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Dr
.
Elena
Voss
Professor
of
Computational
Neuroscience
elena
.
voss
@
university
.
edu
+1 (555) 234-5678
cognitionlab
.
org
University
of
Stanford
,
CA
ACADEMIC
APPOINTMENTS
2020–
Present
Professor
,
Department
of
Psychology
&
Cognitive
Science
,
Stanford
University
Computational
Neuroscience
Program
·
Faculty
of
AI
&
Decision
Making
2016–2020
Associate
Professor
,
Department
of
Brain
&
Cognitive
Sciences
,
MIT
Affiliate
,
McGovern
Institute
for
Brain
Research
2012–2016
Assistant
Professor
,
Department
of
Cognitive
Science
,
University
of
California
,
San
Diego
EDUCATION
2012
Ph
.
D
.
in
Computational
Neuroscience
,
Princeton
University
Dissertation
: "
Hierarchical
inference
in
visual
cortex
:
a
recurrent
neural
network
approach
"
2006
B
.
Sc
.
in
Cognitive
Science
&
Mathematics
,
University
of
Tübingen
,
Germany
Summa
cum
laude
·
Thesis
: "
Bayesian
models
of
perceptual
decision
-
making
"
RESEARCH
INTERESTS
Neural
population
coding
·
probabilistic
computation
in
cortical
circuits
·
deep
reinforcement
learning
models
of
decision
-
making
·
representational
geometry
in
high
-
dimensional
neural
spaces
·
meta
-
learning
and
cognitive
flexibility
·
bridging
machine
learning
and
systems
neuroscience
.
SELECTED
PUBLICATIONS
2025
—
Representational
drift
in
recurrent
neural
networks
trained
on
perceptual
inference
tasks
.
Voss
,
E
.
R
., &
Lee
,
S
.
H
.
Nature
Neuroscience
, 28(3), 412–424.
2024
—
Meta
-
learning
of
Bayesian
priors
enables
rapid
adaptation
in
human
and
artificial
agents
.
Kim
,
J
.
T
.,
Voss
,
E
.
R
., &
Tenenbaum
,
J
.
B
.
Proceedings
of
the
National
Academy
of
Sciences
, 121(17),
e
2319872121.
2023
—
A
unifying
framework
for
neural
population
codes
:
from
tuning
curves
to
probabilistic
representations
.
Voss
,
E
.
R
., &
Pouget
,
A
.
Annual
Review
of
Neuroscience
, 46, 215–238.
2022
—
Efficient
coding
of
uncertainty
in
the
primate
visual
cortex
.
Voss
,
E
.
R
.,
Zylberberg
,
J
., &
Fetsch
,
C
.
R
.
Neuron
, 110(8), 1362–1375.
2021
—
Attractor
dynamics
in
recurrent
neural
networks
explain
perceptual
multistability
.
Voss
,
E
.
R
., &
Beck
,
J
.
M
.
PLoS
Computational
Biology
, 17(5),
e
1009002.
2019
—
Probabilistic
inference
in
neural
circuits
:
a
canonical
computational
primitive
.
Voss
,
E
.
R
., &
Ma
,
W
.
J
.
Current
Opinion
in
Neurobiology
, 55, 112–119.
2017
—
Hierarchical
recurrent
processing
explains
variability
in
human
perceptual
decisions
.
Voss
,
E
.
R
.,
He
,
B
.
J
., &
Huk
,
A
.
C
.
Journal
of
Neuroscience
, 37(8), 2053–2067.
GRANTS
&
AWARDS
TEACHING
1 / 2
NSF
CAREER
Award
(2021–2026)
"
Probabilistic
computation
in
cortical
microcircuits
" —
$
1.2
M
NIH
R
01
(2022–2027)
"
Neural
basis
of
decision
-
making
under
uncertainty
" —
$
2.8
M
McDonnell
Foundation
Scholar
Award
(2018–2023)
$
600
k
Alfred
P
.
Sloan
Research
Fellowship
(2017)
James
S
.
McDonnell
Foundation
Postdoctoral
Fellowship
(2012–2014)
Computational
Neuroscience
(
PSYC
230) —
Graduate
seminar
Stanford
, 2020–
Present
Probabilistic
Models
of
Cognition
(
COGS
150) —
Undergraduate
Stanford
, 2021–
Present
Machine
Learning
for
Neuroscience
(
MIT
9.70) —
Graduate
MIT
, 2017–2020
Introduction
to
Cognitive
Science
(
UCSD
COGS
1) —
Undergraduate
UCSD
, 2013–2016
ADVISING
Current
:
5
Ph
.
D
.
students
(2
expected
2026), 3
postdoctoral
fellows
, 2
research
scientists
.
Past
:
12
Ph
.
D
.
graduates
(
now
at
Google
DeepMind
,
Princeton
,
MIT
,
UC
Berkeley
,
Chan
Zuckerberg
Initiative
,
Stanford
Medicine
), 7
postdocs
(
now
faculty
at
Columbia
,
UCL
,
University
of
Tokyo
,
Carnegie
Mellon
).
PROFESSIONAL
SERVICE
Editorial
Board
:
Journal
of
Neuroscience
(2019–
Present
),
PLoS
Computational
Biology
(2021–
Present
)
Program
Committee
Chair
:
Computational
and
Systems
Neuroscience
(
COSYNE
) 2024
Reviewer
:
NSF
,
NIH
,
Simons
Foundation
,
Wellcome
Trust
;
journals
including
Nature
,
Neuron
,
PNAS
,
eLife
Organizer
: "
Probabilistic
Computation
in
Neural
Systems
"
workshop
,
NeurIPS
2022 & 2023
Member
:
Society
for
Neuroscience
,
Computational
Neuroscience
Society
,
Cognitive
Science
Society
SELECTED
TALKS
&
KEYNOTES
"
Representational
geometry
of
uncertainty
in
cortical
circuits
" —
Keynote
,
COSYNE
2025,
Montreal
"
Meta
-
learning
Bayesian
priors
in
brains
and
machines
" —
Simons
Institute
,
UC
Berkeley
, 2024
"
Probabilistic
computation
in
neural
populations
" —
Gatsby
Computational
Neuroscience
Unit
,
UCL
, 2023
"
From
tuning
curves
to
probabilistic
codes
" —
Bernstein
Conference
2022,
Berlin
"
Recurrent
neural
dynamics
in
perceptual
inference
" —
Invited
talk
,
Stanford
Neurosciences
Symposium
, 2021
2 / 2
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