Welcome! I am a fifth-year Ph.D. candidate in the Operations Research program at Carnegie Mellon University, where I am advised by Gérard Cornuéjols. My research sits at the intersection of integer programming, discrete optimization, and lattice theory, with additional interests in convex optimization, network optimization, and data-driven decision-making. Before my Ph.D., I received a B.Sc. in Industrial Engineering from the University of Wisconsin–Madison in 2022, where I was advised by Yonatan Mintz.

In Summer 2026, I was an applied scientist intern at Amazon in the Modeling and Optimization (MOP) team. I was also a research scientist intern in the MOP team during Summer 2025.

I am also an active member of the INFORMS community, having served as president of the CMU INFORMS Student Chapter from 2024 to 2026.

You can find my CV here.

News

• Nov 2026 (upcoming): Will give a talk on my Amazon internship work at the 2026 INFORMS Annual Meeting, San Francisco, CA.
• Jul 2026: Presented Computing a Nonnegative Dyadic Solution to a System of Linear Equations at Amazon’s Modeling and Optimization (MOP) seminar.
• Oct 2025: Presented a poster on Computing a Nonnegative Dyadic Solution to a System of Linear Equations at the Young Researchers Workshop, Cornell University, Ithaca, NY.
• Jul 2025: Presented Reducing the Chvátal Rank through Binarization at Amazon’s Modeling and Optimization (MOP) seminar.
• Oct 2024: Gave a talk on Reducing the Chvátal Rank through Binarization at the INFORMS Annual Meeting, Seattle, WA.
• Oct 2024: Presented a poster on Addressing Estimation Errors on Expected Asset Returns through Robust Portfolio Optimization at the Young Researchers Workshop, Cornell University, Ithaca, NY.
• Aug 2024: Co-chaired the YinzOR Student Conference.
• Mar 2024: Co-chaired a session and gave a talk on Prescriptive 0-1 Neural Networks for Personalized Medicine at the INFORMS Optimization Society Conference, Houston, TX.