Academic CV — page 1

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

Academic CV — page 2

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

Academic CV — page 3

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

Academic CV — page 4

Stanford

University

adesai

@

cs

.

stanford

.

edu

Harvard

Medical

School

dbhatt

@

hms

.

harvard

.

edu

4 / 4

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