About

Rajat Poovaiah is a seasoned software engineer with a focus on data science and the systems that support it. He is currently pursuing his MS in Computer Science at Stony Brook University and has a Bachelor's degree in Aerospace, Aeronautical and Astronautical Engineering from IIT Kanpur. With over 6 years of relevant experience, Rajat is passionate about theoretical computer science and algorithm design. Currently, Rajat is working as a Graduate Teaching Assistant at Stony Brook University, where he has been responsible for conducting courses on Advanced Topics in Computer Science, Discrete Mathematics, Principles of Programming Languages, and Foundations of Computer Science. In his previous roles, he has worked as a Technical Consultant at glowroad.com and as a Senior Computer Scientist at Sigtuple. At glowroad.com, Rajat was responsible for tuning the parameters of the JVM to increase application stability and reduce resource utilization, thereby increasing uptime by 5% and reducing per instance costs by 50%. He also automated and streamlined deployments to allow for seamless autoscaling and configuration management and set up monitoring utilities including the ELK stack for centralized logging and Sentry for error management and alerting. At Sigtuple, Rajat designed and prototyped a program to run analyses directly on edge devices to reduce turnaround times and alleviate the need for internet access. He also built a distributed job scheduling cluster to optimize resource utilization during the training of deep neural networks over large volumes of medical image data, thereby cutting cloud costs by 40%. Additionally, he streamlined development by deploying and streamlining a CI/CD pipeline for core projects and publishing a backbone/guideline for future projects. Rajat's tech stack includes Data Science, Software Engineering, Research Science, AI, CI/CD, and Neural Networks. With his strong background in computer science and data science, Rajat is a valuable addition to any team looking to innovate and optimize their systems.