American computer scientist
Barbara Elizabeth Engelhardt is an American
computer scientist and specialist in
bioinformatics . Working as a Professor at
Stanford University , her work has focused on
latent variable models , exploratory data analysis for
genomic data , and
QTLs .
[1] In 2021, she was awarded the
Overton Prize by the
International Society for Computational Biology .
Education
Engelhardt received a
Bachelor of Science in
Symbolic Systems and a
Master of Science in Computer Science from
Stanford University . She received a
PhD in 2008 from the
University of California, Berkeley supervised by
Michael I. Jordan .
[3]
Career and research
Engelhardt worked as a
postdoctoral researcher at the
University of Chicago in the Department of Human Genetics with
Matthew Stephens from 2008 to 2011.
[4] She joined
Duke University in 2011 as an assistant professor in the Biostatistics and Bioinformatics Department. She joined
Princeton University as an assistant professor in 2014 and received a promotion to Associate Professor with tenure in 2017.
[5] In August 2022, she moved to California, she now holds the position of Professor at
Stanford University and
Gladstone Institute of Data Science and Biotechnology .
[6]
[7]
After graduating from Stanford, Engelhardt worked at the
Jet Propulsion Laboratory in the Artificial Intelligence group for two years, working on planning and scheduling for autonomous spacecraft.
[8] As a graduate student at Berkeley, she developed statistical models for
protein function annotation and statistical frameworks for reasoning about
ontologies .
[9]
[10] During her postdoctoral research, she developed sparse factor analysis models for population structure
[11] and Bayesian models for association testing.
[12]
In her faculty position, the bulk of Engelhardt's research focused on developing latent variable models and exploratory data analysis for genomic data,
[13] and also on statistical models for association testing in expression
QTLs .
[14] As a member of the Genotype Tissue Expression (GTEx) Consortium, her group was responsible for the trans-eQTL discovery and analysis in the GTEx v6
[15] and v8 data.
[16]
Post tenure, Engelhardt's research in these latent variable models has expanded to include single cell sequencing, with a particular focus on spatial transcriptomics.
[17] She also has work on
Bayesian experimental design using contextual multi-armed bandits, and has adapted this work to the novel species problem in order to inform single cell data collection for atlas building.
[18] Her work has also expanded into machine learning for electronic healthcare records.
[19]
[20]
Engelhardt's work has been featured in
Quanta Magazine . In 2017, she gave a
TEDx talk entitled: 'Not What but Why: Machine Learning for Understanding Genomics.'
[21]
Honors and awards
Engelhardt's research has been funded by the
National Institutes of Health through two R01 grants and a number of other mechanisms. Engelhardt has been recognized by several awards including an
Alfred P. Sloan Fellowship in Computational Biology,
[22] a
National Science Foundation CAREER Award,
[23] two
Chan Zuckerberg Initiative grants for the
Human Cell Atlas ,
[24] and a
Fast Grant for her recent work on COVID-19.
[25] In 2021, she was awarded the
Overton Prize by the
International Society for Computational Biology .
[26]
Engelhardt's postdoctoral work was partly funded through an NIH NHGRI K99 grant,
[27] and her PhD was partly funded through an NSF Graduate Research Fellowship and the Google Anita Borg Scholarship in 2005.
[28] She received SMBE's Walter M. Fitch Prize in 2004.
[29]
Service and leadership
Engelhardt served on the Board of Directors (2014–2017) and the Senior Advisory Council (2017–present) for Women in Machine Learning.
[30] She is the Diversity & Inclusion Co-chair at the International Conference on Machine Learning (ICML, 2018–2022).
[31] In 2019, she was a member of the NIH Advisory Committee to the Director, Working Group on Artificial Intelligence
[32]
References
^
a
b
Barbara Engelhardt publications indexed by
Google Scholar
^
Barbara Engelhardt at the
Mathematics Genealogy Project
^
"Michael I. Jordan's Home Page" . people.eecs.berkeley.edu . Retrieved 2021-01-11 .
^
"Stephens Lab" . stephenslab.uchicago.edu . Retrieved 2021-01-11 .
^
"Eleven Women Faculty Members Who Have Been Assigned New Duties" . Women In Academia Report . 2018-03-08. Retrieved 2021-01-11 .
^
"Barbara Elizabeth Engelhardt's Profile | Stanford Profiles" . profiles.stanford.edu . Retrieved 2022-08-27 .
^
"barbara.engelhardt@gladstone.ucsf.edu" . gladstone.org . Retrieved 2022-08-27 .
^
"3cs | AIG" . sensorwebs.jpl.nasa.gov . Retrieved 2021-01-11 .
^ Engelhardt, Barbara E.; Jordan, Michael I.; Muratore, Kathryn E.; Brenner, Steven E. (2005-10-07).
"Protein Molecular Function Prediction by Bayesian Phylogenomics" . PLOS Computational Biology . 1 (5): e45.
Bibcode :
2005PLSCB...1...45E .
doi :
10.1371/journal.pcbi.0010045 .
ISSN
1553-7358 .
PMC
1246806 .
PMID
16217548 .
^ Engelhardt, Barbara E.; Jordan, Michael I.; Srouji, John R.; Brenner, Steven E. (2011-11-01).
"Genome-scale phylogenetic function annotation of large and diverse protein families" . Genome Research . 21 (11): 1969–1980.
doi :
10.1101/gr.104687.109 .
ISSN
1088-9051 .
PMC
3205580 .
PMID
21784873 .
^ Engelhardt, Barbara E.; Stephens, Matthew (2010-09-16).
"Analysis of Population Structure: A Unifying Framework and Novel Methods Based on Sparse Factor Analysis" . PLOS Genetics . 6 (9): e1001117.
doi :
10.1371/journal.pgen.1001117 .
