Taylor Childers

Taylor Childers is a Computer Scientist specializing in high-performance computing and particle physics, currently working in the Leadership Computing Facility division at Argonne National Laboratory. Taylor is the Deputy Technical Lead for the ALCF-4 project and a member of the Data Services & Workflows Group at ALCF. He works with HEP scientists to accelerate and scale their codes on current supercomputing resources, engages with all users for training and mentoring, and is planning for the post-Exascale supercomputing future.

He graduated from the University of Kentucky in 2002 with a B.S. in Physics. In 2007, he earned his Ph.D. in Physics from the University of Minnesota. His Ph.D. thesis involved studying cosmic rays as a member of the CREAM (Cosmic Ray Energetics And Mass) collaboration, utilizing a particle physics detector suspended from a high-altitude balloon flown above Antarctica. 



From 2007 to 2011, Taylor worked as a post-doctoral researcher at Universität Heidelberg in Germany. As a member of the ATLAS collaboration at CERN in Switzerland, he installed, calibrated, and operated the trigger electronics for the Level-1 Calorimeter Trigger, which made rapid store or not-store decisions for collision events within a 7-microsecond latency. This system reduced the 40MHz collision rate to around 10kHz using custom hardware in VME crates.



In 2011, Taylor was awarded a rare two-year fellowship by CERN, a notable achievement for a citizen of a non-member state. He continued his work with the ATLAS collaboration, focusing on the L1 Central Trigger and Top Quark physics in the Standard Model Group.



In 2013, Taylor joined the Argonne ATLAS group in the HEP division as an Assistant Physicist. He worked on adapting and scaling high-energy physics simulation codes for the Mira supercomputer. This work included running LHC simulation at the scale of 1 million concurrent processes on Mira to produce leading-order vector boson plus jet processes for the ATLAS experiment.

After working closely with the ALCF for many years, Taylor transitioned to become a Computer Scientist in the Datascience group in 2018. In this new role, he continued to engage with HEP scientists in their efforts to leverage supercomputers to speed up time to results. His own research shifted to applying newly popular Deep Learning methods, spawning a collaboration with Rochester Institute of Technology, to study the application of Graph Neural Networks on the raw detector data from the ATLAS detector.