Snake AI

I'm a master's student at UCSD who is highly motivated to innovate in the field of AI. I aim to build artificial agents that show human-like “common sense” in their operating domains. When I'm not in front of my computer, I like to hike, play the piano, and read a book. I also upload programming tutorials on my YouTube channel where I wish I was more active.
I worked for AppDefense (now CarbonBlack) which is an application security product for workloads and endpoints. Part of my work involves designing and building automation frameworks in Python to ensure correctness of our security features. I also built a Vulnerability Assessment for determining the vulnerabilities present in OSes and applications which saved the company a ton of money because we were earlier using a third party service for the same.
I was responsible for re-writing the lower level code for an internal framework to comply with newer standards. As the framework was in constant use by over 50+ engineers, I had to make changes such that they do not impact anyone at the user-level. My role required strong Python skills, shell scripting and working over virtual machines and datacenters.
As a technology intern under the GE Renewables umbrella, I optimized the algorithm used for determining the mechanical load on GE Wind Turbines. I worked along-side principal scientists and brought down the run-time from 3 hours to 20 minutes by using efficient mathematical minimization functions.
Alongside my corporate intersnhip with VMware, I also participated in an academic research project with Dr. Vidhya Balasubramanian and Dr. Shunmuga Velayutham. We outlined the design of a successful fitness function, which "evolves" an artificial agent to play (and perfect) the Snake Game - using a novel combination of Neuroevolution and Search Algorithms (like Curiosity Search and Novelty Search). We then modeled the snake game as a goal-seeking problem where our agents showed great adaptability even in uncertain environments.
I served as a part-time research intern at Preflet, a startup in Lisbon, Portugal. I built a platform which automatically trains a Machine Learning model using the most suitable algorithm given a dataset. By using population-based Evolutionary Algorithms, the platform was able to fine-tune the model's hyper parameters which further increased its robustness.
Under the mentorship of Dr. Gowtham R and Prof. Dayanand Vinod, I designed a digital and real-time solution to prevent Human-Elephant conflicts across the forest fringes of Kerala, India. We developed a novel layered approach that minimizes the load of running deep learning models on computationally limited devices like Raspberry Pi. The system was successfully able to detecte all 4 instances of intruding elephant herds along our campus boundary.
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