Contributing Profession Experience

2021 – 2025, Trice Imaging, San Diego, California (Remote)

• Company Mission: Medical ultrasound imaging support

• Position: Director, Machine Learning

AI Contributions:

• Developed 3-year strategic plan for technology development

• Developed Conversational mobile app for discussing ultrasound images with patients (Claude API)

• Developed user facing agentic support for contract review and analytics based on Hubspot and other repositories

• Developed machine vision system for interpreting maternal fetal medicine ultrasound images

• Designed new productivity reporting to incorporating analytics from AI concerning sonography operations

• Developed automation for MLOps, including training data curation and version control

• Developed product demonstrators supporting new initiatives, including GPT co-pilot

• Recruited and managed sonographer team to support science-based training data annotations

2018 – Present, Stratos Perception, LLC, Houston, Texas

• Company Mission: Develop artificial intelligence solutions and software that increase productivity and reliability in aerospace systems

• Position: Principal Investigator, Deep Learning, Software Developer

AI Contributions:

• NASA SBIR Phase 1 Contract. ($110K award) Developed a machine vision process incorporating convolutional neural networks to perform multiphase flow management. (C/C++, Python, CUDA); Completed on time; Patent US 11,341,657 (2022)

  • Proposed, designed, and developed solution

  • Features YOLOv3, OpenCV, C/C++, Python, Supervised Learning

  • Performs real-time thermo-fluid dynamic analyses on two-phase channel flow based on machine-vision observations of the flow field at 1000 fps​

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• Developed novel inferential sensor for estimating dynamical states and any number of time varying parameters, thereby providing first-principals observability to unanticipated failure modes; and also providing many advanced autonomous capabilities to machines. Inspired by the human cerebellum, Foundational AI programming (Pytorch); Solves under-constrained estimation problems (new paradigm for adaptive control); Patent allowed (2025), pursuing continuation.

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2017-2019, Sunnova Energy Corporation, Houston, TX

• Company Mission: To install and finance rooftop solar systems and battery storage systems for residential energy customers.

• Position: Full Stack / Mobile Developer

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AI Contributions:

• Automated of the quality assurance inspection work for solar system installs, which were accomplished by engineers directly reviewing photographs of installed system components. Developed a deep learning system featuring a convolutional neural network utilizing object detection to automate part of the review of the photos to identify equipment installs and to extract serial numbers to a database.  Features YOLO, OpenCV, C/C++, Python, Supervised Learning, AWS (S3 and SQS), PostgreSQL

• Modeled National Solar Radiation Data using LSTM network to supplement the published data, which included from 8%-30% error in the NOAA solar radiation data attributed to a local weather station. The objective was to effectively generalize the weather station data over the local regions of the US and more consistently predict the solar radiation, providing a shadow system to support better financial predictions. Python, TensorFlow, Keras, Jupyter, Supervised Learning

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2000 – 2004   Los Alamos National Laboratory, Los Alamos, NM,  Technical Staff Member, Nuclear Systems Design and Risk Analysis, Decision Applications Division​

AI Contributions:

• Proposed a method utilizing neural networks to interpret human intent from the acceleration field of people wearing accelerometers  

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