Andrew Beam

Andrew Beam, PhD

Assistant Professor of Epidemiology, Harvard T.H. Chan School of Public Health
Assistant Professor of Biomedical Informatics, Harvard Medical School (Secondary)

Andrew Beam is an assistant professor in the Department of Epidemiology at the Harvard T.H. Chan School of Public Health, with secondary appointments in the Department of Biomedical Informatics at Harvard Medical School and the Department of Newborn Medicine at Brigham and Women’s Hospital. His research develops and applies machine-learning methods to extract meaningful insights from clinical and biological datasets, and he is the recipient of a Pioneer Award from the Robert Wood Johnson Foundation for his work on medical artificial intelligence.

Previously he was a Senior Fellow at Flagship Pioneering and the founding head of machine learning at Generate Biosciences, Inc., a Flagship-backed venture that seeks to use machine learning to improve our ability to engineer proteins.

He earned his PhD in 2014 from N.C. State University for work on Bayesian neural networks, and he holds degrees in computer science (BS), computer engineering (BS), electrical engineering (BS), and statistics (MS), also from N.C. State. He completed a postdoctoral fellowship in Biomedical Informatics at Harvard Medical School and then served as a junior faculty member.

Beam’s group is principally concerned with improving, stream-lining, and automating decision-making in healthcare through the use of quantitative, data-driven methods. He does this through rigorous methodological research coupled with deep partnerships with physicians and other members of the healthcare workforce. As part of this vision, he works to see these ideas translated into decision-making tools that doctors can use to better care for their patients.

Long term mortality in critically ill burn survivors.
Authors: Nitzschke S, Offodile AC, Cauley RP, Frankel JE, Beam A, Elias KM, Gibbons FK, Salim A, Christopher KB.
Burns
View full abstract on Pubmed
Predictive Modeling of Physician-Patient Dynamics That Influence Sleep Medication Prescriptions and Clinical Decision-Making.
Authors: Beam AL, Kartoun U, Pai JK, Chatterjee AK, Fitzgerald TP, Shaw SY, Kohane IS.
Sci Rep
View full abstract on Pubmed
Translating Artificial Intelligence Into Clinical Care.
Authors: Beam AL, Kohane IS.
JAMA
View full abstract on Pubmed
An investigation of gene-gene interactions in dose-response studies with Bayesian nonparametrics.
Authors: Beam AL, Motsinger-Reif AA, Doyle J.
BioData Min
View full abstract on Pubmed
Bayesian neural networks for detecting epistasis in genetic association studies.
Authors: Beam AL, Motsinger-Reif A, Doyle J.
BMC Bioinformatics
View full abstract on Pubmed
Beyond IC50s: Towards Robust Statistical Methods for in vitro Association Studies.
Authors: Beam A, Motsinger-Reif A.
J Pharmacogenomics Pharmacoproteomics
View full abstract on Pubmed
Salmonella awareness and related management practices in U.S. urban backyard chicken flocks.
Authors: Beam A, Garber L, Sakugawa J, Kopral C.
Prev Vet Med
View full abstract on Pubmed
Zebrafish developmental screening of the ToxCast™ Phase I chemical library.
Authors: Padilla S, Corum D, Padnos B, Hunter DL, Beam A, Houck KA, Sipes N, Kleinstreuer N, Knudsen T, Dix DJ, Reif DM.
Reprod Toxicol
View full abstract on Pubmed
Ex-Vivo Modeling for Heritability Assessment and Genetic Mapping in Pharmacogenomics.
Authors: Motsinger-Reif A, Brown C, Havener T, Hardison N, Peters E, Beam A, Everrit L, McLeod H.
Proc Am Stat Assoc
View full abstract on Pubmed
Optimization of nonlinear dose- and concentration-response models utilizing evolutionary computation.
Authors: Beam AL, Motsinger-Reif AA.
Dose Response
View full abstract on Pubmed