Kaleigh Mentzer

Hi, I’m Kaleigh Mentzer.

My name is Katherine Leigh Mentzer, I go by Kaleigh.

I recently completed my Ph.D. in Computational and Mathematical Engineering at Stanford University, advised by Irene Lo and Itai Ashlagi. My dissertation work focused on using Operations Research tools to improve student assignment algorithms in the San Francisco Unified School District, and our research has influenced educational policy in the district. I enjoy working with stakeholders to formulate, execute, and communicate solutions to computationally difficult algorithmic and optimization-based problems, and I’m passionate about using computational tools to improve equity of access to education.

Before Stanford, I graduated Magna Cum Laude from Dartmouth College with a BA in Physics (with Honors) and a minor in Economics.

Right now, I’m excited about geospatial data, and I’m interested in drawing insights from the HCI community to better communicate computational results.

You can find me on LinkedIn and GitHub.

Recent Updates

  • August 2023: I gave a workshop for Women in Data Science on Student Assinment and Public Sector Collaborations. Video avalable here.
  • August 2023: I taught the Data Visualization workshop for the ICME Fundamentals of Data Science Summer Workshop Series – slides and other course materials available here!
  • July 2023: Our work, Overbooking with Priority-Respecting Reassignment, was accepted to EAAMO – please stop by my co-author’s presentation if you’re attending!
  • July 2023: Completed the Stanford Graduate School of Business Ignite program, an entrepreneurship intesive
  • June 2023: Honored to receive an honorable mention for the Gene Golub Dissertation Award given by ICME.
  • June 2023: Congrats, Granica on the launch! Excited to be joining as a Research Engineer later this summer.
  • March 2023: My work on neural network surrogate models for inertial confinement fusion applications from my time at Lawrence Livermore National Laboratory was published in Physics of Plasmas.
  • December 2022: Topography of pleural epithelial structure enabled by en face isolation and machine learning, a paper I collaborated on, was published in the Journal of Cellular Physiology
  • July 2022: Our work on re-designing student assignment in San Francisco was selected as a finalist for the INFORMS Doing Good with Good OR Student Paper Competition. Looking forward to presenting the work in Indianapolis!
  • June 2022: Excited to start a Data Science internship with the Credit and Collections Machine Learning team at PayPal!
  • June 2022: Honored to receive the Stanford School of Engineering Justice, Equity, Diversity, and Inclusion Graduation Award
  • June 2022: Honored to receive the Stanford Management Science & Engineering Department Course Assistant Award for work on MS&E 323H (Accelerated Game Theory)
  • May 2022: Excited that our paper, “Designing School Choice for Diversity in the San Francisco Unified School District” was accepted to EC ’22!