Monisha
Jegadeesan
Software
Engineer,
Google
H
+91
9035212894
B
monishaj.65@gmail.com
Í
monisha-jega.github.io
monisha-jega
monisha-jegadeesan
Education
2015-2020
Dual
Degree
(B.Tech
+
M.Tech)
in
Computer
Science
and
Engineering
Indian
Institute
of
Technology
Madras,
Chennai,
India
CGPA:
8.78
2015
XII
-
Karnataka
Board,
KLE
Society’s
Independent
PU
College,
Bangalore
97.30
%
2013
X
-
ICSE,
B
P
Indian
Public
School,
Bangalore
96.33%
Professional
Experience
Dec
2022
-
Present
Software
Engineer,
Level
IV,
Google
LLC,
New
York
{
Working
on
Keep,
a
notetaking
editor
in
Google
Workspace.
Aug
2020
-
Nov
2022
Software
Engineer,
Level
IV,
Google
India
Pvt
Ltd,
Bangalore
{
Developing
intelligent
features
for
the
Google
Workspace
Editors
(Docs,
Slides,
Keep,
etc)
using
my
expertise
on
the
products’
client-side
software,
supporting
tools
and
libraries,
and
natural
language
processing
infrastructure.
{
Using
cutting-edge
frontend
tools
like
Web
Assembly
and
Emscripten,
and
Google-internal
technologies
like
j2Cl,
client-side
cross-platform
frameworks
and
build
systems,
to
develop
user-facing
features
such
as
spellcheck
in
encrypted
documents
for
five
languages
and
writing
style
suggestions
for
English
text.
{
Formulating
technical
designs
for
independent
end-to-end
problems,
driving
cross-team
collaboration,
upholding
software
reliability
practices,
technical-debt
resolution
and
documentation,
and
proactively
identifying
areas
of
future
work.
{
Guiding
junior
engineers
on
programming
and
software
design
tasks
to
enable
timely
delivery
of
products
to
customers.
May
2019
-
July
2019
Software
Engineering
Intern,
Google
India
Pvt
Ltd,
Bangalore
Worked
on
the
Editors
client-side
software
infrastructure
to
develop
a
user
interface
with
control
options
to
undo
or
provide
feedback
on
the
correction
and
a
logging
framework,
for
the
Google
Docs
text
auto-correction
feature.
May
2018
-
July
2018
Research
Intern,
Big
Data
Experience
Labs,
Adobe
Research,
Bangalore
Developed
a
mobile
application
for
Text
to
Scene
Conversion
in
Augmented
Reality,
based
on
novel
research
techniques
for
prediction
of
three-dimensional
object
sizes
and
positions
from
textual
features.
Research
Experience
Sep
2019
-
May
2020
Paraphrase
Generation
with
a
Bilingual
Model
and
Continuous
Embeddings
Master’s
Thesis,
Language
Technologies
Institute,
Carnegie
Mellon
University
Machinated
a
novel
technique
for
paraphrase
generation
using
the
von
Mises-Fisher
(vMF)
Loss
on
a
transformer
network,
and
showed
that
it
produces
superior
paraphrases
as
compared
to
the
log-likelihood
model
by
employing
bilingual
data
to
induce
zero-shot
paraphrasing,
guided
by
Prof.
Yulia
Tsvetkov
.
May
2017
-
July
2017
Cognitive
Approach
to
Natural
Language
Processing
Research Intern,
Department of Computer Science and Automation, Indian Institute of Science (IISc), Bangalore
Developed
a
cognitive
text
parser
that
combines
syntactic
and
semantic
approaches,
to
process
textual
data
into
cognitive
structural
representations,
to
be
used
as
a
feature
extractor
for
downstream
NLP
tasks,
and
demonstrated
the
correlation
of
the
extracted
cognitive
features
with
semantic
and
syntactic
text
features,
guided
by
Prof.
Veni
Madhavan
.
