Summary
Sweta Karlekar is a PhD student and NDSEG/Provost’s Diversity Fellow at Columbia University with a decade of experience applying machine learning, Bayesian statistics, and causal inference to real-world products and research. She has driven high-impact applied research at Meta—leading generative AI safety work that measurably increased demographic diversity in model outputs—and built Bayesian causal-inference pipelines that unlocked over $500M in annual value. Her background spans production ML, NLP, and computer vision from internships and research roles at Google AI, Yelp, and MITRE, plus hands-on software engineering across startups. Comfortable bridging research and product, she coordinates cross-functional roadmaps and turns probabilistic models into deployable systems. An early STEM organizer who scaled a youth outreach program to 11 chapters, she combines technical depth with a proven talent for building teams and communicating complex results.
10 years of coding experience
6 years of employment as a software developer
High School Computer Science Computer Engineering Biology Chemistry, High School Computer Science Computer Engineering Biology Chemistry at Thomas Jefferson High School for Science and Technology
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Columbia University
Bachelor of Science (B.S.) Computer Science, Bachelor of Science (B.S.) Computer Science at University of North Carolina at Chapel Hill
Spanish, Marathi, Hindi, English