I am an Operations Research Scientist in the Data Science team at Convoy. Here, I work on building efficiency into our network of shipments. I develop, deploy, and maintain machine learning and optimization algorithms in production, and I provide quantitative insights to inform product decisions. A high-level description of the problem we are solving for can be found here.
Previously, I received my Ph.D. from the Department of Energy Resources Engineering at Stanford University. My advisor was Prof. Adam Brandt and I was a Wells Family Stanford Graduate Fellow.
In my Ph.D. research, I focused on applying state-of-the-art computational tools at the intersection of machine learning and optimization to energy systems problems. As an example, I have worked extensively on the development of new algorithms and applications of time-series aggregation for infrastructure planning and operations. Out of my research, two open-source software packages have emerged: TimeSeriesClustering implements unsupervised learning methods for time-series data, and CapacityExpansion provides an extensible, data-driven infrastructure planning tool for energy systems.
During my studies, I interned at the battery software company Doosan GridTech; in the renewable energy forecasting division of Vaisala (formerly 3Tier); in the market optimization group at RWE Power, one of Europe’s largest utility companies; and at ThyssenKrupp, one of the world’s largest steel producers.
PhD in Energy Resources Engineering, 2020
Ignite Program in Innovation and Entrepeneurship, 2018
Stanford University, Graduate School of Business
MS in Energy Resources Engineering, 2016
BS in Mechanical Engineering, 2014
RWTH Aachen University
I have successfully worked with multiple companies on short-term and medium-term projects in the past. I would be happy to talk about how we can work together, please contact me for an initial consultation.