Electrical and Computer Engineering at the University of Florida. My research interests lie at the intersection of machine learning, computer vision, and remote sensing, with a focus on developing self-supervised learning methods for hyperspectral imagery.

My doctoral thesis, Beyond Band Masking: Decomposition-Guided Self-Supervised Learning for Hyperspectral Images, explores novel approaches to learning representations from hyperspectral data using Vision Transformers and Masked Autoencoders. I am particularly interested in applying these methods to ecological monitoring and precision agriculture applications.

I have experience developing large-scale datasets, building open-source tools for ecological research, and applying deep learning to challenging real-world problems in remote sensing and computer vision.

Education

University of Florida, Gainesville, FL

Ph.D. in Electrical and Computer Engineering • August 2021 - Present
Thesis: Beyond Band Masking: Decomposition-Guided Self-Supervised Learning for Hyperspectral Images

M.S. in Electrical and Computer Engineering • August 2019 - August 2021

Kurukshetra University, Kurukshetra, HR, India

B.S. in Electronics and Communication Engineering • August 2014 - August 2018

Skills

Programming Languages: Python, C++, SQL

Tools & Frameworks: PyTorch, TensorFlow, Slurm, Linux, ROS, Git, Comet, Wandb, AWS Bedrock, Jupyter Notebooks

Hardware: HPC, LiDAR, Raspberry Pi, Jetson Nano, Bluetooth/Wi-Fi/GSM modules, ultrasonic, infrared and moisture sensors