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Gordon Watts (he/him/his)

Professor

Contact Information

206-543-4186
B203

Biography

B.S., Physics and Math, University of Texas at Austin, 1989
Ph.D., Physics, University of Rochester, 1994

My research focuses on using collider experiments to explore beyond the Standard Model theories, addressing questions of dark matter and the matter-antimatter imbalance in the universe. I have a particular interest in theories predicting long-lived particle final states and advancing computing methodologies in particle physics.

I am actively involved in several projects:

  • ATLAS Experiment at CERN: As a member of the ATLAS collaboration at the LHC, I contribute to searches for long-lived particles decaying in the calorimeter, employing machine learning techniques to enhance detection capabilities.

  • IRIS-HEP: I am the deputy executive director of the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP), an NSF-funded software institute developing cyberinfrastructure for data-intensive research at the HL-LHC. My focus is physics analysis software, infrastructure, and tools.

  • MATHUSLA Collaboration: MATHUSLA aims to detect ultra-long-lived particles that the main detectors at the LHC might miss.

I have been involved in various experiments, including DZERO and CDF at the Tevatron at Fermilab and the AMY experiment at KEK in Japan. I have led flavor tagging groups in ATLAS and DZERO and contributed to significant discoveries such as the top quark, single-top quark production, and Higgs boson searches.

I am dedicated to education and outreach, with extensive teaching experience in classrooms, labs, and tutorial settings.

I have contributed to the physics community through various service roles, including serving on the Executive Committee of the Division of Particles and Fields (DPF) of the American Physical Society (APS). I co-chaired the 800-person 2022 Snowmass Community Summer Study Workshop and have participated in organizing international conferences like the ACAT, CHEP and MODE workshop on differentiable programming series.

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