Harvard— Postdoctoral Scholar, Astronomy — Cambridge, MA
Insight Data Science— Fellow, Data Science — Boston, MA
UC Santa Cruz— PhD, Astronomy — Santa Cruz, CA
UC Irvine— BS, Physics — Irvine, CA
Work Experience
Esri — Principal Data Scientist San Diego, CA (Home Office) - (5 years)
Generative AI & LLM Tooling: Contributed to generative AI workflows by implementing tools that integrate large language models for image interrogation, free-form text object detection, and automated object replacement.
Advanced Imagery & Zero-Shot Detection: Spearheaded advanced imagery analysis initiatives utilizing zero-shot detection and conducted comprehensive statistical evaluations on the resulting AI outputs.
3D Scene & LIDAR Optimization: Optimized 3D LIDAR processing pipelines and applied PointCNN models alongside advanced AI algorithms and image embeddings to identify infrastructural assets scenes.
Oceanic Predictive Modeling: Developed deep many-channel CNN models and forecasting systems to predict the worldwide occurrence of rogue and anomalously large waves based on oceanic conditions.
Environmental Deep Learning: Created automated deep learning and hyperspectral models to process satellite and sensor data for accurate land classification and the prediction of harmful algal blooms.
Aerial Feature Extraction: Applied transfer learning techniques to aerial imagery to generate precise, pixel-level labels for widespread infrastructural features, such as unpaved road networks.
Time-Series Imagery Monitoring: Developed proof-of-concept pipelines to retrieve and analyze time-series satellite imagery for monitoring culturally significant sites impacted by regional conflicts.
Automated Anomaly Detection: Designed and deployed automated solutions to actively monitor open-source map catalogs and identify suspicious changesets.
NLP & Document Parsing: Authored parsing tools to analyze scanned legal documents and automatically extract and map the geographic regions described within the text.
Leadership & External Enablement: Directed analyst teams to generate high-quality satellite imagery datasets and delivered technical workshops and presentations on AI enablement to external organizations.
Berkshire Grey — Principal Data Scientist Lexington, MA - (2 years)
Robotics Software Stack: Led optimization efforts of Python/ROS software stack used for pick and place in a multi-component robotics system, including robotic arms, high-performance conveyors, and automated shuttles.
Motion Planning & Parameter Prediction: Created and integrated parameter prediction to select optimal robotic motions for unseen products on demand.
Bayesian Sensing & Pick Verification: Developed online Bayesian analysis of data from sensors integrated into the picking system to dynamically determine how many items the robotic arm lifted.
Operations Analytics: Curated a dashboard of key performance indicators (KPIs) for the deployed robotic system via the ELK Stack.
Harvard-Smithsonian — NASA Einstein/ITC Fellow Cambridge, MA - (5 years)
Research Leadership: Technical lead of an eight-person research team of undergraduate/graduate students and postdocs resulting in dozens of completed scientific projects with 10k+ citations.
Science Communication: Appeared on the NOVA television program in 2018, describing data analysis by my group to measure a black hole’s mass using a recently destroyed star.
MOSFiT & Bayesian Modeling: Developed MOSFiT, a Bayesian engine to infer the most likely analytical models for time-series data.
Open Astronomy Catalogs: Led creation of the Open Astronomy Catalogs, a platform for sharing astronomical data, with a user-facing frontend and an API backend to serve data quickly to users.