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Dr
.
Sarah
Kenwood
Assistant
Professor
of
Computational
Biology
Department
of
Integrative
Biology
University
of
California
,
Berkeley
Berkeley
,
CA
94720
skenwood
@
berkeley
.
edu
· +1 (510) 555-0184
kenwoodlab
.
berkeley
.
edu
EDUCATION
Ph
.
D
.
in
Computational
Biology
2017 – 2022
Stanford
University
,
Stanford
,
CA
Dissertation
:
Inferring
Gene
Regulatory
Networks
from
Single
-
Cell
Multi
-
Omics
Data
Advisor
:
Prof
.
Elena
Marchetti
B
.
S
.
in
Molecular
Biology
&
Computer
Science
2013 – 2017
Massachusetts
Institute
of
Technology
,
Cambridge
,
MA
Minors
:
Mathematics
·
Linguistics
Summa
cum
laude
·
GPA
: 3.96/4.0
ACADEMIC
APPOINTMENTS
Assistant
Professor
,
Department
of
Integrative
Biology
2024 –
present
University
of
California
,
Berkeley
,
CA
Affiliate
:
Center
for
Computational
Biology
,
Berkeley
Institute
for
Data
Science
Postdoctoral
Fellow
,
Laboratory
of
Dr
.
Rajiv
Nair
2022 – 2024
Broad
Institute
of
MIT
and
Harvard
,
Cambridge
,
MA
Research
:
Machine
learning
methods
for
spatial
transcriptomics
and
protein
–
DNA
interaction
modeling
RESEARCH
INTERESTS
Computational
modeling
of
gene
regulation
;
single
-
cell
and
spatial
multi
-
omics
;
machine
learning
for
biological
sequence
analysis
;
statistical
inference
of
regulatory
networks
;
chromatin
conformation
and
3
D
genome
organization
;
development
of
open
-
source
bioinformatics
software
.
PUBLICATIONS
*
denotes
equal
contribution
;
†
corresponding
author
1.
Kenwood
,
S
.
†
,
Liu
,
J
.,
Peterson
,
A
.,
and
Nair
,
R
. (2024).
SPARROW
:
scalable
probabilistic
inference
of
gene
regulatory
networks
from
scRNA
-
seq
and
scATAC
-
seq
.
Nature
Biotechnology
, 42(6), 922–935.
2.
Kenwood
,
S
.
*
and
Osei
,
K
.*,
and
Marchetti
,
E
.
†
(2023).
Chromatin
topology
modulates
transcription
factor
binding
dynamics
.
Molecular
Systems
Biology
, 19(4),
e
11230.
3.
Kenwood
,
S
.
†
,
Voss
,
M
.,
and
Marchetti
,
E
. (2022).
A
variational
autoencoder
framework
for
integrating
single
-
cell
multi
-
omics
data
.
Cell
Systems
, 13(2), 144–160.
4.
Nair
,
R
.
,
Kenwood
,
S
.
,
and
Bhatt
,
D
. (2024).
Deep
learning
predictions
of
transcription
factor
binding
specificity
from
intrinsic
disorder
.
Nature
Communications
, 15, 1182.
5.
Kenwood
,
S
.
†
and
Marchetti
,
E
. (2021).
Benchmarking
of
network
inference
methods
on
simulated
single
-
cell
perturbation
data
.
Bioinformatics
, 37(24), 4818–4827.
1 / 4
6.
Peterson
,
A
.
,
Kenwood
,
S
.
,
and
Liu
,
J
. (2025).
Spatial
transcriptomics
reveals
compartment
-
specific
immune
microenvironments
in
glioblastoma
.
Cell
, 188(1), 110–128.
7.
Kenwood
,
S
.
†
,
Patel
,
R
.,
and
Osei
,
K
. (2020).
scGraph
:
a
graph
convolutional
network
for
cell
-
type
classification
from
single
-
cell
gene
expression
.
PLOS
Computational
Biology
, 16(10),
e
1008374.
8.
Bhatt
,
D
.
,
Kenwood
,
S
.
,
and
Nair
,
R
. (2023).
Predicting
the
effects
of
non
-
coding
variants
on
transcription
factor
binding
using
transfer
learning
.
Genome
Research
, 33(9), 1543–1557.
AWARDS
&
HONORS
NSF
CAREER
Award
(2025)
$
1.2
M
over
5
years
for
"
Computational
frameworks
for
inferring
context
-
specific
gene
regulation
"
NIH
F
32
Postdoctoral
Fellowship
(2023–2024)
Individual
NRSA
for
postdoctoral
training
in
computational
biology
Harold
Weintraub
Graduate
Student
Award
(2022)
Fred
Hutchinson
Cancer
Center
—
outstanding
graduate
research
in
computational
biology
Stanford
Graduate
Fellowship
(2018–2022)
Four
-
year
fellowship
for
doctoral
research
ISMB
Best
Student
Paper
Award
(2021)
International
Conference
on
Intelligent
Systems
for
Molecular
Biology
Phi
Beta
Kappa
(2017)
MIT
chapter
GRANTS
&
FUNDING
NSF
CAREER
(
DBI
-2541821) —
$
1,200,000 — 2025–2030 —
PI
NIH
R
01
(
GM
145821) — "
Machine
learning
models
of
chromatin
architecture
and
gene
regulation
" —
$
2,450,000
— 2025–2030 —
Co
-
I
(
PI
:
Marchetti
)
Chan
Zuckerberg
Biohub
— "
Spatial
transcriptomics
of
the
human
liver
" —
$
480,000 — 2024–2027 —
PI
Google
Research
Scholar
Program
—
$
60,000 — 2025 —
PI
TEACHING
EXPERIENCE
Instructor
,
Computational
Genomics
(
IB
295)
Spring
2025
UC
Berkeley
·
Graduate
seminar
on
machine
learning
methods
for
genomics
.
