Dwight “Doc” Abrahams

SOFTWARE · HEALTHCARE OPERATIONS · WORKFORCE LEARNING

Software engineer.
Grounded in operations.

I’m Dwight “Doc” Abrahams. I bring experience in Army medical operations, healthcare workflows, and workforce training to practical software projects.

Applied machine learning, data processing, and computer vision—with attention to how systems behave and how people use them.

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SELECTED WORK

Three projects. Real tradeoffs.

Coursework case studies covering the implementation, reported findings, and limits of each experiment.

PIPELINE OVERVIEW
Prepare text
PositiveNeutralNegative
Curated response
Classical NLP with inspectable responses.

CSC525 · Applied NLP

Supportive Conversation Assistant

A Python assistant that classifies sentiment and selects a response from a curated catalog. Data preparation, model training, and response retrieval in one application.

  • Python
  • scikit-learn
  • TF-IDF
  • Logistic regression
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REPORTED RUNTIME · SECONDS
Sequential641.23
Threaded1,417.49
Two approaches. A slower threaded run.

CSC507 · Systems & performance

Large-File Processing & Concurrency

A comparison of sequential, threaded, and chunk-based Python processing. The threaded run was slower—an investigation into how a workload changes the value of concurrency.

  • Python
  • File processing
  • Concurrency
  • Benchmarking
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PIPELINE OVERVIEW
GrayscaleDetectBlur
3evaluation images
Detection errors affect the final redaction.

CSC515 · Computer vision

Face Detection & Redaction

An OpenCV pipeline for face and eye detection, regional blur, and saved comparison outputs. A small experiment that makes detection failures part of the analysis.

  • Python
  • OpenCV
  • Haar cascades
  • Image processing
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BACKGROUND

An operations perspective on engineering.

I’ve worked where clear processes, reliable information, and practical training matter.

My background spans Army healthcare and medical-record workflows, healthcare scheduling, workforce learning, and backend development. That experience shapes what I look for in software: understandable failures, useful documentation, and evidence that a change works for the people using it.

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HEALTHCARE & READINESS

U.S. Army

Medical care, patient documentation, operational readiness, and training in clinical and field settings.

WORKFLOWS & ADOPTION

QTC Management · Leidos

Healthcare training, scheduling-system rollout, user acceptance testing, defect documentation, and post-release training.

SOFTWARE & LEARNING SYSTEMS

Lyft · Caregiver Inc.

Backend refactoring and testing at Lyft; training workflows, Relias reporting, and compliance tracking at Caregiver.

CAPABILITIES

Skills with a context.

The technologies and working practices behind the projects and experience above.

Programming & data

Python, Java, JavaScript, SQL, data preparation, file processing, and reproducible scripts.

Applied machine learning

scikit-learn, TF-IDF, logistic regression, sentiment classification, and evaluation.

Computer vision

OpenCV, Haar cascades, image preprocessing, and regional blur.

Engineering & operations

Testing, performance measurement, workflow analysis, user acceptance testing, and technical documentation.

GET IN TOUCH

Let’s discuss the work.

Software engineering opportunities connected to healthcare operations, workforce learning, and practical data tools.

[email protected]

Get in touch to discuss a role or a project.