Publications and Talks
Computational Phenotyping In CPAP Therapy: Using Interpretable Physiology‑Based Machine Learning Models To Predict Therapeutic CPAP Pressures
Using Novel EEG Phenotypes and Artificial Intelligence to Estimate OSA Severity
Accepted presentation at SLEEP 2019
Is AI the Future for Sleep Testing?
"A Cross-Validation Approach to Inter-scorer Reliability Assessment”
"Computational Phenotyping In Polysomnography: Using Interpretable Physiology-Based Machine Learning Models To Predict Health Outcomes"
"Sleep apnea: a review of diagnostic sensors, algorithms, and therapies"
"A modeling study on inspired CO2 rebreathing device for sleep apnea treatment by means of CFD analysis and experiment"
"Study on CO2 Rebreathing Device for Sleep Apnea Treatment by Means of CFD Analysis and Experiment"
"Sleep Scoring Automation Via Large Scale Machine Learning"
NSF Award: Young Professionals Contributing to Smart & Connected Health
SLEEP 2016 Annual Meeting
"NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning"
"Leveraging Supervised, Active, and Deep Machine Learning Methods for Sleep Scoring Automation and Personalization"