David Grayson Email & Phone Number

United States

United States

Vancouver, Washington, US

Sheridan, WY, US

Palo Alto, CA, US

Palo Alto, CA, US

- Computer vision with high-content image and video- End-to-end MLOps- Active learning pipelines- Domain adaptation- Zero-shot object detection- Synthetic data generation

Palo Alto, CA, US

Designed and executed ML roadmaps for two of California’s largest utility companies, supervising up to 4 ML scientists/engineers concurrently.Built an ML app forecasting daily failure probabilities on >200K devices with self-supervised learning.Trained and deployed patent-pending computer vision pipelines used on >1M high-content images.

San Francisco, California, US

- Analytics, computer vision, and machine learning for organoid research and neuropsychiatric drug discovery.- Team lead for video acquisition and analysis pipeline, used to assay genetic effects and drug perturbation on neuronal network activity.- Technical lead for neurodegenerative disease program: responsible for scientific roadmaps, experimental.

Mountain View, California, US

- Tech lead for QuickBooks Online's self-help recommendation algorithm.- Trained, deployed, and AB tested deep learning models that reduced customer call rates and boosted customer engagement.- Wrote distributed computing algorithms (in Spark) to process billions of customer clicks.- Trained interns and led exploratory machine learning / NLP research for.

San Francisco, CA, US

Portland, Oregon, US

- Led 2 research projects on a data team comprised of graduate students, postdoctoral scientists, and research staff, resulting in 3 publications.- Predicted functional brain imaging (MRI) data, achieving >60% variance explained, using multilinear regression models incorporating anatomical and gene expression data.- Trained students and research staff in.

- Built flexible and automated data pipelines in Python to process several hundreds of MRI scans from different institutions and extract thousands of useable features for data analysis and predictive modeling.- Identified axes of clinical variability from high-dimensional datasets using graph theory and machine learning.

Davis, California, US

- Led multiple brain imaging projects and published 11 peer-reviewed studies (>500 citations, 4 first-author) covering advanced statistical and computational techniques for brain imaging (MRI) data.- Independently developed data analysis strategies selected for nationally competitive funding awards.- Produced results that were instrumental in securing.

Doctor Of Philosophy - Phd, Neuroscience (Computational Neuroimaging)

Bachelor Of Arts (B.A.), Independent Major: Computational Neuroscience