M.S. Financial Engineering — NYU Tandon
Building at the intersection of stochastic modeling, statistical learning, and systematic trading. Focused on regime-based allocation, risk analytics, and signal research.
I'm a Financial Engineering graduate student at NYU Tandon, with an undergraduate degree in Computer Science (AI/ML specialization) from SRM University on a 100% scholarship.
My work sits at the convergence of quantitative finance and machine learning—from Hidden Markov regime models and bootstrap-validated trading strategies, to sector-level clustering of S&P 500 market structures. I care deeply about statistical rigor: if it can't survive a null hypothesis test, it doesn't ship.
Currently seeking quant research, strats, and risk roles where I can apply probabilistic modeling and systematic thinking to real market problems.
Developed a secure, cross-platform digital consent collector using SHA-256 cryptographic hashing, ensuring regulatory compliance for the ADeX government platform. Engineered full-stack JavaScript solutions enabling 38 critical datasets for a government-academia joint venture.
Represented 10,000+ students as primary liaison to administration. Directed cross-functional teams to execute cultural fests with $100,000+ budgets.
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