Mark Neubauer
Affiliate Professor, Department Of Electrical And Computer Engineering
Urbana, Illinois, United States
Summary
👤
Senior🎓
Top SchoolMark Neubauer is a professor and experimental particle physicist at the University of Illinois Urbana-Champaign with affiliate appointments in Electrical & Computer Engineering, NCSA, and the Discovery Partners Institute. He played a pivotal role in landmark neutrino and electroweak measurements—his PhD work on SNO provided the first direct evidence of electron neutrino flavor change and his group later contributed to Higgs discovery and its decay to W pairs. Neubauer leads searches for physics beyond the Standard Model using ATLAS data at the LHC, leveraging the Higgs as a precision probe and advancing detector capabilities through machine learning and advanced electronics. Trained at the University of Pennsylvania and seasoned by postdoctoral work at MIT and UC San Diego, he blends deep experimental expertise with interdisciplinary engineering. He is based in Urbana and is notable for bridging large-scale collaborative physics with practical efforts to modernize instrumentation and data analysis.
10 years of coding experience
17 years of employment as a software developer
Bachelor of Science - BS, Bachelor of Science - BS at Kutztown University of PennsylvaniaDoctor of Philosophy - PhD, Elementary Particle Physics, Doctor of Philosophy - PhD, Elementary Particle Physics at University of Pennsylvania
Github Skills (25)
foundation10
energy10
high-energy-physics10
snl-applications10
physics10
voila9
fpga8
data-analysis8
pruning8
quantization-aware-training8
machine-learning8
atlas6
mlp6
jupyter-notebook5
html5
Programming languages (10)
Github contributions (5)
illinois-mlp/MachineLearningForPhysics
Jan 2024 - Apr 2026
This is the top-level repository for the Machine Learning for Physics (PHYS 498 MLP) course at the University of Illinois at Urbana-Champaign
Contributions:306 pushes, 2 branches in 2 years 3 months
machine-learningmlp
illinois-ipaml/MachineLearningForPhysics
Aug 2023 - Nov 2025
This is the top-level repository for the Instrumentation Physics Applications of Machine Learning (PHYS 503) course at the University of Illinois at Urbana-Champaign
Contributions:1 review, 6 PRs, 218 pushes in 2 years 3 months
machine-learning
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.