James A. Coppock, PhD

Manager, AI/ML Applied Science

Infinia ML, the AI arm of Aspirion

• Promoted to manager. Lead the ContractIQ and Pricing & Scoring teams.

Senior AI/ML Applied Scientist

Infinia ML, the AI arm of Aspirion

• Lead the ContractIQ and Pricing & Scoring teams.
• Shaped ContractIQ from its earliest design to production: a contract-intelligence platform that turns payer contracts into structured, auditable reimbursement logic, so providers can see what they should be paid and catch underpayments.
• Pricing & Scoring applies ML to denied and underpaid claims to surface the ones most worth pursuing on appeal.
• Set technical direction across both, and build the team that brings AI rigor to revenue integrity.

Independent consultant

SolarUnsoiied

Principal Data Scientist, leading Data Science & AI

Bionic Health (now Thrive Wellness)

• Built a custom EHR and web and mobile apps for patients and clinicians, as an ML engineer across the platform.
• Designed the system that ingests multi-modal patient data (imaging, labs and blood biomarkers, continuous glucose, blood pressure, sleep and heart rate), runs inference on it, and produces personalized disease-risk profiles, including 30-year cardiovascular risk.
• Built an LLM-powered assistant that lets patients and clinicians ask questions of their health data and get custom analytics on the fly.
• Developed a FHIR-compliant, agent-based generative-AI framework for real-time clinical decision support.
• Built a retrieval-augmented assistant for patient onboarding and clinician-approved lifestyle guidance.

ML Research Scientist, Medical Imaging

Duke University

• Built segmentation and registration models that track intervertebral disc structure, composition and function across MRI time points and sequences.
• Developed and validated a diffeomorphic, unsupervised MR registration method for non-invasive, voxel-wise estimates of disc strain in vivo.
• Supported NIH-funded projects (R01AR075399, R01AR074800) with experimental design and statistical analysis.

Machine Learning Engineer, Wearable Biometrics

Valencell

• Developed deep-learning algorithms for real-time heart rate and blood pressure from wearable PPG sensors; contributed to a cuffless blood-pressure monitor that went to market.
• Built ETL pipelines for training, testing and validating time-series models.

Algorithm Engineer, Embedded Sensors

Wilson Sporting Goods

• Developed algorithms and data pipelines for the Wilson X line of connected footballs and basketballs.
• Ran field studies with NFL and NCAA teams on next-generation analytics for athletes and coaches.