I'm a machine learning engineer and hydrometeorologist with a PhD in Hydrology and Atmospheric Sciences, and I build production ML systems for environmental problems. My work centers on forecasting and remote sensing: satellite-based flood detection, including fine-tuning geospatial foundation models on radar imagery, weather nowcasting, and satellite analytics such as crop detection. I contributed to NASA's Global Precipitation Climatology Project (V3.2) and received the NASA Robert H. Goddard Award as part of the GPCP team.
On the side, I like turning data into things people can actually use: small open tools, and short write-ups of what they show, from measuring lakes from space to mapping the taxes you would pay across the country. I'm also into personal finance and investing, and I build tools and write on 401(k) strategy, retirement, and long-term wealth building, leaning on data and backtests rather than opinions.
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