Professor CV — page 1

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

Professor CV — page 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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