SPEAKER: Dr. Ahmad Dhaini, assistant professor of Computer Science at the American University of Beirut (AUB)
ABSTRACT:
In
this
talk,
we
discuss
a
case
study
on
how
automated
solution
using
computer
science
methods
such
as
machine
learning
and
image
analysis
can
help
in
clinical
decision-making.
Namely,
we
discuss
a
novel
automated
solution
that
evaluates
the
presence
of
corneal
haze
in
optical
coherence
tomography
images
for
keratoconus
patients
that
underwent
cross-linking.
Results
demonstrate
the
efficacy
and
effectiveness
of
the
proposed
techniques
vis-a-vis
manual
measurements
in
a
much
faster,
repeatable
and
reproducible
manner.
BIOGRAPHY:
Ahmad
Dhaini
is
currently
an
assistant
professor
of
Computer
Science
at
the
American
University
of
Beirut
(AUB),
and
visiting
assistant
professor
at
University
of
Waterloo,
while
on
leave
from
AUB.
He
received
his
B.Sc.
in
Computer
Science
from
AUB
in
2004,
his
M.Sc.
degree
in
Electrical
and
Computer
Engineering
from
Concordia
University,
Canada
in
2006,
and
his
Ph.D.
degree
in
Electrical
and
Computer
Engineering
from
University
of
Waterloo,
Canada
in
2011,
where
he
was
granted
several
research
and
teaching
awards.
Before
joining
AUB,
Dr.
Dhaini
was
a
Postdoctoral
Scholar
at
Stanford
University,
working
in
the
Photonics
and
Networking
Research
Laboratory
(PNRL)
after
being
awarded
the
Natural
Sciences
and
Engineering
Research
Council
of
Canada
Postdoctoral
Fellowship
(NSERC
PDF).
He
also
completed
the
Stanford
Ignite
program
for
entrepreneurship
and
innovation;
it
is
a
mini-MBA
program
in
Stanford’s
Graduate
School
of
Business,
designed
to
teach
scientists
how
to
convert
an
idea
into
a
business.
Dr.
Dhaini’s
research
interests
cover
several
themes
of
optical
networks
such
as
fiber-wireless
(FiWi)
broadband
access
networks,
mission-critical
networks,
green
communications,
and
software-defined
networking.
He
has
been
also
tackling
several
research
problems
related
to
Biotechnology,
especially
in
medical
image
analysis,
medical
wearable
devices,
and
mobile
health.