Elena
Vasquez
PhD
Candidate
in
Computational
Neuroscience
elena
.
vasquez
@
stanford
.
edu
+1 (650) 555-0192
Stanford
,
CA
elenavasquez
.
io
·
github
.
com
/
evasquez
RESEA RCH
INT EREST S
Neural
coding
Population
dynamics
Reinforcement
learning
High
-
density
electrophysiology
Computational
psychiatry
Causal
inference
EDUCAT ION
PhD
in
Neuroscience
Expected
June
2026
Stanford
University
,
Stanford
,
CA
Advisor
:
Prof
.
Maya
Chen
·
Dissertation
:
Neural
population
dynamics
underlying
credit
assignment
in
reward
learning
BSc
in
Cognitive
Science
,
summa
cum
laude
May
2020
University
of
California
,
Berkeley
,
CA
Minor
in
Computer
Science
·
GPA
: 3.98/4.0 ·
Highest
Honors
in
Cognitive
Science
PUBLICAT IONS
Cortical
population
dynamics
reflect
task
-
specific
credit
assignment
signals
.
Vasquez
,
E
.
,
Chen
,
M
.
Nature
Neuroscience
, 2025.
Featured
Article
A
framework
for
dissociable
value
and
policy
learning
in
recurrent
neural
networks
.
Kim
,
J
.,
Vasquez
,
E
.
,
Chen
,
M
.
Advances
in
Neural
Information
Processing
Systems
(
NeurIPS
), 2024.
Spotlight
Neural
manifolds
of
uncertainty
during
probabilistic
reversal
learning
.
Vasquez
,
E
.
,
Park
,
S
.,
Chen
,
M
.
Proceedings
of
the
National
Academy
of
Sciences
, 2024.
Hierarchical
inference
in
prefrontal
cortex
during
volatile
environments
.
Vasquez
,
E
.
,
Chen
,
M
.
Computational
and
Systems
Neuroscience
(
COSYNE
)
Abstract
, 2023.
RESEA RCH
EXPERIENCE
Graduate
Research
Assistant
Sep
2020 –
Present
Chen
Lab
,
Wu
Tsai
Neurosciences
Institute
,
Stanford
University
Undergraduate
Research
Assistant
Jan
2019 –
Aug
2020
Redwood
Center
for
Theoretical
Neuroscience
,
UC
Berkeley
Research
Intern
Jun
2018 –
Dec
2018
Janelia
Research
Campus
,
HHMI
T EACHING
EXPERIENCE
Teaching
Assistant
,
NSCI
200 —
Neural
Data
Science
Spring
2023, 2024
Stanford
University
Designed
and
implemented
closed
-
loop
optogenetics
+
Neuropixels
recordings
in
behaving
mice
to
dissect
prefrontal
-
subcortical
circuits
during
reward
-
guided
decision
making
—
Developed
a
variational
autoencoder
framework
for
demixing
mixed
-
selectivity
neural
populations
,
reducing
dimensionality
from
~800
neurons
to
12
latent
factors
—
Built
and
maintained
a
shared
analysis
pipeline
(
Python
,
DataJoint
)
adopted
by
4
lab
members
for
spike
sorting
,
behavioral
alignment
,
and
statistical
modeling
—
Modeled
hierarchical
Bayesian
inference
in
prefrontal
cortex
using
probabilistic
programming
(
Pyro
)
and
compared
model
predictions
to
human
fMRI
data
—
Co
-
authored
a
first
-
author
preprint
on
uncertainty
representation
in
prefrontal
cortex
during
reversal
learning
—
Developed
a
real
-
time
calcium
imaging
analysis
pipeline
(
Suite
2
p
+
custom
Python
)
for
larval
zebrafish
whole
-
brain
recordings
—
Identified
a
novel
population
code
for
prey
capture
initiation
in
the
optic
tectum
,
presented
at
Janelia
Annual
Meeting
—
1 / 2
Developed
course
materials
on
dimensionality
reduction
,
GLMs
,
and
spike
train
analysis
for
45
graduate
students
.
Held
weekly
office
hours
and
led
two
computational
lab
sections
.
Received
TA
excellence
award
(
Spring
2024).
Guest
Lecturer
,
PSYC
150 —
Computational
Psychiatry
Fall
2023
Stanford
University
Delivered
a
90-
minute
lecture
on
reinforcement
learning
models
of
anhedonia
and
their
neural
correlates
.
Designed
an
in
-
class
coding
exercise
using
hierarchical
Bayesian
models
.
SKILLS
&
MET HODS
Experimental
:
Neuropixels
,
two
-
photon
calcium
imaging
,
optogenetics
,
stereotaxic
surgery
,
mouse
behavior
(
operant
,
reversal
learning
,
foraging
),
chemogenetics
,
histology
,
whole
-
cell
patch
clamp
(
experience
)
Computational
:
Python
,
MATLAB
,
R
,
C
++ (
intermediate
),
PyTorch
,
JAX
,
GPyTorch
,
DataJoint
,
Suite
2
p
,
Kilosort
,
Stan
,
probabilistic
programming
(
Pyro
,
NumPyro
)
Analysis
:
Dimensionality
reduction
(
PCA
,
LDS
,
VAE
),
GLMs
,
reinforcement
learning
models
,
Bayesian
inference
,
time
-
series
analysis
,
spectral
analysis
,
spike
sorting
,
decoding
,
representational
similarity
analysis
Other
:
Git
,
Docker
,
SLURM
/
HPC
,
AWS
(
EC
2,
S
3),
scientific
writing
,
peer
review
(
reviewed
for
JNeurosci
,
eLife
,
NeurIPS
),
mentorship
of
3
rotation
students
HONORS
&
AWA RDS
Wu
Tsai
Interdisciplinary
Scholar
Award
—
Stanford
University
2024
NSF
Graduate
Research
Fellowship
(
GRFP
)
—
Honorable
Mention
2021, 2022
TA
Excellence
Award
—
Stanford
Department
of
Neurobiology
2024
Summa
Cum
Laude
&
Highest
Honors
in
Cognitive
Science
—
UC
Berkeley
2020
Goldwater
Scholar
—
Barry
Goldwater
Scholarship
Foundation
2019
SERVICE
&
OUT REACH
Co
-
Organizer
,
Stanford
NeuroData
Journal
Club
2022 –
Present
Co
-
founded
a
weekly
journal
club
bridging
computational
and
experimental
neuroscience
.
Manage
speaker
schedule
,
moderate
discussions
,
and
mentor
first
-
year
graduate
presenters
. ~25
regular
attendees
across
6
departments
.
Mentor
,
BRAINS
Program
for
Underrepresented
Undergraduates
2023 –
Present
Mentor
2
undergraduate
researchers
from
underrepresented
backgrounds
on
independent
computational
projects
.
One
student
received
a
Cota
-
Robles
fellowship
;
both
presented
at
SACNAS
.
REFERENCES
Available
upon
request
.
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