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Basics

Name John Brevard Sigman
Label Principal Data Scientist

Work

  • 2019.01 - present
    Principal Data Scientist
    InfiniaML
    I lead and have led teams for large internal and client-facing projects such as:
    • Appeal Letter Generation, a Large Language Model (LLM) application.
    • Medical Record Retrieval Augmented Generation (RAG).
    • LLM entity extraction including LLM fine tuning and self-hosted inference of Open Source LLMs.
    • Healthcare payment remittance entity extraction.
    • Biometric database entity matching.
    • Legal Contract AI R&D Team.
    • Vision-based biotherapeutics particle detection and characterization.
    • Time-series grid use forecasting for large energy services firm.
    • Large scale medical insurance coordination of benefits.
    • M&A Insurance RFP Extractive Summarization.
    • Earnings statement recognition and extraction.
    • 3D volumetric object detection for threat recognition (Contributing Role).
    • Graph methods for communication recommendation at a tier-one investment bank (Contributing Role).
    • Vision-based Layout detection in documents (Contributing Role).
  • 2016.01 - 2016.12
    ORISE Fellow
    US Army Corps of Engineers - Signature Physics Branch
    Electromagnetics research in resonant tunnel detection.
  • 2012.01 - 2015.12
    Software Contractor
    Fannie Mae
    Wrote several enterprise iPad applications. Holds two patents for mobile appraisal verification.
  • 2010.01 - 2012.12
    Associate Engineering Program Manager
    Alarm.com
    Embedded software development, hardware design.

Volunteer

Education

  • 2017.01 - 2019.12

    Postdoc
    Duke University
    Deep Learning Research

  		•
    High School Diploma
    Thomas Jefferson High School for Science and Technology

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

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

Skills

Technical Skills
Python
Pytorch
Tensorflow
MATLAB
C
Objective-C
Gitlab CI
Docker
Linux
LaTeX
emacs lisp
pandas
sklearn
C++
bash
Scheme
MIPS assembly
VHDL
Visual Basic
Fortran
OpenMPI
PADS

Interests

Machine Learning
Large Language Models
Document feature extraction
Security applications in computer vision
Domain-adaptive neural networks
Semi-supervised learning
Electrical Engineering
Forward and inverse scattering problems
Electromagnetic signature classification
High-frequency electromagnetic induction sensing