Physics · Cornell University · Class of 2028
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~600km · Magnetosphere
Hello, I'm a physics student at Cornell interested in turning data from physical systems into useful information for decision-making. My work sits across space weather, meteorological forecasting and commodity markets. I've worked on radar signatures in the ionosphere, weather ensembles for power markets as well as soil-moisture signals for agricultural forecasting. So yes, basically a glorified data scientist.
~250km · Satellites
End-to-end pipeline studying Medium-Scale Travelling Ionospheric Disturbances. Downloads RINEX files from NOAA CORS S3, computes ionospheric pierce points at 250km, applies degree-10 polynomial detrending.
~10km · Troposphere
Predicting next-day PJM electricity price volatility using GEFS 31-member ensemble spread. When meteorologists disagree about tomorrow's temperature, power traders should price that uncertainty.
Ground sensor network analysis on soil moisture data as a Data Team member at CU GeoData.
LSTM model for soybean yield prediction, bringing sequence modeling to agricultural remote sensing.
~0km · Ground Level
Collaborating with a PhD student on real-time LMP modeling for the Malaysian electricity market. TBD.
Open to energy trading roles, research collaborations, and conversations about chaotic systems in any form.
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