Curriculum Vitae

Basics

Name John Brevard Sigman
Label Principal AI/ML Applied Scientist

Work

  • 2019 - Now
    Principal AI/ML Applied Scientist
    InfiniaML
    Manage 4 direct reports and lead extended cross-functional teams of 12–15 scientists and engineers delivering production AI systems for internal and client-facing projects.
    • Led Appeal Letter Generation, a production LLM workflow for automated insurance-denial appeals submitting >$500M/month (>$6B annualized) in claims; progressed from tech lead (discovery) to product owner to team lead.
    • Built LLM entity extraction and medical-record retrieval-augmented generation (RAG), including fine-tuning and self-hosting of open-source LLMs.
    • Delivered entity extraction for healthcare payment remittances and large-scale coordination-of-benefits automation for medical insurance.
    • Led the legal contract AI R&D team; built M&A insurance RFP extractive summarization and earnings statement recognition and extraction.
    • Developed biometric database entity matching, vision-based biotherapeutics particle detection and characterization, and time-series grid-usage forecasting for a large energy-services firm.
    • Contributed to 3D volumetric object detection for threat recognition, graph methods for communication recommendation at a tier-one investment bank, and vision-based document layout detection.
  • 2016 - 2016
    ORISE Fellow
    US Army Corps of Engineers - Signature Physics Branch
    Researched detection of underground tunnels using low-frequency electromagnetic waves.
  • 2012 - 2015
    Software Contractor
    Fannie Mae
    Developed enterprise iPad applications; co-inventor on two published patent applications for mobile appraisal.

Volunteer

Education

  • 2017 - 2019

    Durham, NC

    Postdoc
    Duke University
    Deep Learning Research
  • 2012 - 2017

    Hanover, NH

    Ph.D.
    Dartmouth College, Thayer School of Engineering
    Electrical Engineering
    • Computational electromagnetics
    • Remote sensing
    • Machine learning
  • 2006 - 2010

    Charlottesville, VA

    B.S.
    University of Virginia, School of Engineering and Applied Science
    Electrical Engineering
    • Signal processing concentration

Skills

Technical Skills
Python
PyTorch
TensorFlow
pandas
scikit-learn
C
C++
MATLAB
Bash
Objective-C
Emacs Lisp
Docker
Linux
GitLab CI
LaTeX
OpenMPI
Hugging Face
Haystack
LangChain
AWS Bedrock
Ollama
LanceDB

Publications