Colloquia
Re-Imagining the Search for Fundamental Interactions with Machine Learning
Argonne National Lab Physics Colloquium, Nov. 2023.
Machine Learning for Fundamental Physics
Yale University Physics Department Colloquium, October 2022.
What can deep learning teach us about particle physics?
University of San Francisco Department of Physics and Astronomy Colloquium, September 2022.
What can deep learning teach us about particle physics?
TRIUMF Colloquium, April 2022.
What can deep learning teach us about particle physics?
IFIC Colloquium, May 2021.
High dimensional jet measurements in pp and ep collisions
SMU Physics Department Speaker Series, Feb. 2021.
Deep Learning, Quantum Information, and the LHC as a Gluon Factory
MIT Laboratory for Nuclear Science Colloquium, September, 2019.
What can deep learning teach us about fundamental physics?
Aspen Physics Center Colloquium, September, 2019.
Student Becomes Teacher: How Machine Learning can Teach us Fundamental Physics
Cornell University Physics Department Colloquium, March 2019.
Rutgers University Physics Department Colloquium, March 2019.
Advancing High Energy Physics with Machine Learning
2018 APS/Gorden & Betty Moore Foundation Fundamental Physics Innovation Lectureship, University of California Riverside, Jan. 2019.
Advanced Machine Learning for Classification, Regression, and Generation in Jet Physics
CERN Data science seminar, November 2017.
Modern Machine Learning with Jet Images for Experimental High Energy Physics
University of California, Santa Cruz Physics Department Colloquium, October 2017.