Highlights and Opportunities in AI at Fermilab
In this first joint seminar series, we will highlight current Artificial Intelligence (AI) activities at Fermilab. Machine learning techniques have long been at the core of particle physics. We will present recent scientific results deploying modern deep learning, which has enabled Fermilab to achieve its mission to conduct research in particle physics, from neutrinos, to cosmology, to the energy frontier. We will also discuss the exciting opportunities at the intersection of particle physics and AI that can push the boundaries of new algorithms and hardware to power the next generation of experiments and scientific discovery.
More information: https://indico.fnal.gov/event/22307/ (video link will be provided)
Nhan Tran is currently a Wilson Fellow at Fermilab. Tran’s research focus is on using accelerator-based experiments, such as CMS at the LHC, to search for new phenomena. His current activities center on the Higgs boson and dark sectors experiments. He is developing technology at the intersection of electronics, computing, and artificial intelligence to amplify experimental capabilities. He was a postdoctoral associate at Fermilab, and prior to that he received his PhD from Johns Hopkins University in 2011 and his bachelor’s degree from Princeton University in 2005. Tran is a recipient of the URA Tollestrup Award, the APS Henry Primakoff Award, and the DOE Early Career Award.