Machine Learning Engineer with a focus on biomedical informatics. Extensive research and application experience in ML, NLP, and sentiment analysis for healthcare.
Research Assistant
Developed improved ML tools focused on histology image analysis
Intern
Implemented an online data-entry process for QC’s equipment qualification (EQ). Collaborated with stakeholders to revise SOP’s in the interest of FDA compliance. Analyzed inventory data to detect and meliorate non-compliant instruments. Participated in LEAN operations and collected KPI’s to track and reduce waste.
Machine Learning Engineer / App Developer
Used Python to build powerful machine learning models for clients. Deployed applications to the web using attractive front-end interfaces. Designed and implemented back-end SQL databases and REST APIs. Emphasis on natural language processing and recurrent neural networks.
Developed language-based RNN to analyze text. Designed, implemented, and deployed full-stack application running the model at scale. Database, authentication, task scheduling, unit testing.
Developed hardware and software for point of care 3D imaging of burn patients to more accurately measure TBSA. Validated error of 1.4% (vs. 20% typical).
- Presented poster @ UC Davis School of Engineering Design Showcase 2019
- Presented project @ UC Davis Biomedical Engineering Design Symposium, 2019
- Abstract Published @ American Burn Association Conference, 2020
- Abstract Published @ IEEE HI-POCT conference, 2019, awarded 'Rising Star in Healthcare Innovations'
Journal of Pathology Informatics
CNN-based educational tool for generating histology ddx lists from histo whole slide images
AMIA Annual Symposium 2021
ML tool to predict effect of deep brain stimulation in Parkinson's patients
AMIA Annual Symposium 2022
Used NLP & Network analysis to mine and graphically analyze clinical-note-derived risk factors as they relate to suicidal thoughts and behaviors
Vanderbilt University Medical Center
In progress, Dissertation Research - Using NLP, ML, RF, LSTM to improve suicide risk prediction w clinical notes & temporality
Vanderbilt University Medical Center
In progress, Dissertation Research - Using NLP, ML, LSTM, Sentiment Analysis to improve suicide risk prediction w patient portal messages
Journal of the American Medical Informatics Association
Using GPT-4 LLM to generate discharge summaries in English and Spanish, and at different reading levels, then analyzing generations for completeness and readability to assess the practicality of the tool.