About Me
I am Yongbin Feng (冯永彬 in Chinese), an assistant professor at Department of Physics and Astronomy of Texas Tech University studying experimental particle physics (HEP-ex). More information can be found in my CV [link].
For potential graduate students and postdocs interested in any of the topics of CMS data analyses, advanced calorimeter R&D (especially on the simulation and machine learning assisting reconstruction), heterogeneous computing with or without machine learning, and search for dark sector and dark matter at small fixed-target experiments, please feel free to contact me!
Work Experience
- Assistant Professor of Physics at Texas Tech University
Lubbock, Texas, USA, Aug. 2024 - present
- Postdoctoral Research Associate at Fermi National Accelerator Laboratory
Batavia, Illinois, USA, Nov. 2020 - Jul. 2024
Education
- Physics Ph.D.: University of Maryland, College Park, Maryland, USA, Aug. 2015 - Oct. 2020
- Physics B.S.: University of Science and Technology of China, Hefei, Anhui, China, Aug. 2011 - Jun. 2015
Research Interests
- High Precision Electroweak Measurements: W and Z cross sections, differential cross sections, etc [Pub]
- SONIC: Services of Network Inferences on Coprocessors for CMS and other experiments [Pub]
- Machine Learning Application in HEP: pileup mitigation, missing transverse momentum regression, calorimeter clustering and energy regression, etc [Pub]
- DarkQuest: proton fixed-target experiment to search for dark sector and light dark matter [Pub]
News
To be updated
Publications
To be updated
Talks & Seminars
- Introduction to Graph Neural Networks in High Energy Physics
Discussion led at the Fermilab Lab-wide AI Meeting, Batavia, 11/2022 [Slides].
- DarkQuest: Probing dark sector with a proton fixed-target experiment at Fermilab
Talk presented at the SYSU-PKU Particle Physics Forum, Virtual, 05/2022 [Slides].
- Semi-supervised graph neural network for pileup noise removal
Talk presented at the University of Washington Machine Learning Forum, Virtual, 05/2022 [Slides].
- DarkQuest - Searching for light dark matter with a proton fixed-target experiment at Fermilab
Talk presented at the 2022 Phenomenology Symposium, Pittsburg, Pennsylvania, USA, 05/2022 [Slides].
- Semi-supervised meachine learning for pileup per particle identification with graph neural networks
Talk presented at the 2021 BOOST workshop, Virtual, 08/2021 [Slides].
- Searching for light dark matter at Fermilab’s proton fixed-target experiment: DarkQuest
Talk presented at the 2021 Particle Physics and Cosmology workshop, Virtual, 05/2021 [Slides].
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