Publications
and
Patents
[Publication
and
Poster]
Improving
the
Diversity
of
Unsupervised
Paraphrasing
with
Embedding
Outputs
(
Paper
,
Poster
)
Monisha
Jegadeesan
,
Sachin
Kumar,
John
Wieting,
Yulia
Tsvetkov
In
Workshop
on
Multilingual
Representation
Learning
,
The
2021
Conference
on
Empirical
Methods
in
Natural
Language
Processing
(
EMNLP
2021
)
[Publication
and
Poster]
Adversarial
Demotion
of
Gender
Bias
in
Natural
Language
Generation
(
Paper
,
Poster
)
Monisha
Jegadeesan
In
ACM
CODS-COMAD
2020
-
Young
Researchers’
Symposium
[Poster]
ARComposer:
Authoring
Augmented
Reality
Experiences
through
Text
(
Poster
)
Sumit
Kumar,
Paridhi
Maheshwari,
Monisha
Jegadeesan
,
Amrit
Singhal,
Kush
Kumar
Singh,
Kundan
Krishna
In
ACM
User
Interface
Software
and
Technology
Symposium
2019
(
ACM
UIST
2019
)
[Filed
Patent]
Visualizing
Natural
Language
through
3D
Scenes
in
Augmented
Reality
Sumit
Kumar,
Paridhi
Maheshwari,
Monisha
Jegadeesan
,
Amrit
Singhal,
Kush
Kumar
Singh,
Kundan
Krishna
Filed
at
the
US
PTO
(Application
Number:
16/247,235)
[Publication
and
Poster]
Leveraging
Ontological
Knowledge
for
Neural
Language
Models
(
Paper
,
Poster
)
Ameet
Deshpande,
Monisha
Jegadeesan
In
ACM
CODS-COMAD
2019
-
Young
Researchers’
Symposium
Projects
July
2019
-
Dec
2019
Graph
Neural
Networks
for
Extreme
Summarization
Indian
Institute
of
Technology
Madras
Formulated
appropriate
graph-based
deep
neural
models
for
the
Extreme
Summarization
(
XSum
)
task
with
sentence-level
and/or
document-level
graphs,
and
obtained
better
performance
than
simple
recurrent
and
hierarchical
models.
March
2019
-
April
2019
Risk-Sensitivity
in
Multi-Armed
Bandits
Indian
Institute
of
Technology
Madras
Surveyed and implemented risk-sensitivity methods for stochastic bandit problems, and upgraded the Explore-Then-Commit
algorithm
for
VaR
and
cVaR
measures
with
competent
performance.
Aug
2018
-
Dec
2018
Leveraging
Ontological
Knowledge
for
Neural
Language
Models
Indian
Institute
of
Technology
Madras
Incorporated
Weight
Initialization
in
learning
word
embeddings
using
the
WordNet
Ontology
for
a
task
in
the
Construction
domain,
resulting
in
a
faster
convergence
rate
and
better
representation
of
domain-specific
terms.
July
2018
-
Dec
2018
Multimodal
Dialogue
Generation
Indian
Institute
of
Technology
Madras
Developed
a
deep
neural
model
to
establish
the
positive
effect
of
domain
features
in
the
performance
of
image
retrieval
in
multimodal
dialogue
systems
and
explored
the
performance
of
attention
and
memory-based
models
with
adaptations
for
multimodal
dialogue
and
domain
knowledge
integration.
Oct
2018
-
Nov
2018
Risk-Sensitive
Reinforcement
Learning
Indian
Institute
of
Technology
Madras
Empirically
analyzed
the
existing
methods
for
risk-sensitive
reinforcement
learning,
tested
the
effectiveness
of
modified
versions
and
proposed
a
new
distance-based
risk
measure
and
algorithm
for
Gridworld.
Feb
2018
-
March
2018
Summarization
and
Keyword
Extraction
using
TextRank
Indian
Institute
of
Technology
Madras
Analysed
the
TextRank
algorithm
for
keyword
extraction
with
syntactic
filters
and
augmentation
via
Explicit
Semantic
Analysis,
and
for
text
summarization
with
exploration
of
various
textual
similarity
methods.
