Scholar
Brian Hill
Google Scholar ID: UnyYursAAAAJ
Age Bold
Citations & Impact
Citations
1,295
H-index
19
i10-index
22
Publications
20
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published multiple papers, including 'CHIRon: A Generative Foundation Model for Structured Sequential Medical Data' (2023 NeurIPS DGM4H Workshop), 'Extend and Explain: Interpreting Very Long Language Models' (2022 ML4H Symposium), 'Methylation risk scores are associated with a collection of phenotypes within electronic health record systems' (2022 npj Genomic Medicine), 'Imputation of the continuous arterial line blood pressure waveform from non-invasive measurements using deep learning' (2021 Scientific Reports), 'An automated machine learning-based model predicts postoperative mortality using readily-extractable preoperative electronic health record data' (2019 British Journal of Anaesthesia).
Research Experience
- Currently working as a data scientist at Age Bold, an evidence-based, digital exercise platform for older adults that reduces falls and improves health. Previously, was an AI/ML scientist at Optum AI (UnitedHealth Group) where he led a team building ML models for trend forecasting. Interned at Microsoft Research with Daniel McDuff, interned at Intel for four years under the mentorship of Gans Srinivasa, and worked as the founding engineer at Omics Data Automation (now dātma) for three years.
Education
- PhD in Computer Science from UCLA, under the guidance of Professor Eran Halperin. Earned a degree in Electrical and Computer Engineering from Oregon State University.
Background
- A data scientist focused on using machine learning to improve healthcare. Research interests include the intersection of machine learning and medicine, leveraging electronic health records, physiological waveform signals, genomics, medical imaging data, and clinical text. Additionally, interested in large language models, causal inference, graphical models, imputation/missing data, and entrepreneurship.
Miscellany
- Resides in Los Angeles, CA.
Co-authors