I’m associated with Green Communications Systems Lab under Dr. Ganesh Prasad, and working in the Machine Learning domain.
Parallely, I’m also interning with <a href = “https://www.nvidia.com/en-in/”, target=”_blank”> NVIDIA Graphics, Bangalore, in Deep Learning Inference using CUDA Parallel Programming.
During April - June, I have worked with Speech and Language Technology Lab at <a href = “https://saarthi.ai”, target=”_blank”>Saarthi.ai</a>, a conversational AI startup, as Deep Learning Research Intern to improve the dialogue agent policy using Actor-Critic framework and focusing on dialogue generation through few-shot knowledge transfer networks. Major topics of study were Reinforcement Learning, Dialogue Policy Learning, ML Interpretability & Natural Language Processing.
I had voluntarily worked, as the Event Head, Data Strata and Publicity Co-Head for Tecnoesis ‘20 (NITS’ Techno-management fest) till February.
Since, September till November, I had been heading various teams in different fests organized as the courtesy of NITS Gymkhana. These were basically Web Development Head at SPIC MACAY, Technical Head at All India Inter NIT Tournament & Technical Team in Srijan.
Late August, I had emerged as the Winner of Hackathon Module at NIT Conclave in NIT Rourkela amongst 31 NITs for the app, The PaperLess.
During May - July, I had an enriching experience of working in Pattern Recognition and Image Analysis Lab at Indian Institute of Technology Indore with Dr. Vivek Kanhangad, where we developed a Pore based Fingerprint Recognition System built on residual based Convolutional Neural Network Architecture and its Unsupervised Deep Domain Adaptation using a gradient reversal layer.
February, our team was selected to represent NIT Silchar in the Nationals of Smart India Hackathon 2020 organized by Ministry of Human Resources and Development, Government of India.
I also have worked with Computer Vision and Pattern Recognition Lab at Motilal Nehru National Institute of Technology Allahabad with Dr. Dushyant Kumar Singh to explore various basic machine learning algorithms and to employ challenge of ICDAR to predict the gender of a handwritten document during Winter of 2018.