Expertise

AI & machine learning expertise

CBDr. Caleb Bradberry · PhD
PhDInfo Systems
What I know well

Where my experience actually runs deep

“AI consultant” can mean almost anything these days, so here's the specific ground I cover. It comes from a PhD in Information Systems plus years of building and shipping this work, not from a weekend course.

Because I teach and publish in the field, what I bring to a project tends to be current. I'm not handing you a method I read about a year ago and never used.

If your problem isn't on this page, it's still worth asking. Half of consulting is recognizing a familiar problem wearing different clothes.

Core areas

The work I do most

AI & Machine Learning

The everyday work of designing and training models that do a real job.

  • Transformer architectures
  • Generative pre-trained models
  • Diffusion & auto-regressive models
  • Variational auto-encoders
  • Predictive modeling

Healthcare Informatics

Healthcare data systems and predictive modeling.

  • Healthcare analytics systems
  • Synthetic medical data
  • HIPAA-compliant processing
  • Medical coding & billing
  • Patient-outcome prediction

Workflow Automation

Getting software to do the repetitive parts so people don't have to.

  • Workflow analysis
  • Process optimization
  • Document-processing automation
  • Administrative automation
  • Legacy-system integration

Research AI & Grant Support

AI/ML methods for research projects and grant proposals.

  • Grant-proposal AI methodology
  • Custom research models
  • Technical writing support
  • Proof-of-concept development
  • Research-team implementation

Creator Consulting

Reading audience data so creators can grow on purpose.

  • Engagement-analysis models
  • Audience-insight analytics
  • Content optimization
  • Growth-prediction models
  • Competitor analysis

Synthetic Data Generation

Datasets that preserve privacy and statistical properties.

  • HIPAA-compliant medical data
  • Financial-transaction simulation
  • Customer-behavior modeling
  • Research data augmentation
  • Realistic test data

Data Security & Privacy

Handling sensitive data and analyzing breach cost.

  • Sensitive-data identification
  • Privacy-preserving AI
  • Data-governance frameworks
  • Breach-cost analysis
  • Compliance assessment

Custom Model Development

Specialized models fine-tuned for your domain.

  • Domain-specific training
  • Custom architecture design
  • Transfer-learning optimization
  • Small-dataset efficiency
  • Deployment & integration

Make-vs-Buy Consulting

Build custom AI or use existing platforms, decided with data.

  • Technical-requirements assessment
  • Total-cost-of-ownership analysis
  • Team-capability evaluation
  • Strategic-value assessment
  • Implementation roadmap
Toolkit

What I build with

For the technically inclined, the stack I reach for, chosen per project.

AI & ML Frameworks

  • PyTorch & TensorFlow
  • scikit-learn & XGBoost
  • Keras & fast.ai
  • NVIDIA CUDA
  • Hugging Face Transformers
  • Diffusion models & GANs

Programming Languages

  • Python (advanced)
  • R for statistical analysis
  • SQL for data management
  • C# for application development
  • JavaScript for the web
  • Rust for performance-critical code

Cloud & Infrastructure

  • AWS for ML deployment
  • Azure AI services
  • Docker & Kubernetes
  • MLOps & CI/CD pipelines
  • Data-warehousing solutions
  • Serverless AI infrastructure
Applied

A closer look at four of them

Custom Fine-Tuned Models

Specialized models fine-tuned for your domain and objectives, beyond generic pre-trained options.

Key benefits

  • Domain understanding of your terminology and nuances
  • Enhanced accuracy for your use cases
  • Reduced data needs via efficient learning
  • Competitive advantage from proprietary models

Deployed across healthcare, research, e-commerce, and content creation, consistently outperforming generic alternatives.

Synthetic Data Generation

Realistic artificial datasets that maintain statistical properties while ensuring privacy and compliance.

Applications

  • Healthcare: HIPAA-compliant medical data
  • Finance: transaction data for fraud & risk modeling
  • Research: augmentation for limited datasets
  • Testing: data that mirrors production

Creator Analytics & Optimization

Optimize your social presence, sharpen content strategy, and grow your audience with intent.

