Tushar Chandra is a software engineer with a decade of experience building production ML and web systems, currently at Loop after leading AI-driven clinical test development at Tempus. He ships end-to-end solutions across Python, TypeScript, React, and Kubernetes—turning research prototypes and Bayesian models into hardened Flask APIs serving thousands of daily requests. At Nielsen he developed novel Bayesian inference methods (US patent pending) and rebuilt flagship TV-rating pipelines to run faster and reduce false positives. He enjoys small, fast-moving teams and builds developer tooling and observability (OpenTelemetry wrappers, testing and type-checking improvements) to increase delivery speed and confidence. An active full-stack open-source contributor, he improved UX and search for the widely used Census Reporter project, demonstrating attention to both user-facing polish and backend correctness. He holds MS and BS degrees in Computer Science from Northwestern and often bridges research and product to make complex models operational.
10 years of coding experience
9 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Northwestern University
Awards: Indiana Academic All-Star, National Merit Finalist, National AP Scholar, Moody's Mega Math Challenge Winner, Indiana Math League School Winner, Outstanding Senior in Science, Awards: Indiana Academic All-Star, National Merit Finalist, National AP Scholar, Moody's Mega Math Challenge Winner, Indiana Math League School Winner, Outstanding Senior in Science at Columbus North High School
Census Reporter is a Knight News Challenge-funded project to make it easier for journalists to write stories using information from the U.S. Census bureau.
Role in this project:
Full-stack Developer
Contributions:29 commits, 6 PRs, 18 pushes in 1 month
Contributions summary:Tushar primarily focused on enhancing the front-end and user experience of the Census Reporter project. They implemented features such as highlighting and redirection for search results, and developed a tabbed view for filtering search results. The user also made styling changes to the search results page and autocomplete functionality. Additionally, they updated the project to correctly handle Puerto Rico table IDs and address cases where tables might not have a core counterpart.
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