Greg Darnell

Research Scientist

I am a Senior Research Scientist in the Health AI group of Apple's AI/ML organization.

Previously, I was a postdoctoral fellow at the Institute for Computational and Experimental Research in Mathematics (ICERM) at Brown University, and participated in the semester program in model and dimension reduction in uncertain and dynamic systems. I worked closely with Sohini Ramachandran, Lorin Crawford, Sigal Gottlieb, and Yanlai Chen.

I completed my PhD in machine learning and statistical genetics in the Quantitative and Computational Biology Ph.D program at Princeton University, where I was advised by Barbara Engelhardt (Princeton) and co-advised by Sayan Mukherjee (Duke). I have worked in research labs at Microsoft Research New England (with Jennifer Listgarten and Nicolo Fusi), Rockefeller University (with Robert Darnell and Chaolin Zhang), and Harvard School of Public Health (with Alkes Price). At UCLA, my research mentor was Eleazar Eskin.

Research

Modeling personalized heart rate response to exercise and environmental factors with wearables data

Latent Temporal Flows for Multivariate Analysis of Wearables Data

PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression

Multi-scale Inference of Genetic Trait Architecture using Biologically Annotated Neural Networks

Generalizing Variational Autoencoders with Hierarchical Empirical Bayes

Pathway Analysis within Multiple Human Ancestries Reveals Novel Signals for Epistasis in Complex Traits

Sparse multi-output Gaussian processes for online medical time series prediction

Joint analysis of gene expression levels and histological images identifies genes associated with tissue morphology

Adaptive Randomized Dimension Reduction on Massive Data

Statistical tests for detecting variance effects in quantitative trait studies

Incorporating prior information into association studies

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