As a Ph.D. candidate in the David R. Cheriton School of Computer Science at the University of Waterloo, I pursue research at the intersection of artificial intelligence, optimization, and machine learning. My goal is to develop novel and efficient algorithms for solving complex and dynamic problems in various domains, such as signal processing, communications, and networks. I have a strong background in online learning, a branch of machine learning that deals with sequential decision making under uncertainty and partial feedback. I have published a paper in IEEE Transactions on Signal Processing, where I proposed and analyzed a projection-free algorithm for online convex optimization with non-stationary losses and noisy gradients. I also have experience in applying online learning techniques to real-world scenarios, such as matrix completion and background separation in video. Additionally, I have a Master of Technology from the Indian Institute of Technology, Kanpur, where I worked on similar topic.