Capabilities

  • Engagement analysis of what resonates
  • Audience insights on demographics & behavior
  • Content strategy for content, timing, and platform
  • Competitive analysis of your niche

Creator clients have achieved meaningful, measurable follower growth while maintaining or increasing engagement.

Research Grant AI Consulting

Strengthen proposals with AI methodology, technical writing, and custom model development for NSF, NIH, and other agencies.

Services

  • Methodology development
  • Technical narrative for reviewers
  • Proof-of-concept models
  • Budget planning for AI components

Academic clients have strengthened competitive proposals with custom AI methodologies that reviewers specifically highlighted.

Research

Selected publications

2024

The Machine Learning Transformer as a Universal Product Catalog Indexer

Proceedings of the Southeast INFORMS, 2024

Best Paper in Track

Demonstrates how transformer architectures enable efficient indexing and retrieval of product information across diverse catalog systems.

2023

Synthetic Data Generation for Healthcare: A Privacy-Preserving Approach

Journal of Medical Informatics, 2023

A novel approach to generating synthetic healthcare data that maintains statistical validity while preserving patient privacy and HIPAA compliance.

2022

A Design Science Approach to Machine Learning Applications of Physical Fitness

Proceedings of the Southeast INFORMS, 2022

Explores the methodological foundations of the Gain Genie application via a design-science framework for fitness recommendation systems.

2022

Data Mining Cosmetologists' Social Media Posts to Discover Latent Occupational Health Risk Factors

Proceedings of the Southeast INFORMS, 2022

with Linkous, N. & Wang, W.

Uses NLP to identify potential occupational health risks from social-media content in the beauty industry.

2021

Implementation of Clinical Practice Guidelines for Low Back Pain: A Case-Control Cohort Study of Knowledge Translation in a Multi-Site Healthcare Organization

Journal of Evaluation in Clinical Practice

with Kolb, W. & Bade, M.

Examines how medical knowledge and guidelines can be effectively implemented across healthcare organizations, informing aspects of the Lifesynai project.

In progress

What I'm researching right now

Synthetic Medical Data

Generating realistic synthetic medical data that conforms to statistical parameters, enabling algorithm development while maintaining HIPAA compliance.

Current focus: pairing generated medical images with expert-level tabular chart data for more accurate diagnostic algorithms.

AI for Social Content

Analyzing and optimizing social-media content performance, focusing on multi-modal analysis and engagement prediction.

Exploring how transformer models relate visual elements, captions, and engagement to shape effective content strategy.

AI for Higher Ed Administration

Using transformers to automate administrative tasks, particularly accreditation reporting and advising systems.

Researching how RAG and low-rank adaptation apply to higher-education workflows for efficiency and better student outcomes.

Transformers for Workflow Automation

How transformer-based ML can automate routine tasks in small and medium enterprises.

Developing techniques to extract workflows from unstructured business processes and generate tailored automation for the New River Valley.

Credentials

The paperwork, for what it's worth

Education

2016

Ph.D., Information Systems

The University of North Carolina at Greensboro

Dissertation: A Design Science Framework for Research in Healthcare Analytics

2010

M.B.A., Management

Marshall University

Thesis: An Econometric Analysis of a Resource-Dependent State Economy

2007

B.B.A., Information Systems

Marshall University

Supporting area: Computer Science

Certifications & teaching

  • Advanced ML Model Engineering: custom model development and fine-tuning
  • Microsoft Certified Professional: server environments
  • Microsoft Developer Affiliate: C#
  • Advanced AWS for ML: deployment and testing of ML solutions

Teaching

University-level courses developed and taught include Data Science, AI Decision Support Systems, Healthcare Information Systems, and Programming with Python.

Get in touch

Think one of these fits your problem?

Tell me what you're up against. I'll give you a straight read on whether it's something I can help with.