Abhishek Kumar Umrawal earned two master’s degrees — one in statistics from the Indian Institute of Technology (IIT), Kanpur, in 2011, and the other in economics in 2021 from Purdue, where he is a current PhD student in industrial engineering. A former marketing analyst in India, he has served as an instructor of business analytics, statistics, mathematics and economics, and most recently, as a Purdue graduate teaching assistant in industrial engineering, EPICS, and mathematics. Abhishek’s research is focused on machine learning for social networks, machine learning for statistical power analysis, multi-armed bandits and online learning, and deep reinforcement learning for efficient and intelligent transportation. Recently, he developed a genetic algorithm-based framework to learn the statistical power manifold in a time-efficient manner by significantly reducing the number queries to the power function oracle. He holds certifications in deep learning, probabilistic graphical models, managerial economics and business analysis, and data science. His skill level with Python software has produced top-quality simulation and data analysis results for his research. At Purdue, he has served as chair of the academic and social affairs committees for the Industrial Engineering Graduate Student Organization, and vice president and president of the INFORMS student chapter. As a future faculty member, he hopes to bolster diversity, equity and inclusion through research, teaching and community engagement.

Research Interests

Machine learning algorithms for social networks