Hi, I’m Sri! I’m a Carnegie Mellon University graduate student and I build machine learning systems, data products and pipelines, and mission-driven analytics. My technical foundation spans natural language processing (retrieval-augmented generation, multimodal reasoning, fine-tuning), classical machine learning (time series forecasting, clustering, anomaly detection), and data engineering (SQL databases, API integration, workflow automation). I work at the intersection of technical execution and domain expertise, targetting real operational constraints. I design systems considering deployment context, evaluation under temporal distribution shift, fairness metrics, and implementation feasibility. I focus on domains where data science can support evidence-based decisions in climate and energy policy, finance, public health, urban infrastructure, and justice system reform.
Education
Carnegie Mellon University, Heinz College — Pittsburgh, PA
M.S. Public Policy Management & Data Science (August 2024 – May 2026)
Focus: Applied ML, NLP, decision systems, optimization, econometrics, AI safety
Purdue University — West Lafayette, IN
B.S. in Data Science, Minor in Economics (August 2018 – May 2022)
Certificates: Entrepreneurship & Innovation, Music Technology
