Brett K. Beaulieu-Jones, PhD

Brett Beaulieu-Jones, PhD

Former Instructor in Biomedical Informatics
Former Research Fellow in Neurology, Brigham and Women's Hospital
Biomedical Informatics Research Training Fellow, 2017-2019

Brett Beaulieu-Jones received his PhD from the Perelman School of Medicine at the University of Pennsylvania under the supervision of Dr. Jason Moore and Dr. Casey Greene. Beaulieu-Jones’ doctoral research focused on using machine learning-based methods to more precisely define phenotypes from large-scale biomedical data repositories, e.g. those contained in clinical records. At DBMI he is expanding this concentration to include large-scale data integration (genomic, therapeutic, imaging) to both better understand disease etiology as well as provide precise therapeutic recommendations. Initially, he is working to develop targeted models of drug selection for patients with refractory epilepsy and to further develop machine learning methods that model the way patients progress over time using longitudinal data.  

Reproducibility of computational workflows is automated using continuous analysis.
Authors: Beaulieu-Jones BK, Greene CS.
Nat Biotechnol
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MISSING DATA IMPUTATION IN THE ELECTRONIC HEALTH RECORD USING DEEPLY LEARNED AUTOENCODERS.
Authors: Beaulieu-Jones BK, Moore JH.
Pac Symp Biocomput
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Semi-supervised learning of the electronic health record for phenotype stratification.
Authors: Beaulieu-Jones BK, Greene CS.
J Biomed Inform
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