okay very good okay so my name is Elza Erkip. It's hard to believe but I've
been in this institution for almost 20
years. I started in 1999 and this
institution has changed for the better
and we're going up we're going up at a
fast pace. I'm a professor in the
electrical and computer engineering
department and I realize that I'm the
opening act for the better presentations
to come by our young students by our
junior faculty. So I wanted to take some
time and talk a little bit about what
engineering is, what it is to me, where do
I stand in this engineering world, and I
also wanted to give you a flavor of some
of the projects that we've been doing
particularly looking at networks,
understanding an engineering networks
from wireless networks to social
networks. I'm also proud mom of two
teenagers, two teenage daughters, and they
and their friends often ask me what is
engineering. Isn't it a boring subject?
And I say on the contrary, it's one
of the best jobs in the world and I hope
I can convince the non engineers in the
room that it's the best job in the world.
Now what is engineering? Okay so if you
know the dictionary definition of
engineering is application of scientific
knowledge to solve real-world problems.
And you'll also see engineering together
with science right and
engineering. What's the difference
between science and engineering? What
does the scientists do? What does an
engineer do? Well scientists goal is to
understand the universe and to create
knowledge to understand the universe.
Where as an engineer takes that
knowledge and uses it to solve
real-world problems by designing and
building things. So you know a scientist
maybe looks like the one on the left and
an engineer you know interesting enough I was
searching for cartoon engineers in the
internet and everything that came up had
a hard hat and a building. Well
there are some engineers who do that but
many of the engineers look like me, maybe 
in shabbier clothes. You know sitting in an
office, in front of a computer with pen
and pencil. So we do a lot of interesting things.
Now what does an engineer do? You know, so it solves real-world problems.
How does an engineer do it? Well I think
the first and the most important step or
one of the most important steps of
engineering is taking that real-world
problem, which is very complex and
abstracting it out. What's the
what's the essence of that problem? And
it's very important to come up with an
abstract model that's tractable so you
can understand and study it, but it's
complicated enough that it captures some
of the essences of the real world. So
this is the art of engineering if you will. And once you have a good abstract
model, the next step is to understand
that model and come up with solutions.
An engineer has a lot of tools at
her disposal such as you know many
scientific fields from biology to
physics to chemistry and certainly math
a lot of math you know which is what
makes it fun to understand this abstract
problem and devise solutions taking into
account practical constraints. Now
practical is very important here, we just
don't want to come up with any solution.
We want to come up with solutions that
realize that the real world has these
constraints whether they're
energy whether their computational
constraints, the materials you can use. So
these are very important in
understanding engineering problems. Now
computational tools are very important
as well and my dad was a civil engineer
and he spent a good part of his career
using this computational tool. Does
anybody know what this is? So my dad
used to go on and on how he would kind
of you know compute using fad rule. I
never got to see them but you know I
certainly use computers and and more and
more sophisticated computational tools
which we call artificial intelligence,
machine learning. These are all the tools
at an engineer's disposal. And at the end of
the day the engineer has to ensure that
the design solution works in the real
world. So never is the solution done
in a one-shot basis. There's a constant
feedback loop that the engineer has to
go through. So we abstract our problem,
we solve it, and then we have to build
and test and send it out to the real
world. And the real world tells us that
our solution works in certain ways but
doesn't work in certain other ways. So we
have to get it back to our engineering
domain this abstract domain, refine our
model, refine our solution. And rarely
this is done by one person. It takes a
team of engineers to do all of this
right and it takes a team of engineers
to communicate within the team but it
also takes the team of engineers to talk
to people who have this real-world
problem. So engineering involves art it,
involves communication certainly
communication skills are very important
that's why it's the best job in the
world, and it involves math. I love math. Okay so
what do I do? Where do I stand in this
engineering world? Now in high school you
know, as you realize you know, I was a
good student. I loved math. But I didn't
want to be just I shouldn't say just but
I didn't want to be a mathematician
working on pure math problems. I wanted
to use math to do things, so engineering
was the natural choice for me and I went
to into Electrical Engineering. And in my
area is can be called in general
networks, and I spend more on the side of
abstract modeling and solving problems
using that abstract model. But I also
collaborate with many other engineers in
understanding the practical problems,
practical constraints, and once in a
we will go out and build things as
well. So certainly I have physics and I
have a lot of math at my disposal but
also a lot of the computational tools as
well. So today I want to give you a
flavor of the kinds of things that I've
been working on.
