When Jeffrey Varner, professor of chemical and biomolecular engineering, first joined Cornell in 2005, his teaching and research focused on modeling and analyzing biological systems, with an emphasis on how disease perturbs the regular operation of these systems. Over time, he grew interested in another complex, dynamic system – financial markets – a pivot that would catalyze a new curricular spine at the R.F. Smith School.
In 2022, Varner translated his new focus into teaching, bringing the same engineering mindset to financial markets: how to model them, understand their statistical structure and design automated financial decision systems. He developed two complementary courses for engineers: data science and computational methods, and machine learning and artificial intelligence for STEM. This two-course sequence explores diverse applications, from classical process engineering to human health and quantitative finance, and now anchors the revamped Master of Engineering program, which Varner helps lead as associate director.
In 2025, these courses were recognized as the number one program in the Best Master’s in Data Science & Artificial Intelligence rankings by MastersInAI.org. Varner is now busy converting the classroom experience into an eCornell certificate, maintaining a careful balance between theoretical rigor and hands‑on practice that has made the in-person courses successful.
The marquee offering developed by Varner is the Quantitative Finance for Engineers course, launched in 2022. This course now draws more than 140 students across Cornell Engineering and has expanded to both in-person and online sections to meet demand. The course moves quickly from the time value of money to the empirical properties of equity returns, simulation models for debt and equity prices, and the pricing and interesting applications of derivative products. The final three weeks focus on AI in quantitative finance, from alpha discovery to portfolio management, and conclude with the release of an automated trading agent. The trade-bot capstone has become a popular tradition in the course. Alums of the course have gone on to take quantitative finance and trading roles after graduation at some leading firms in the space.
Building on that momentum, Varner launched an eCornell quantitative finance certificate in 2025 and is collaborating with Cornell Financial Engineering in Manhattan on a new in-person certificate that explores AI tools for contemporary problems in finance, set to debut in 2026. He contributes to workshops and conferences, including the 2025 Future of Finance AI meeting hosted by Cornell Financial Engineering in Manhattan.
“Teaching CHEME 5660 is a privilege,” said Varner. “The material is alive, the students push me, and I walk out of most lectures having learned something new.”
Across these efforts, the throughline is steady: use engineering principles to build models that inform decisions. Looking ahead, Varner aims to equip students to reason with data, design robust decision-making systems, and apply that discipline to biological networks, financial markets and every other complex system that chemical engineers may encounter.