Lindsey Gray

Experimental Physicist · Fermilab

I'm a research scientist working at the intersection of sensing, computing, and algorithms, with 20 years in experimental high energy particle physics. Expert in C++ and Python, with experience spanning control systems, data acquisition, data engineering, statistics, AI/ML, and systems design. I lead teams that design novel particle detectors with advanced pattern recognition capabilities, yielding multi-million dollar detector construction projects for science.

Lindsey Gray

Positions & Education

  • Scientist (tenured) · Fermilab2020 – present
  • Associate Scientist (tenure-track) · Fermilab2015 – 2020
  • Research Associate · Fermilab2012 – 2015
  • Ph.D. Experimental HEP · University of Wisconsin – Madison2012
  • B.S. Physics & Mathematics · University of Florida2007

Major Projects

smartpixels

2023 – present

Principal Scientist & Coordinator

First-generation intelligent detector systems: low-power, real-time machine learning embedded directly in pixel detector readout ASICs. Coordinating research across 9 institutes and ~20 contributors, from ML systems design through TSMC 28nm implementation.

TensorFlow · QKeras · HLS4ML · Catapult AI NN · TSMC 28nm

coffea

2019 – present

Project Lead & Developer

Columnar analysis platform for High Energy Physics with hundreds of users and years of published papers built on it. Roughly 1000× faster than the interpreter-bound workflows it replaced, with GPU exploration promising more.

Scientific Python · C++ · HTCondor · SLURM · Kubernetes

MIP Timing Detector

2016 – 2019

Principal Scientist

30-picosecond precision timing detector for CMS. Created 4D reconstruction capabilities now found in textbooks, led the physics justification, and served as interim system manager across 32 institutes while the project was ratified — now being built for the HL-LHC.

C++ · Python · Low-gain avalanche detectors

High Granularity Calorimeter & ML Reconstruction

2014 – 2023

Reconstruction Developer / ML4RECO Lead

Reconstruction algorithms central to the physics case for the CMS endcap calorimeter upgrade, and graph-neural-network based event reconstruction — including the first known deployment of a GNN in NVIDIA Triton.

PyTorch · GNNs · GEANT · C++ · CUDA

CMS Experiment

2008 – present

Physics Researcher

Electroweak and Higgs physics at the LHC: boosted Higgs decays to heavy flavor, effective field theory measurements, future collider studies (FCC-ee, muon collider), and USCMS L2 leadership for HL-LHC software and computing.

C++ · Python · statistical modeling · compute clusters

phase.rs

2026 – present

Core Contributor · Combo-Detection Architect

Open-source Magic: The Gathering rules engine in Rust (34,000+ cards, full comprehensive-rules semantics, native + WASM). Designed and led its infinite-combo detector across a ~25-PR series: certified loop detection via resource-vector net-progress and ω-coverability analysis of growing cascades, driving the paper-Magic loop-shortcut procedure (CR 732.2a–c) — automated offer, opponent response, and collapse — end to end. Second-largest contributor overall (~1,700 commits) spanning engine internals, AI decision logic, and CI.

Rust · WASM · TypeScript · formal methods · game-tree search

Grants

  • Real-time ML (DOE, smart detectors)
    2025–2026 · $350k
  • CODE4hep: future collider software
    2025–2027 · $350k
  • Graph Neural Networks LDRD
    2019–2021 · $480k
  • Precision Timing LDRD
    2017–2019 · $500k

Awards

  • CMS Young Researcher Prize, 2020
  • Fermilab Exceptional Performance Recognition Award, 2017
  • CMS Achievement Award, 2014