Physics · Cornell University · Class of 2028
Finding signals in chaotic systems —
from ionospheric plasma to electricity markets.
Descend
~600km · Magnetosphere
I study how information hides in complex systems — whether that's electron density fluctuations in the ionosphere or ensemble spread in weather forecasts that predicts electricity price spikes. The tools are the same. The instinct is the same.
~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.
Serving as Team Leader for the Malaysian Physics Olympiad team — an unusually senior role for an undergraduate. Prepared teaching materials covering plasma physics, magnetospheric dynamics, and auroral physics.
~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. Next semester: 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.
Built with Next.js · Three.js · Cornell, NY