Summer 2026 Technology Internship Program

Cut data retrieval time by ~97% with a Python CLI using AVEVA PI Web API, automating ingestion and replacing manual Excel processes.

Built a real-time monitoring system with PI System Explorer and PI Vision to track data center load volatility, enabling proactive decisions.

Improved winter peak load forecasts, reducing MAPE by 47% with an XGBoost model for more accurate demand predictions.

Developed a BERT-based model to encode patient histories as vectors, enabling identification of undiagnosed patients and improved clinical trial cohort selection.

Performed delayed-entry Kaplan–Meier survival analysis with Python’s lifelines package, providing actionable mortality insights for patient risk assessment.

Analyzed CDKL5 Deficiency Disorder subpopulations via Komodo Health’s Sentinel, validating anti-epileptic drug usage to support clinical research.

Built an AI-powered app enabling client executives to query analytics via natural language, reducing analytics team overhead.

Cut AI processing costs by 50% and improved efficiency using OpenAI’s Batch API for large-scale asynchronous processing jobs.

Increased LLM response accuracy by 16% by creating a specialized training dataset with complex PostgreSQL queries for retail forecasting.

Standardized development environments with Mamba YAML and documentation, reducing onboarding time and ensuring consistency.