Curriculum Vitae

The full CV is available as a PDF.

Education

Ph.D., Physics

Southern Methodist University, Dallas, TX, USA · August 2014 to August 2019

• Dissertation Advisor: Prof. Stephen J. Sekula
• Dissertation: A Search for Boosted Low Mass Resonances Decaying to the b\bar{b} Final State and Produced in Association with a Jet at \sqrt{s} = 13~\mathrm{TeV} with the ATLAS Detector

M.S., Physics

Southern Methodist University, Dallas, TX, USA · August 2014 to December 2016

M.A., Physics

University of Virginia, Charlottesville, VA, USA · August 2012 to December 2013

B.S., Engineering Physics; Mathematics Minor

University of Illinois at Urbana-Champaign, Urbana, IL, USA · August 2007 to May 2012

Research Experience

Research Scientist

University of Wisconsin–Madison, Madison, WI, USA · June 2024 to present

Data Science Institute, Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP), ATLAS Experiment. Principal Investigator: Kyle Cranmer, Data Science Institute.

• Data science applications for experimental high energy physics, data physicist
• IRIS-HEP Executive Board member
• IRIS-HEP Analysis Systems Area Lead
• Large model parameter scan of pMSSM analyses with the ATLAS detector
• Analysis preservation, reuse, and reinterpretation for the ATLAS collaboration

Postdoctoral Research Associate

University of Wisconsin–Madison, Madison, WI, USA · June 2022 to June 2024

Data Science Institute, Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP), ATLAS Experiment. Advising Principal Investigator: Kyle Cranmer, Data Science Institute.

• Data science applications for experimental high energy physics, data physicist
• IRIS-HEP Executive Board member
• IRIS-HEP Analysis Systems Area Lead
• Large model parameter scan of pMSSM analyses with the ATLAS detector
• Search for resonant HH production with the ATLAS detector
• Analysis preservation, reuse, and reinterpretation for the ATLAS collaboration

Postdoctoral Research Associate

University of Illinois at Urbana-Champaign, Urbana, IL, USA · August 2019 to June 2022

ATLAS Experiment, Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP). Advising Principal Investigator: Mark S. Neubauer, Department of Physics.

• Search for resonant HH production with the ATLAS detector
• Analysis preservation, reuse, and reinterpretation for the ATLAS collaboration
• Analysis Systems for IRIS-HEP

Ph.D. Candidate

Southern Methodist University, Dallas, TX, USA · January 2015 to August 2019

High Energy Physics Group. Advising Professor: Stephen J. Sekula, Department of Physics.

• Search for low mass dark matter mediators at high p_T in the Z' \to b\bar{b} + ISR jet decay channel
• Study of the Higgs cross-section at high p_T in the H \to b\bar{b} + ISR jet decay channel

Selected Papers, Notes, and Publications

• Alexander Puck Neuwirth, Matthew Feickert, Lukas Heinrich, Eduardo Rodrigues, pylhe: A Lightweight Python interface to Les Houches Event files. Journal of Open Source Software, 11(126), 11128, Oct, 2026. DOI: 10.21105/joss.11128
• Claudius Krause, Ramon Winterhalder, Matthew Feickert, Benjamin Nachman, The Living Guide of Machine Learning for Particle Physics. Aug, 2026. arXiv:2608.09531
• Jon Butterworth et al., Reinterpretation and preservation of data and analyses in HEP. Apr, 2025. arXiv:2504.00256
• Diego Ciangottini et al., Analysis Facilities White Paper. Apr, 2024. arXiv:2404.02100
• Marco Donadoni et al., Scalable ATLAS pMSSM computational workflows using containerised REANA reusable analysis platform. Mar, 2024. DOI: 10.1051/epjconf/202429504035 arXiv:2403.03494
• Matthew Feickert, Lukas Heinrich, Malin Horstmann, Bayesian Methodologies with pyhf. Sep, 2023. DOI: 10.1051/epjconf/202429506004 arXiv:2309.17005
• Matthew Feickert, Daniel S. Katz, Mark S. Neubauer, Elizabeth Sexton-Kennedy, Graeme A. Stewart, Software Citation in HEP: Current State and Recommendations for the Future. Sep, 2023. DOI: 10.1051/epjconf/202429508017 arXiv:2309.14571
• ATLAS Collaboration, Measurements of multijet event isotropies using optimal transport with the ATLAS detector. JHEP 10 (2023) 060. May, 2023. DOI: 10.1007/JHEP10(2023)060 arXiv:2305.16930
• Brian Bockelman, Peter Elmer, Gordon Watts et al., IRIS-HEP Strategic Plan for the Next Phase of Software Upgrades for HL-LHC Physics. Feb, 2023. arXiv:2302.01317
• Stephen Bailey, Kyle Cranmer, Matthew Feickert, Rob Fine, Sabine Kraml, Clemens Lange, Reinterpretation and Long-Term Preservation of Data and Code. Snowmass 2021 Computational Frontier CompF7 topical group report. Sep, 2022. arXiv:2209.08054
• Gabriele Benelli et al., Data Science and Machine Learning in Education. Contribution to 2022 Snowmass Summer Study. Jul, 2022. arXiv:2207.09060
• Stephen Bailey et al., Data and Analysis Preservation, Recasting, and Reinterpretation. Contribution to 2022 Snowmass Summer Study. Mar, 2022. arXiv:2203.10057
• Kyle Cranmer et al., Publishing statistical models: Getting the most out of particle physics experiments. SciPost Phys. 12, 037 (2022). Sep, 2021. DOI: 10.21468/SciPostPhys.12.1.037 arXiv:2109.04981
• ATLAS Collaboration, Configuration and performance of the ATLAS b-jet triggers in Run 2. Eur. Phys. J. C 81, 1087 (2021). Jun, 2021. DOI: 10.1140/epjc/s10052-021-09775-5 arXiv:2106.03584
• Lukas Heinrich, Matthew Feickert, Giordon Stark, Kyle Cranmer, pyhf: pure-Python implementation of HistFactory statistical models. Journal of Open Source Software, 6(58), 2823, Feb, 2021. DOI: 10.21105/joss.02823
• Matthew Feickert, Benjamin Nachman, A Living Review of Machine Learning for Particle Physics. Feb, 2021. arXiv:2102.02770
• Daniel S. Katz et al., Software Sustainability & High Energy Physics. Oct, 2020. DOI: 10.5281/zenodo.4082137
• LHC Reinterpretation Forum Collaboration, Reinterpretation of LHC Results for New Physics: Status and Recommendations after Run 2. Mar, 2020. DOI: 10.21468/SciPostPhys.9.2.022
• ATLAS Collaboration, Reproducing searches for new physics with the ATLAS experiment through publication of full statistical likelihoods. Aug, 2019. CDS: ATL-PHYS-PUB-2019-029
• ATLAS Collaboration, Search for boosted resonances decaying to two b-quarks and produced in association with a jet at \sqrt{s} = 13~\mathrm{TeV} with the ATLAS detector. Nov, 2018. CDS: ATLAS-CONF-2018-052
• K. Albertsson et al., Machine Learning in High Energy Physics Community White Paper. 2018. arXiv:1807.02876

