Summary
Priyanka Khante is a Senior Generative AI Scientist and PhD candidate in Electrical and Computer Engineering at UT Austin with 11 years of experience applying machine learning and deep learning to real-world pattern recognition. She has deep expertise in leveraging high-density wearable and multimodal sensor data to detect human behaviors, having built end-to-end pipelines and deployed algorithms in healthcare and consumer products during internships at UnitedHealth Group and Procter & Gamble. Her work blends rigorous academic research—active learning, unsupervised multimodal clustering, and robot perception—with practical deployment skills in Python, R, SQL, BigQuery, and cloud-based data engineering. Priyanka has repeatedly translated research into impact, from halving human query requirements in active learning experiments to improving Fitbit sleep detection on insurer datasets. Based in Albany, NY, she combines meticulous study design and publishing experience with a knack for turning noisy, in-the-wild signals into robust, actionable models.
11 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD Electrical and Computer Engineering, Doctor of Philosophy - PhD Electrical and Computer Engineering at The University of Texas at Austin
Bachelor's Degree Computer Science, Bachelor's Degree Computer Science at Stony Brook University
English, Hindi, Marathi