Nov
2016
-
Dec
2016
Scaling
Graph
Algorithms
Indian
Institute
of
Technology
Madras
Implemented
optimized
graph
algorithms
for
maximum
network
flow
and
finding
a
maximum
matching
in
a
bipartite
graph
for
real
data
graphs
with
up
to
10,000
vertices
and
100,000
edges.
Nov
2017
Skin
Disease
Diagnostic
System
Microsoft
code.fun.do
Contest,
Indian
Institute
of
Technology
Madras
Designed
a
web
application
that
attempts
to
diagnose
skin
diseases
based
on
images
of
the
user’s
skin
powered
by
a
deep
neural
model
trained
on
a
dataset
created
by
scraping
images
from
the
web.
Sept2017
-
Oct
2017
Breakout
Game
Indian
Institute
of
Technology
Madras
Developed
an
Android
application
for
the
Breakout
game
with
basic
playing
and
scoring
features.
Teaching
Experience
Jan
2020
-
May
2020
Natural
Language
Processing
-
Course
Teaching
Assistant,
Indian
Institute
of
Technology
Madras
{
Designed
and
evaluated
theoretical
and
practical
assignments
on
various
topics
in
Natural
Language
Processing.
{
Presented
lectures
on
Edit
Distance
and
the
Cocke-Young-Kasami
(CYK)
algorithm
,
to
a
class
of
70
students.
{
Mentored
sixteen
pairs
of
students
on
research
projects,
with
supervision
through
regular
team-wise
progress
meetings.
Courses
[Statistical
Learning]
Advanced
Deep
Learning,
Deep
Learning,
Machine
Learning,
Natural
Language
Processing,
Reinforcement
Learning,
Multi-Armed
Bandits,
Probabilistic
Graphical
Models,
Computational
Models
of
Cognition
[Curriculum]
Computer Networks, Database Systems, Operating Systems, Data Structures and Algorithms, Object-Oriented Programming
[Mathematics]
Probability-Statistics-Stochastic
Processes,
Discrete
Mathematics,
Linear
Algebra,
Graph
Theory
Skills
Languages
C,
C++,
C#,
Java,
Python,
HTML,
CSS,
Javascript,
Web
Assembly
Tools
Unity,
ARCore,
Android
Studio,
Stanford
CoreNLP,
Git,
Bootstrap,
jQuery,
Emscripten,
Blaze,
j2Cl
Libraries
NLTK,
django,
scipy,
pandas,
sklearn,
gensim,
keras,
tensorflow,
pytorch
Scholastic
Achievements
{
First
runner-up
in
the
AWS
Deep
Learning
Hackathon
held
during
Shaastra
2018,
IIT
Madras:
Developed
a
prototype
for
image-translation
of
English
text
on
signboards
and
posters
into
vernacular
languages.
{
State
Rank
17
in
Karnataka
Common
Entrance
Test
for
Engineering,
2015,
out
of
approximately
1.2
lakh
students.
{
Topped
respective
academic
institutions
in
both
Class
X
and
Class
XII
board
exams.
Positions
of
Responsibility
June
2019
Organizer,
Management
Team,
Tech
Intern
Connect,
Google
India
Pvt
Ltd,
Bangalore
{
Member
of
the
central
managing
committee
that
organized
a
networking
event
hosting
technology
interns
from
the
city.
June
2016
-
Dec
2016
Technical
Operations
Coordinator,
Shaastra
2017,
Indian
Institute
of
Technology
Madras
{
Developed
the
front-end
components
of
major
websites
and
internal
portals
for
the
annual
technical
fest
of
IIT
Madras.
Extra
Curricular
Activities
Cultural
Trained
in
and
have
performed
the
Indian
classical
dance
form
of
Bharatanatyam
for
eight
years.
Sports
Part
of
NSO
(Institute
Sports)
Basketball
during
the
first
year
of
engineering
(2015-2016).