15, delhi. i spend most of my time on math, algorithms, and ML

map<string, string> ongoing_work = {
    {"competitive_programming", "CF ~1650,USACO Gold → pushing Platinum, aiming for IOI 2027", "Content author @USACO.guide"},
    {"olympiad_math",           "RMO qual, targeting INMO"},
    {"ml_research",             "KAZE -> predicting dust mineral composition from satellite data(working on publishing)"},
    {"this_summer",             "software engineering intern @ [redacted] + ML research"}
};

• linear algebra, calc I–III, probability, abstract algebra, discrete math
• MIT OCW: 6.042J, 6.006, 6.036 — currently doing 14.310x (econometrics), Stanford CS229
• languages: C++, Python, JS | ML: PyTorch, NumPy, Pandas

ML-econ: automated mechanism design, learned auctions, incentive compatibility. also getting into causal inference lately, feels like the more rigorous way to actually answer empirical questions rather than just finding correlations. doing 14.310x and CS229 to fill in the gaps.

KAZE started because i wanted to understand how dust storms move. ended up building a three-head neural net pipeline ingesting MODIS, EMIT, AERONET, and ERA5 data. working on getting it published.

if you're working on something in this space, open to talking.