ML for Health

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

Recently, 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.

Education

  • Princeton University

    Ph.D. Quantitative and Computational Biology (2014-2019)

  • UCLA

    B.S. Computer Science, minor Bioinformatics (2008-2013)

  • Curriculum vitae
  • Research

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

    Generalizing Variational Autoencoders with Hierarchical Empirical Bayes

    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

    Contact

    • Email

      greg b darnell @ gmail . com