Industry Experience

My industry work focuses on large-scale machine learning systems, geospatial modeling, and production-ready AI experimentation.

Incoming ML Intern — Regeneron

May 2026

Joining Regeneron’s Machine Learning team to work on applied modeling and validation systems within large-scale biomedical and operational pipelines.

AI/ML Open Source Contributor — DeepChem (Google Summer of Code)

May 2026

Contributing to DeepChem, an open-source library for deep learning in drug discovery and chemistry, as part of Google Summer of Code. Focusing on integrating Open Language Models (OLMo) as large as 7B parameters, enabling advanced reasoning and interpretability for chemical datasets.

AI Associate Developer — Insurity

Oct 2025 – Jan 2026

Peril Prediction Project

  • Engineered large-scale geospatial preprocessing pipelines (6M+ rows) integrating climate variables with peril events via time alignment, spatial filtering, and feature engineering using Python, Pandas, and GeoPandas.
  • Built and evaluated LightGBM-based multi-class peril classifiers, applying SMOTE class balancing to improve accuracy and F1 score by approximately 10%.
  • Experimented with a Temporal Fusion Transformer (TFT), modeling seasonal dependencies via cyclical week encoding and training GPU-accelerated PyTorch models on NVIDIA RTX hardware.

Computer Vision — Geospatial Change Detection

  • Developed a geospatial change-detection system for before/after satellite imagery using OpenCV and deep learning pipelines.
  • Implemented CNN and Transformer-based architectures including U-Net++ for high-resolution semantic segmentation.