In late Feb 2025, I joined the research science faculty at the University of Maryland, College Park (UMD)'s Applied Research Laboratory for Intelligence & Security (ARLIS) as well as the AI Interdisciplinary Institute at Maryland (AIM) and the Department of Physics.
Education
Doctorate in Physics from University of Oxford (Rhodes Scholarship)
B.S. Honors (x2) in Physics & Astronomy from the University of Texas at Austin
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I was also at Caltech and University of California - Irvine and Riverside.
Research Interests
-Applied & Basic AI/ML
-Quantum Science and Technologies (incl. algorithms)
-Mathematical foundations for:
machine learning, logic, & intelligence
quantum information science & physics
Reach out for a recent CV:
millesa
and then the normal symbol that goes here
umd dot edu
Miller, Kocoglu, Argyle, Lakhdar-Hamina, Casey, Galitski, Lopata. Quantum Spectral Neural Networks: Adaptive Spectral Architectures with Modes as Neurons. (to submit 2026)
Argyle, Lakhdar-Hamina, Miller, Galitski. Measurement-Induced Quantum Neural Network. (submitted 2026): https://arxiv.org/abs/2603.19200
Shou, Miller, Galitski. Proof of Hiding Conjecture in Gaussian Boson Sampling. (submitted 2025, accepted @ Quantum 2026): https://arxiv.org/abs/2508.00983
Lakhdar-Hamina, Liu, Barney, Miller, Green, Linke, Galitski. Benchmarking a Tunable Quantum Neural Network on Trapped-Ion and Superconducting Hardware. (submitted 2025, accepted @ PRL 2026): https://arxiv.org/abs/2507.21222
Davies, Miller, Milley. On Sums of 𝒫-free forms Under Misère Play. (submitted 2025, accepted @ Integers 2026) : https://arxiv.org/abs/2506.05257
Miller. Spacetime symmetries and Topological Quantum Theory of sided sets (papers in prep, talk given at first annual Inspiring Math conference 2025, Chicago IL)
Miller. Surreal Observables (paper in prep, talk given at Universality in Physics Workshop, EMFCSC, Erice - Sicily, May 2026)
Miller. CGT foundations for neural networks (paper in prep, material in talk at Inspiring Math 2025)
I conducted physics and astrophysics research at Caltech and the University of California, Irvine (on a Chancellor's Fellowship) & Riverside (advising students), after receiving my doctorate at Oxford. I modeled the dynamics of the largest collection of high redshift rotation curves at that time with high quality spectra. I used data mostly from instruments on the Keck Telescopes and the Hubble Space Telescope, ultimately trying to probe how dark matter evolves across the age of the universe in disk galaxies with respect to "normal matter." My supervisors and mentors included Richard Ellis, Mark Sullivan, James Bullock, Bahram Mobasher, and my luck continued with many more amazing collaborators. I was also fortunate to help advise many talented students during this time as well. A couple examples of work from this period include:
Miller, Bundy, Sullivan, Ellis, & Treu, (2011) The Astrophysical Journal, 741. https://arxiv.org/abs/1102.3911
Miller, Ellis, Sullivan, Bundy, Newman, Treu (2012) The Astrophysical Journal 753 74 https://arxiv.org/abs/1201.4386
I also led a study at the Keck Institute for Space Studies on airships as a new kind of platform for science:
Miller, Fesen, Hillenbrand, Rhodes, Baird, Blake, Booth, Carlile, Duren, Edworthy, Freeze, Friedl, Goldsmith, Hall, Hoffman, Hovarter, Jensen-Clem, Jones, Kauffmann, Kiessling, King, Konidaris, Lachenmeier, Lord, Neu, Quetin, Ram, Sander, Simard, Smith, Smith, Smoot, Susca, Swann, Young, Zambrano (2014) Airships: A New Horizon for Science. https://arxiv.org/abs/1402.6706
Before that I worked in theoretic physics research in the areas of general relativity and gravitational radiation with Richard Matzner at the Center for Relativity at the University of Texas at Austin, as well as with Shardha Jogee, working on automated methods to analyze large surveys to better understand galaxy evolution and cosmology. A couple examples include:
Miller & Matzner. (2009) Multipole Analysis of Kicks in Collision of Binary Black Holes Gen.Rel.Grav.41:525-539 https://arxiv.org/abs/0807.3028
Jogee, Miller, Penner, et al. (2009) The Astrophysical Journal, 697, 1971 - 1992. https://arxiv.org/abs/0903.3700
I left my astrophysics postdoctoral fellowship early to begin serving as a data scientst, and eventually Lead Scientist and then Chief Scientist, in increasingly broad AI/ML adoption and coordination programs in the United States federal government. I started out in hands-on applied machine learning roles, and after some years, began working on increasingly broader enterprise and policy-related initiatives in increasingly impactful leadership roles. Eventually I was working to coordinate programs across multiple Agencies and Departments, including support to the White House, and regularly briefing multiple Congressional and Judiciary components. I was honored for both excellence in my work as well as championing privacy and civil liberties in enduring ways, from grassroots efforts to high-level policy-related work.
https://www.intelligence.gov/ai/ai-ethics-framework