4800 Oak Grove Drive, M/S 300-323
Pasadena, CA 91109Caltech/JPL
Hi! I'm Hrusikesha Pradhan, a dedicated machine learning researcher, I recently completed my PhD journey at IIT Kanpur. During my doctoral studies, my research primarily focused on the development of efficient machine learning algorithms that prioritize resource utilization while achieving high learning accuracy. I concentrated on leveraging kernel learning methods to uncover unknown functions across diverse machine learning applications. My work centered on designing kernel-based learning algorithms that offer richer function approximation, supported by robust theoretical convergence guarantees. These algorithms, complemented by innovative subset selection strategies, were tailored to address challenges in streaming data and large-scale data environments. I am deeply passionate about leveraging machine learning algorithms to address various environmental challenges we face, aiming to contribute towards creating a sustainable and better world for all.
Founding Chair, IEEE Signal Proc. Society Student Branch, IIT Kanpur
Organized a semester long IEEE Signal Processing Society Seminar Series on Optimization and Learning
Reviewer: AISTATS, IEEE Transactions on Signal Processing, Journal of Selected Topics in Signal Processing, IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, IEEE Communication Letters, and IEEE Signal Processing Letters
Function learning, Bayesian Learning, Kernel based methods, Distributed Learning, Optimization algorithms, Gaussian Processes