I am a first-year PhD student in Machine Learning at the Georgia Institute of Technology advised by Tuo Zhao and a Machine Learning Research Intern at Microsoft Research advised by Neel Joshi. My work is generously supported by the DoD NDSEG Fellowship.
I received my BS in Applied and Computational Mathematics at the University of Southern California advised by Shaddin Dughmi, where I was a Trustee Scholar and Viterbi Fellow. My senior thesis in convex optimization received the USC Discovery Scholar distinction for exemplary research. During my undergraduate, I was a Machine Learning Research Intern at Google X and Sandia National Laboratories.
I use theory to develop and understand large-scale machine learning models which can be deployed in high-consequence applications. My current focus is optimization and generalization in deep learning, where I seek to reconcile theoretical understanding with empirical phenomena. I also enjoy working on self-supervised and weakly supervised machine learning, particularly for computer vision applications.
In 2021, I was one of two undergraduates to receive both the DoD NDSEG and NSF GRFP fellowships in Computer Science; the other was Ethan Fahnestock. To democratize the fellowship application process, I have made my essays available here.
- Michael C. Krygier, Tyler LaBonte, Carianne Martinez, Chance Norris, Krish Sharma, Lincoln N. Collins, Partha P. Mukherjee, and Scott A. Roberts. Quantifying the Unknown: Impact of Segmentation Uncertainty on Image-Based Simulations. Nature Communications, 12(5414), 2021.
- Tyler LaBonte. Finding the Needle in a High-Dimensional Haystack: Oracle Methods for Convex Optimization. Undergraduate Thesis, 2021. USC Discovery Scholar distinction.
- Tyler LaBonte, Carianne Martinez, and Scott A. Roberts. We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric Uncertainty. Manuscript, 2019.
- DoD NDSEG Fellowship ($170,000)
- NSF Graduate Research Fellowship ($138,000—declined)
- USC Discovery Scholar (research distinction for <100 USC graduates)
- USC Trustee Scholar ($225,000)
- USC Viterbi Fellow ($24,000)
- Machine Learning Research Intern, Microsoft Research (2021)
- Machine Learning Research Intern, Google X (2020)
- Machine Learning Research Intern, Sandia National Labs (2019)
- Machine Learning Engineer Intern, Air Force Research Lab (2018)
- Pratik Deolasi—Georgia Tech undergrad (2021)
- Rishit Mohan Ahuja—Georgia Tech undergrad (2021)
- USC CSCI 270: Intro to Algorithms and Theory of Computing (2021)
- USC Center for AI in Society: Introduction to Machine Learning (2020)
- USC CSCI 170: Discrete Methods in Computer Science (2019)
Service and Leadership
- Projects Lead, USC Center for AI in Society (2019)
- Associate Director of Robotics Outreach, USC Viterbi K-12 STEM Center (2018)
- Volunteer VEX Robotics Mentor, USC Viterbi K-12 STEM Center (2017—2018)