Hriday Sangvhi

Hriday Sangvhi  was awarded a merit scholarship for his Bachelor studies and holds a B.Tech degree in Computer Science and Engineering from the SRM Institute of Science and Technology in India. In addition, he has completed certified programmes, a Machine Learning course and a six-course specialization in Deep Learning, by Andrew Ng, Stanford University. He has also completed a series of machine learning projects to understand the underlying mathematics behind popular machine learning algorithms.
Hriday has worked on real-life data science projects in two paid internships as a Bachelor’s student. One was at a leading network security engineering company, where he built network security analytics and intelligence applications based on Splunk and IBM QRadar. Another was at a global IT consultancy, where he was selected through a competitive process, and where he developed a recommender system for an e-commerce shopping cart.
Hriday won the best paper award for his Bachelor’s research on Deep Q-Networks Reinforcement Learning. His research paper titled, ‘Damped Sinusoidal Exploration Decay Schedule to improve Deep Q-Networks-based Agent Performance’ is published in the Springer journal ‘Artificial Intelligence and Evolutionary Computations in Engineering Systems’. Hriday is the first author of his research paper, with a faculty member being the only other co-author. Hriday’s PhD research involves bringing innovations to Deep Multi-Agent Reinforcement Learning, to analyze real-time granular data from connected autonomous vehicles, for self-organising traffic system optimization.
Hriday combines a unique blend of skills in scientific research and software engineering that focus on Artificial Intelligence.
“I am interested in building advanced Machine Learning and Artificial Intelligence systems that push the boundaries of innovation. My goal is to combine cutting edge research with industrial-strength software to solve real-world problems.”

Supervisors: Professor Vinny Cahill