Summary
Taveesh Sharma is a PhD student and graduate research assistant in computer science at the University of Chicago, specializing in Internet measurements, network performance, and data-driven policy analysis. He blends large-scale data engineering, statistical modeling, and machine learning to diagnose broadband bottlenecks and reveal spatial equity gaps in connectivity, with findings that have implications for both network operators and policymakers. His work includes ML models that can infer WebRTC video quality using only transport-layer features, and spatial analyses that challenge reliance on administrative boundaries for measuring digital disparities. Before academia he spent several years as a software engineer at PayPal and ePayLater, building backend systems and automation for fraud and commerce platforms. He has revived region-specific tooling like the African Route Collectors Data Analyzer and contributes to hands-on teaching in machine learning for systems. Actively seeking data-focused roles, he combines production engineering experience with applied research rigor.
10 years of coding experience
3 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and Science
Master's degree, Computer Science, Master's degree, Computer Science at University of Cape Town
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Chicago