Machine Learning Researcher | Computer Vision, GeoAI & Physics | Astronomy PhD
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.
Project 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 about 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.
Check out my About and Projects pages to learn about my educational background and workplace experiences. I maintain a blog, where I occasionally post about readings that catch my interest. Outside of work, I enjoy following cricket, playing board games, and going out on nature walks.