I recently started my role as a Machine learning engineer at Birdstop.io, where I'm working on projects that use LLMs to generate autonomy in swarm systems and am developing computer vision based solutions for multiple use cases (such as dynamic social grouping, human and object re-id, zero shot multi-level object classification, object tracking, stereo image based geo location, etc).In my previous job at Lauretta AI, as a Machine Learning Engineer, I used similar techniques to develop security solutions for various Govt organizations like the DHS, TSA, DoD and MTA.I graduated with my Masters in Electrical and Computer Engineering from Johns Hopkins University. At Hopkins, I developed compressive sensing algorithms to reduce the post-processing times in medical imaging. In Prof. Kanolds's lab, I did some brief work with animal brain imaging and the automation of these systems. I was also the head of hardware for a Baltimore-based startup - TAMPAL, during which we won the SIL "Best Prototype Award". Additionally, I was part of a design team called iRoam. For who, I implemented computer vision models on embedded devices to aid the navigation of visually impaired people to storefronts and bus stops. We worked with and were supported by the National Federation of the Blind. At UW-Madison, I did extensive modeling and simulation work with theoretical physics and nuclear physics labs. I worked on a patent-pending project regarding the early identification of infections in veinous catheters. I was also the head of engineering for a rocketry project that aimed to study the effects of zero gravity on plant growth for the biochemistry department.