Lauren Conger
PhD candidate at Caltech
I am an applied mathematician and engineer interested in the use of mathematical analysis driven by emerging applications in the information sciences. I build analysis tools to lift finite-dimensional results in control theory, game theory and machine learning to infinite dimensions, elucidating new application insights that depend on this infinite-dimensional structure. In game theory, I extend classical finite-dimension notions of contractivity to the (infinite-dimensional) measure-valued setting via analysis of coupled multispecies gradient flows. In control theory, among core distributed control results, my work lifts a recent parameterization to the (infinite-dimensional) Hilbert space setting. In support of robust machine learning, I analyze (infinite-dimensional) distributional models to illustrate the effects of strategic agents on learning algorithms.
I am final-year PhD candidate in Control and Dynamical Systems at Caltech, advised by Professors Eric Mazumdar, Franca Hoffmann and John Doyle, and and am currently on the academic job market.
Before Caltech, I earned my Bachelors degree in Electrical and Computer Engineering with a physics minor from Cornell University in 2018. My work is supported by a National Defense Science and Engineering Graduate Fellowship and PIMCO Data Science Graduate Fellowship. You can reach me at lconger [at] caltech [dot] edu.
Selected Publications
Preprints
Conference Papers
Journal Papers
Workshop Papers
Talks and Visits
Projects
System Level Synthesis for Evolution Equations
This repository contains the python code that accompanies the paper \\ Lauren Conger, Antoine P. Leeman and Franca Hoffmann. “Convex Constrained Controller Synthesis for Evolution Equations” IEEE ACC 2025.
Optimal Transport via Min-Max Gradient Flows
This repository contains code accompanying the paper \\ Lauren Conger, Franca Hoffmann, Ricardo Baptista, Eric Mazumdar "Computing Optimal Transport Plans via Min-Max Gradient Flows" IEEE CDC 225.
Teaching
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CS 143: Networks: Algorithms & Architecture Fall 2025
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CDS 131: Linear Systems Winter 2025Developed course material and lectured on system level synthesis. Lecture notes posted soon!
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CS 42: Computer Science Education in K-14 Settings Winter 2024
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CDS 131: Linear Systems Fall 2023
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CS 144: Networks and Economics Winter 2021
Gradient Flows Reading Group
Graduate students and postdocs from around the world meet bi-weekly to discuss research papers related to gradient flows, optimal transport, and mean-field games. Please email me if you would like to join the mailing list or volunteer to present!