Uzziel Perez
  • Bio
  • Skills
  • Papers
  • Talks
  • News
  • CV
  • Experience
  • Projects
  • Teaching
  • Science Communication
  • Projects
    • UzzieNet / ecal-reco-gnn
    • rag-ai-scientist
    • Apprie
    • Manifesto
    • The Evolution of Trust (Filipino Translation)
  • Projects
  • Experience
  • Blog
    • The Unitarity Triangle, 2006–2023
    • Three talks at CHEP 2026 in Bangkok
  • Publications
    • Search for new physics in high-mass diphoton events from proton-proton collisions at √s = 13 TeV
    • Development of the CMS detector for the CERN LHC Run 3
    • Search for physics beyond the standard model in high-mass diphoton events from proton-proton collisions at √s = 13 TeV
    • Path Integral Solutions to the Distributions of Statistical Mechanics
    • Lorentz Dispersion Law from classical Hydrogen electron orbits in AC electric field via geometric algebra
  • Recent & Upcoming Talks
    • Execution-Grounded Agents: Enforcing Physical Constraints in AI Code Generation via Oracle Search
    • Future-Ready Restoration: A Case Study on AI RAG-Enhanced Agentic Revival of a Run-2 2016 Λb → Λγ Analysis
    • Optimizing GNNs for the Wild: PyTorch-to-ONNX Acceleration of GarNet on CPUs and GPUs
    • When Less is More: Towards Lightweight and Distilled Graph Neural Networks for Efficient Particle Reconstruction in LHCb's Next-Generation Calorimeter
    • When Less is More: Towards Lightweight and Distilled Graph Neural Networks for Efficient Particle Reconstruction
    • When Less is More: Lightweight and Distilled GNNs for Efficient Particle Reconstruction
    • Understanding proton complexity and finding cracks in the Standard Model
    • HB TDC LUTs for Long-Lived Particles and Configuration Latency Reduction
  • Teaching
    • Research Data Management and FAIR data
    • Electromagnetism and Physics for Physics Teachers
    • Science Communication
      • The reconstruction menu, and the gates that prune it
      • The space of the Standard Model, and the space still open
      • Auroras: The Science Behind Nature's Light Show
      • Black Hole Visualization

Apprie

Jun 23, 2024 · 1 min read
Go to Project Site

Apprie is a patient-centered open-source application. This is currently just a passion project but would be happy to discuss with potential collaborators/investors!

Last updated on Jun 23, 2025
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Uzziel Perez
Authors
Uzziel Perez
Postdoctoral Researcher · AI for High Energy Physics
← rag-ai-scientist Jan 1, 2026
Manifesto Jun 23, 2024 →

© 2026 Uzziel Perez. This work is licensed under CC BY NC ND 4.0

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