Selected Proceedings and Reports

• KyungEon Choi et al., Building a Columnar Analysis Demonstrator for ATLAS PHYSLITE Open Data using the Python Ecosystem. 27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024), Oct, 2025. DOI: 10.1051/epjconf/202533701359
• Alexander Held et al., The 200 Gbps Challenge: Imagining HL-LHC analysis facilities. 27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024), Oct, 2025. DOI: 10.1051/epjconf/202533701217
• Robert W. Gardner Jr. et al., Operating the 200 Gbps IRIS-HEP Demonstrator for ATLAS. 27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024), Oct, 2025. DOI: 10.1051/epjconf/202533701061
• Marco Donadoni et al., Benchmarking massively-parallel Analysis Grand Challenge workflows using Snakemake and REANA. 27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024), Oct, 2025. DOI: 10.1051/epjconf/202533701168
• Matthew Feickert, Ruben Arts, John Kirkham, Reproducible Machine Learning Workflows for Scientists with Pixi. Proceedings of 24th International SciPy Conference — SciPy 2025, Jul, 2025. DOI: 10.25080/nwuf8465
• Matthew Feickert et al., How the Scientific Python ecosystem helps answer fundamental questions of the Universe. Proceedings of 23rd International SciPy Conference — SciPy 2024, Jul, 2024. DOI: 10.25080/KMXN4784
• Matthew Feickert, Lukas Heinrich, Giordon Stark, pyhf: a pure-Python statistical fitting library with tensors and automatic differentiation. Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP 2022) 414 (2022) 245, Nov, 2022. DOI: 10.22323/1.414.0245 arXiv:2211.15838
• Matthew Feickert, Mihir Katare, Mark Neubauer, Avik Roy, Deep Learning for the Matrix Element Method. Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP 2022) 414 (2022) 246, Nov, 2022. DOI: 10.22323/1.414.0246 arXiv:2211.11910
• S. Malik et al., Software Training in HEP. Computing and Software for Big Science 5 (2021) 22, Oct, 2021. DOI: 10.1007/s41781-021-00069-9 arXiv:2103.00659
• M. Feickert, L. Heinrich, G. Stark, B. Galewsky, Distributed statistical inference with pyhf enabled through funcX. EPJ Web Conf. 251 (2021) 02070, Mar, 2021. DOI: 10.1051/epjconf/202125102070 arXiv:2103.02182
• Matthew Feickert, Lukas Heinrich, Giordon Stark, Likelihood preservation and statistical reproduction of searches for new physics. EPJ Web Conf. 245 (2020) 0617, Nov, 2020. DOI: 10.1051/epjconf/202024506017
• E. Rodrigues et al., The Scikit HEP Project — overview and prospects. EPJ Web Conf. 245 (2020) 0628, Jul, 2020. DOI: 10.1051/epjconf/202024506028 arXiv:2007.03577
• Matthew Feickert and John Alison, Performance of the ATLAS b-jet trigger in 2017 data at high pile-up. Nov, 2017. CDS: ATL-COM-DAQ-2017-182

Magazine and Online Articles

• Matthew Feickert, Extending ATLAS Physics Reach with Analysis Reuse Technology. CERN EP Newsletter, March, 2024.