And I want to give two examples, one from
wireless networks which is an area that
have spent throughout my career, and I want
to tell you in an earlier work that we
did when I started my career at NYU
which can you really jump started my
career and went on for for almost two
decades, and I want to tell you a little
bit about social networks in an area
that we have started getting into
recently. Now before I tell you about my
work, I want to tell you how
your phone works. You know 30
second introduction to wireless, wireless
101. Well so any wireless system is gonna
follow a certain kind of infrastructure
and the way it works is that there are
base stations or if you're using Wi-Fi
there are access points that your phone
communicates with. So whenever you want
to make a call your phone connects to a
base station and then the base station
takes your signals wherever they need to
go. Similarly if you want to download the
YouTube video on your phone, you'll
receive it over the wireless link
through your base station. So if I wanted
to text Jelena we couldn't do it
directly, it has to go through the base
station and that's the basic structure
that all wireless networks abide by. Now
our idea again when I started my career
here was to look at wireless networks
and try to solve this problem of
having unreliable wireless links. So when
a phone is trying to talk to the base
station, that wireless link is typically
unreliable because you know we move
around, the environment changes, signals
can get blocked. So then what happens you
know you don't want to lose the
communication right so you either need
to find another base station to connect
to, or you need to somehow try to repair
that link. And our solution was kind of a
very naive one, if you will, a very simple
one. We said well there are other phones
nearby, why don't I you
use them to help me out? You know they're
around me, they can overhear me,
maybe they can forward my information to
the base station. And then maybe
when I'm in a bad spot, you know one
mobile you know Jelena helps me I mean
she's in a bad spot I help her out.
So it works out for both of us and it improves
communication for both of us.
Now of course devil is in the details
right. It took us many many many years,
you know many many students, many papers
to actually nail this down, get an
abstract model, show that it works. And
this area called cooperative networking
was in fact pioneered by NYU, myself,
and other researchers. And we had
many many students, many talented
students, you know collectively me and
my colleagues won several awards, we
had important papers, and we did in fact
build testbed and some of our ideas
impacted industry standardization and
inspired different wireless technologies
based on this idea of cooperation you
know. Sometimes cooperating mobile,
sometimes cooperating base stations but
this kind of idea made it itself into
reality. Of course now we're part of a
much bigger center called NYU Wireless
and we're at the forefront of wireless
research and we're looking into 5g
wireless, that's the next generation of
wireless, where it's no longer humans
communicating, it's machines
communicating. Whether as an Internet of
things, your fridge orders milk, you know
when it realizes that you're out of milk
or maybe kind of more impactful
solutions such as health care, wildlife
monitoring, you name it. We're also
looking at robotics applications,
industrial automation where wireless is
an important component to make autonomy
among the robots. Autonomous driving,
augmented reality, virtual reality, so now
we're going beyond humans communicating
and Wireless Link is still an important
part of it. So next I want to kind
of switch gears a little bit and I want
to tell you a little bit about a recent
project that we started working on which
is looking at social networks
and in particular privacy in social
networks. Now of course we're all worried
about online privacy. We're worried
about you know Facebook selling our data,
Google, cell phone companies and the kind
of privacy that I'm gonna address here
maybe goes back to the Netflix Grand
Challenge. Who here remembers the Netflix
Grand Challenge? A few people, so about a
little over a decade ago
Netflix wanted to improve its
recommendation systems. So it said I'm
gonna provide data to researchers so
that they could come up with better
recommender systems than I can. So to do
that, Netflix provided users and the
movies that they liked and the stars
that they gave, made it available to
researchers, but in order to protect
privacy of users, they removed user identities.
Okay, so they they thought that that
would keep anonymity of the users. Little
did they know that there were a lot a
lot of researchers out there who went
into public databases like Internet
Movie Database figured out you know
people with their own identities what
they did how they rated the movies and
were able to match and figure out many
users identities on Netflix. This caused
a big uproar, there were some lawsuits
filed, there were similar incidents
happening with AOL removing the making
available the search data by removing
identity of users again the same thing
using publicly available information it
was possible to deanonymize the users
and more recently we see similar kinds
of privacy issues happening in social
networks. We all have our professional
identities on LinkedIn and we also have
our personal social networks such as
Facebook and Instagram. And we wouldn't want
our professional
and personal identities to be matched
with one another. But it turns out that
it's not too difficult to match
identities across social networks
there's been you know several
researchers showing that this is
possible. So our approach has been again
looking at this practical problem and
trying to understand the fundamentals by
abstracting it out. So we've recently
started looking at database and graph
matching in social networks so imagine
two databases such as Rotten Tomatoes
and Netflix rankings. In one database you
know the identities of the users and in the
other one you don't, but certainly
there's some relationship
among these two databases. Similarly you
can envision two social networks in one
you know the identities in the other you
don't but certainly there's a realize
they're not the identical social
networks but they're related. So can we
use properties of these databases and
social networks to actually map the
users? So what we're doing is we're
coming up with tractable yet realistic
mathematical models we're trying to
understand some of the fundamental
limits and algorithms in particular one
can you match the users and that's not a
good thing right so how do we protect
anonymity if we don't want users to be matched. Maybe we could add
some noise but we still want to maintain
the usefulness of these databases. And
then we're also thinking about good
applications of this. You know maybe
matching these databases could be
desirable. My husband is a cancer
researcher and he said that one of the
important problems they face is that
they have a database of childhood cancer
survivors but they cannot constantly
monitor all of them. And they have
a database of adult cancer patients
so these databases are anonymized
you know researchers aren't supposed to
know the identities but if you could
match these two databases then you could
learn what happens to childhood cancer
survivors when they become adults and it
could be a very useful information. So I
hope I've kind of managed to
convinced the non-engineers in the crowd
that engineering is an exciting field it
involves artistry, it involves
communication, it involves a lot of
technical tools but it also involves
talking to a lot of people and with that
I'm happy to take some questions
