Designing My Own Major at WPI: Quantitative Financial Systems Engineering

I’m creating a custom combined BS/MS major at WPI called Quantitative Financial Systems Engineering: a degree built for the future of automation and intelligence in financial markets. Today’s markets are driven not by human intuition, but by mathematical models, high-performance computing, and AI systems making decisions in milliseconds. I wanted a program that reflects that reality: one that engineers how finance actually works underneath the surface. ` - This major blends three fields that are usually kept separate: - Applied Mathematics for stochastic modeling, optimization, and pricing theory - Distributed Computing & Machine Learning for real-time simulation and decision systems - Quantitative Finance for understanding how markets behave and evolve under uncertainty

Instead of studying these disciplines in isolation, this program unifies them to design the algorithms, infrastructure, and intelligence behind global financial systems.

At WPI, I’m structuring my degree around project-based milestones: including a market simulation platform, a stochastic AI modeling engine, and socio-technical optimization research. These projects bridge the gap between theory and real-world implementation, preparing me to operate at the intersection of financial strategy and computational engineering.

Ultimately, this major is my way of building the education I need for the career I want: creating technologies that can reason about risk, optimize liquidity, and adapt to markets faster than any human. Finance is becoming an engineering discipline. This program is my contribution to what comes next.