ISSN
1553-7404 .
PMC
2940725 .
PMID
20862358 .
^ Mangravite, Lara M.; Engelhardt, Barbara E.; Medina, Marisa W.; Smith, Joshua D.; Brown, Christopher D.; Chasman, Daniel I.; Mecham, Brigham H.; Howie, Bryan; Shim, Heejung; Naidoo, Devesh; Feng, QiPing (October 2013).
"A statin-dependent QTL for GATM expression is associated with statin-induced myopathy" . Nature . 502 (7471): 377–380.
Bibcode :
2013Natur.502..377M .
doi :
10.1038/nature12508 .
ISSN
1476-4687 .
PMC
3933266 .
PMID
23995691 .
^ Gao, Chuan; McDowell, Ian C.; Zhao, Shiwen; Brown, Christopher D.; Engelhardt, Barbara E. (2016-07-28). Zhou, Xianghong Jasmine (ed.).
"Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering" . PLOS Computational Biology . 12 (7): e1004791.
Bibcode :
2016PLSCB..12E4791G .
doi :
10.1371/journal.pcbi.1004791 .
ISSN
1553-7358 .
PMC
4965098 .
PMID
27467526 .
^ Dumitrascu, Bianca; Darnell, Gregory; Ayroles, Julien; Engelhardt, Barbara E (2019-01-15). Hancock, John (ed.).
"Statistical tests for detecting variance effects in quantitative trait studies" . Bioinformatics . 35 (2): 200–210.
doi :
10.1093/bioinformatics/bty565 .
ISSN
1367-4803 .
PMC
6330007 .
PMID
29982387 .
^ Aguet, François; Brown, Andrew A.; Castel, Stephane E.; Davis, Joe R.; He, Yuan; Jo, Brian; Mohammadi, Pejman; Park, YoSon; Parsana, Princy; Segrè, Ayellet V.; Strober, Benjamin J. (October 2017).
"Genetic effects on gene expression across human tissues" . Nature . 550 (7675): 204–213.
Bibcode :
2017Natur.550..204A .
doi :
10.1038/nature24277 .
ISSN
1476-4687 .
PMC
5776756 .
PMID
29022597 .
^ The GTEx Consortium (2020-09-11).
"The GTEx Consortium atlas of genetic regulatory effects across human tissues" . Science . 369 (6509): 1318–1330.
Bibcode :
2020Sci...369.1318. .
doi :
10.1126/science.aaz1776 .
ISSN
0036-8075 .
PMC
7737656 .
PMID
32913098 .
^ Verma, Archit; Engelhardt, Barbara E. (2020-07-21).
"A robust nonlinear low-dimensional manifold for single cell RNA-seq data" . BMC Bioinformatics . 21 (1): 324.
doi :
10.1186/s12859-020-03625-z .
ISSN
1471-2105 .
PMC
7374962 .
PMID
32693778 .
^ Camerlenghi, Federico; Dumitrascu, Bianca; Ferrari, Federico; Engelhardt, Barbara E.; Favaro, Stefano (December 2020).
"Nonparametric Bayesian multiarmed bandits for single-cell experiment design" . Annals of Applied Statistics . 14 (4): 2003–2019.
arXiv :
1910.05355 .
doi :
10.1214/20-AOAS1370 .
ISSN
1932-6157 .
S2CID
204509422 .
^ Cheng, Li-Fang; Dumitrascu, Bianca; Darnell, Gregory; Chivers, Corey; Draugelis, Michael; Li, Kai; Engelhardt, Barbara E. (2020-07-08).
"Sparse multi-output Gaussian processes for online medical time series prediction" . BMC Medical Informatics and Decision Making . 20 (1): 152.
doi :
10.1186/s12911-020-1069-4 .
ISSN
1472-6947 .
PMC
7341595 .
PMID
32641134 .
^ Cheng, Li-Fang; Prasad, Niranjani; Engelhardt, Barbara E. (2019).
"An Optimal Policy for Patient Laboratory Tests in Intensive Care Units" . Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing . 24 : 320–331.
arXiv :
1808.04679 .
ISSN
2335-6936 .
PMC
6417830 .
PMID
30864333 .
^
"A Statistical Search for Genomic Truths" . 27 February 2018.
^
"Prof. Barbara Engelhardt recipient of an Alfred P. Sloan Foundation Research Fellowship | Computer Science Department at Princeton University" . www.cs.princeton.edu . Retrieved 2021-01-11 .
^
"Barbara Engelhardt wins CAREER award for research with high-dimensional genomic data | Computer Science Department at Princeton University" . www.cs.princeton.edu . Retrieved 2021-01-11 .
^
"Grants" . Chan Zuckerberg Initiative . Retrieved 2021-01-11 .
^
"Fast Grants" . fastgrants.org . Retrieved 2021-01-11 .
^
"Overton Prize" . www.iscb.org .
^
"NHGRI supports seven young investigators on research career paths" . Genome.gov . Retrieved 2021-01-11 .
^
"2005 Google Anita Borg Memorial Scholarship Winners Announced – News announcements – News from Google – Google" . googlepress.blogspot.com . Retrieved 2021-01-11 .
^ The Society for Molecular Biology & Evolution.
"The Walter M. Fitch Award" . www.smbe.org . Archived from
the original on 2020-08-12. Retrieved 2021-01-11 .
^
"Senior Advisory Council" . Archived from
the original on 2021-01-13. Retrieved 2021-01-11 .
^
"2021 Conference" . icml.cc . Retrieved 2021-01-11 .
^
"ACD Working Group on Artificial Intelligence" . NIH Advisory Committee to the Director . Retrieved 2021-01-11 .