Tyler LaBonte

A photograph of me. 

Tyler LaBonte
Machine Learning Research Intern at X, the moonshot factory
Viterbi Fellow at the University of Southern California
t + lastname@usc.edu

About Me

I am a machine learning research intern at X, the moonshot factory – Alphabet's innovation lab – and an undergraduate researcher in the Theory Group at USC. I have been fortunate to be advised by Shaddin Dughmi, Jason D. Lee, and David Kempe. Previously, I was a machine learning research intern at Sandia National Laboratories and the Air Force Research Laboratory.

I take a scientific approach to reconcile theory with empirical phenomena in deep learning. I develop fast, scrappy experiments that challenge conventional wisdom, then use the results to guide and revise theoretical hypotheses. My undergraduate research has focused on convex optimization, computer vision, and Bayesian learning.

I will graduate from USC in May 2021 with my B.S. in Applied and Computational Mathematics. I am currently applying to Ph.D. programs in machine learning theory. If you are interested in working together, please contact me!

Research Interests

  • Mathematical Foundations of Machine Learning

  • Generalization Theory of Deep Learning

  • Convex and Non-Convex Optimization

  • Online Learning and Bandit Problems

Selected Awards

  • SIMLR Award for Outstanding Intern

  • USC Trustee Scholar ($250,000)

  • USC Viterbi Fellow ($24,000)

  • Dolphin Scholarship ($13,600)

  • Admiral Bernard Clarey Memorial Scholarship ($7,000)

Selected Publications