Enrollment
: 22
students
.
Overall
rating
: 4.7/5.0.
Instructor
,
Introduction
to
Computational
Biology
(
IB
160)
Fall
2024
UC
Berkeley
·
Upper
-
division
undergraduate
course
.
Enrollment
: 48
students
.
Developed
new
module
on
single
-
cell
data
analysis
.
Rating
: 4.5/5.0.
Teaching
Assistant
,
Computational
Molecular
Biology
(
BIO
248)
2019, 2020
Stanford
University
·
Led
discussion
sections
and
designed
computational
assignments
for
80
graduate
students
.
ADVISING
&
MENTORING
Priya
Rajan
—
Ph
.
D
.
student
(2025–
present
),
UC
Berkeley
Integrative
Biology
–
Daniel
Okonkwo
—
Ph
.
D
.
student
(2024–
present
),
UC
Berkeley
Computational
Biology
–
Maya
Takeda
—
Undergraduate
researcher
(2024–
present
),
Berkeley
Bioengineering
.
Recipient
of
SURF
fellowship
(2025).
–
James
Park
—
Rotation
student
(2025),
UCSF
/
UC
Berkeley
joint
program
–
Liam
Foster
—
Postdoctoral
scholar
(2025–
present
),
co
-
mentored
with
Prof
.
Nair
–
2 / 4
PROFESSIONAL
SERVICE
Reviewer
—
Nature
Biotechnology
,
Nature
Communications
,
Cell
Systems
,
Genome
Research
,
PLOS
Computational
Biology
,
Bioinformatics
Program
Committee
—
RECOMB
(2024, 2025),
ISMB
(2023–2025)
Member
—
International
Society
for
Computational
Biology
(
ISCB
),
American
Association
for
the
Advancement
of
Science
(
AAAS
)
Organizer
—
Bay
Area
Computational
Biology
Symposium
(2025),
Berkeley
Single
-
Cell
Workshop
(2024)
SOFTWARE
&
DATA
RESOURCES
SELECTED
INVITED
TALKS
SKILLS
&
EXPERTISE
Python
R
Julia
PyTorch
TensorFlow
scverse
Bioconductor
Nextflow
AWS
/
GCP
Git
Docker
Statistical
modeling
Bayesian
inference
Deep
learning
Single
-
cell
analysis
Spatial
transcriptomics
CRISPR
screens
Scientific
writing
Mentoring
Grant
writing
REFERENCES
Prof
.
Elena
Marchetti
Department
of
Genetics
Stanford
University
emarchetti
@
stanford
.
edu
Dr
.
Rajiv
Nair
Broad
Institute
of
MIT
and
Harvard
rnair
@
broadinstitute
.
org
Prof
.
Anita
Desai
Department
of
Computer
Science
Prof
.
David
Bhatt
Department
of
Systems
Biology
SPARROW
—
R
/
Bioconductor
package
for
gene
regulatory
network
inference
.
bioconductor
.
org
/
packages
/
SPARROW
(770+
downloads
)
–
scVAE
—
Python
package
for
variational
autoencoder
-
based
integration
of
single
-
cell
multi
-
omics
data
.
github
.
com
/
kenwoodlab
/
scVAE
–
scGraph
—
Graph
neural
network
for
cell
-
type
classification
.
github
.
com
/
kenwoodlab
/
scGraph
–
TFnet
—
Deep
learning
model
for
transcription
factor
binding
prediction
from
DNA
sequence
and
chromatin
accessibility
.
github
.
com
/
kenwoodlab
/
TFnet
–
"
Integrating
single
-
cell
multi
-
omics
to
infer
context
-
specific
gene
regulation
" —
Keynote
,
RECOMB
/
ISCB
Computational
Biology
Workshop
(2025)
–
"
Machine
learning
for
gene
regulation
:
from
sequence
to
spatial
organization
" —
Department
of
Computer
Science
,
Princeton
University
(2025)
–
"
SPARROW
:
probabilistic
inference
of
gene
regulatory
networks
" —
Department
of
Computational
Medicine
,
UCLA
(2024)
–
"
Chromatin
topology
and
transcription
factor
binding
" —
Broad
Institute
Annual
Retreat
(2024)
–
"
Variational
inference
for
single
-
cell
multi
-
omics
integration
" —
ISMB
2023,
Lyon
,
France
(2023)
–
"
scGraph
:
graph
convolutional
networks
for
cell
-
type
classification
" —
Cold
Spring
Harbor
Laboratory
Single
-
Cell
Meeting
(2021)
–
3 / 4
Stanford
University
adesai
@
cs
.
stanford
.
edu
Harvard
Medical
School
dbhatt
@
hms
.
harvard
.
edu
4 / 4
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