About

Sanket Singh is a final year student at IIT Kharagpur majoring in Electrical Engineering with a minor in Computer Science and Engineering. He is currently working as a Software Engineer Intern at Intuit, where he is involved in the Modernization of Payroll Tax Center project. Sanket has rewritten the legacy Payroll Tax Center web application from scratch using React for Intuit's AppFabric platform with micro-frontend architecture as the sole developer. He has also simplified the architecture of the Payroll Tax Center, improved authentication, and revamped its user interface. Additionally, Sanket has written unit tests in Jest covering 60.14% of the new application's code. Sanket has worked as an Undergraduate Student Researcher at the Epidemics on Networks Research Group (Epione), IIT Kharagpur, where he implemented statistical learning algorithms to estimate the parameters of dynamical models of epidemics on networks using real COVID-19 data from Europe. He has also developed an ADMM based distributed algorithm for solving the Wasserstein Distributionally Robust Logistic Regression Problem. Sanket has co-authored a publication titled "A Closed-Loop Framework for Inference, Prediction and Control of SIR Epidemics on Networks" in NetEcon 2020. As a Software Engineer at the Autonomous Ground Vehicle Research Group, Sanket developed traffic sign detection modules for autonomous driving using Haar cascade and LBP based region proposal pipeline and ResNet for traffic sign classification. He ranked 2nd in the Auto-Nav challenge of Intelligent Ground Vehicle Competition (IGVC) 2019 held at Oakland University. Sanket's education history includes a Dual Degree in B.Tech and M.Tech in Electrical Engineering and a Minor in Computer Science and Engineering from IIT Kharagpur. He is proficient in Software Engineering, Research Science, Frontend, Spring Boot, Spring, Web, NodeJS, and ReactJS. Sanket has a relevant experience of 1.77 years.