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@rxp-lang @QuantaNews

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RobertxPearce/README.md

About Me

Computer science student and machine learning researcher focused on scientific ML, uncertainty quantification, and high-performance computing. My work connects large-scale simulation data, reproducible ML pipelines, and uncertainty-aware modeling for scientific applications.

Platform Link
Portfolio robertxpearce.com
LinkedIn robert-d-pearce
ORCID 0009-0004-5143-8747
PyPI robertxpearce

Featured Work

  • reionemu — Python package for emulating the kSZ angular power spectrum from reionization simulations.
  • uncertainty-aware-histopathology-survival-analysis — Benchmark of MC-Dropout, Deep Ensembles, and SNGP for uncertainty quantification in an ABMIL + Cox survival model on TCGA glioma whole-slide images.
  • Quorum iOS Accessibility — Senior design work focused on improving accessibility support for blind and visually impaired iOS developers.

Interests

  • Machine Learning
  • Uncertainty Quantification
  • Interpretability
  • Scientific Computing
  • Research Software Engineering
  • GPU/Supercomputing

Pinned Loading

  1. reionization-emulator reionization-emulator Public

    Python package for emulating the kSZ angular power spectrum from reionization simulations, with uncertainty quantification.

    Jupyter Notebook 2

  2. uncertainty-aware-histopathology-survival-analysis uncertainty-aware-histopathology-survival-analysis Public

    Comparing MC-Dropout, Deep Ensembles, and SNGP as uncertainty estimators for survival prediction from whole-slide pathology images.

    Jupyter Notebook

  3. reionemu-platform reionemu-platform Public

    Production ML inference platform for reionemu with APIs, asynchronous jobs, and cloud deployment.

  4. zreion-gpu-port zreion-gpu-port Public

    CUDA/GPU port of the zreion kSZ 2LPT reionization simulations for accelerating reionization research.