Machine Learning Engineer
Currently pursuing MS in AI Engineering at Carnegie Mellon, crafting ML solutions that scale from research to production.
Focus on large-scale ML systems and applied AI research.
Dean's List all semesters, University Honors Scholar, Founders Day Award.
Break Through Tech AI Fellowship — Intensive 1-year program in applied machine learning.
Working on something new.
Built AI document automation processing 100K+ financial documents monthly with 98% accuracy. Developed self-improving feedback loop improving accuracy from 75% to 92%.
Pioneered transformer-based predictive modeling achieving 97% accuracy on 500K+ patient records. Published at 2024 ML for Healthcare Conference.
Led team designing multimodal ML architecture combining vision transformers and BiLSTM to predict YouTube virality with 97% accuracy across 27K+ videos.