I am a physicist building AI and signal processing systems that accelerate scientific discovery, from searching terabytes of astronomy data for signs of life beyond the Earth to shipping production geospatial foundation models for climate action. I combine the academic rigor of a scientist with the execution focus of an engineer, having shipped production ML systems at leading AI startups in London.
Highlights:
- Led the test-driven development of a segmentation model to detect Amazon rainforest cover in satellite imagery, eliminating up to 15 hours of tedious manual data labeling per week.
- Built BLIPSS, a novel open-source signal processing software to search for radar-like transmissions from ~600,000 planetary systems in the Milky Way.
- Developed a scalable tool for near real-time forecasts of earthquake counts from underground carbon storage, enabling proactive seismic hazard mitigation.
Outside of work, I enjoy following cricket, playing board games, and exploring natural wonders. Visit my personal website to learn more about my experiences in and beyond the workplace.
| Repository | Project focus | Technologies |
|---|---|---|
| agriyield_viz | Geospatial Data Visualization in the Cloud |    |
| amazonforest_segmentation | Test-driven Computer Vision Model Development |    |
| blipss | Software Development for Astronomy |     |
| may22-barrel | AI for Agriculture |  |
| oil-well-detection | Computer Vision for Satellite Imagery | |