Rutgers University is one of America's oldest universities. It was founded in 1766,
one of the original eight colonial colleges. The DIMACS center is a little bit younger
than that. It was founded in the late 80s through a National Science Foundation
nationwide competition for science and technology centers. CCICADA Center is even
younger than that. It was founded in a nationwide competition for the
Department of Homeland Security University centers of excellence dealing
with data science. This is an academic institution we tried to develop general
methods that are usable to solve problems other than the ones we start
with. So in our case we've worked with evacuation modeling and inspection
modeling at stadiums and now those have been applied more recently too large
transportation facilities like the bus terminal in New York City and we've used
the same ideas to study inspection of containers as they arrive at the ports.
So here we go from developing ways to solve one problem to using math and computer
science and statistics to solve other problems.
My research broadly focuses on developing computation models of human behavior and how humans
act and interact in high-density situations such as crowds for example.
One key facet of this research is to ensure that
these computation models are grounded in reality and are able to emulate real human
behavior. To facilitate this process we base our computational models of real
empirical observations of human crowds. We are collaborating with a large number of
faculty at Rutgers University to develop an end to end solution for
reconstructing simulating and analyzing and optimizing crowd dynamics at the
Port Authority Bus Terminal. The first step in this process is to use state of
the art light-up technology to reconstruct the entire Port Authority Bus Terminal.
We're then using advanced computer vision technology to be able to reconstruct the
crowd and then finally using this reconstructed data as ground truth we
are developing computational models to be able to simulate the crowd in these
virtual models. So we can use these tools to ask what if questions. For example how would
the crowd will be impacted if we were to change the layout of the building of the Port
Authority Bus Terminal and this allows us to even facilitate the design
and architectural layout of the bus terminal without running expensive and
often prohibitive human subject experiments even before the building was
actually constructed.
So at CCICADA we've worked on developing best practices for stadium security.
This has been for different DHS agencies especially the Office of Safety Act
Implementation who deals with liability protection for a large entertainment
venues that have effective counter-terrorism measures. One of our
projects regarding the stadium security has been in developing mathematical
model and simulation for venues to study their security screening process. At one
particular stadium venue they were considering changing their security
screening procedure from metal detecting wands to walk through metal detectors and so we were able to
actually use our simulator tool that we developed at CCICADA to let them see how it
would impact their patrons through-put rate and it turned out that actually their
initial idea of how many metal detectors to acquire were actually far too few so, in the end
they had to defer their plan and acquire much more metal detectors down the road. One of the
things that we've been researching over the last year or so is walk through metal
detectors in particular. So we've done a lot of experiments with those and this
summer we've had two undergraduate students come in through our REU program,
Research Experience for Undergrads, and they've been helping me work with these
experiments and so the experiments look at how these metal detectors work indoors
and outdoors, on what are the settings
you know how did they perform with people walking through them with
different mental test objects. So you look at different heights, different
orientations on someone's body and how does that impact detection depending on
how you even walk and we are presenting those results to different sports stadiums
and even here at Rutgers to the Rutgers police.
It's an exciting project. DIMACS is the Center for Discrete Math and Theoretical Computer
Science. We were founded in 1989 as an NSF science and technology center.
We continue with our mission to catalyze and conduct research and education in
discrete mathematics, theoretical computer science, and their related areas:
algorithmics, modeling, statistical analysis and so on. My own personal area of research centers a lot around
privacy and security and a recent project that we were involved in was
around modeling of human mobility so the idea is that it's very useful to know
where people concentrate, how they moved throughout the course of the day, not
just as individuals but as a population. Starting off in their homes in the
suburbs, moving into the city to work of course is a very typical pattern but there's
all kinds of other patterns as well and our work on human mobility builds on
some work with our partners at AT&T Labs and Princeton and elsewhere looking at
how you can take
data from cell phone records where you've got just locations, this phone was
at this cell tower, made a phone call or made a text, and so you have a very rich
data source that can be used to understand the patterns of how people
follow. Our work in particular and our contribution to that work was to
add a layer of privacy in there of course, of coursse cell phone data has a lot of privacy
concerns as well as concerns about proprietary-ness of the data so a cellphone
provider is typically not going to want to release their data both because they
have promises to their customers but also because there are business secrets
in that information and so our work actually in a very mathematically
principled way and sort of what's called differential privacy as a layer in the
modeling procedure where we reduce the impact any one individual's data has
on the final outcome and then we did some experimental work to validate that
we were still getting good and useful results. Rutgers is really at the forefront
of work in homeland security and we are recognized in all the work we've already
done. And it's very clear that there's a lot more to do.
But we start from a great place.