Professor Sayama, Systems Science & Industrial Engineering


[Music] Hello, my name is Hiroki Sayama. I’m an associate professor in the Department
of System Science and Industry Engineering at the Thomas J. Watson School of Engineering
and Applied Science. I’m also the graduate program director of
the System Science PhD and masters programs here at Watson School. My research area is generally called complex
system science and engineering, which embraces many different kinds of systems that are made
of many different components that are interacting with each other to create very interesting
behaviors. My original research area was actually computer
science, specifically it’s called the parallel processing – now it’s called the distributed
computation – which is the research area where you have lots and lots of computing units working
together to simulate or calculate very complex computational tasks. And when I was working on that task as a masters
student, I got kind of interested in the interaction between competing computing units. When you put many different units together,
their behavior started looking kinda weird, even though you designed everything through
the bottom of the detail. So that is called emergent properties. When you have interacting components working
together, sometimes their interaction actually causes the really non-trivial outcome. So that is one of the roots why I get interested
in this research area. So that made me drop out of the mainstream
of computer science. Now I’m working on very interdisciplinary
research area. Anything and everything that can be considered
as a complex systems is part of my research agenda. Even though we are part of the engineering
school, I would say the system science program is probably the farthest away from the core
engineering part. We can study, you know, things that are almost
remotely, you know, they’re related to engineering concepts, such as the social media and, you
know, and propagating diseases in human social systems. As long as we can formulate their behaviors
and structures by using some mathematical computation terms, we can study and potentially
predict or manipulate the behavior of those systems. So that’s the – what’s most challenging about
systems science. So, therefore, I’d like to see the students
who are intellectually really, really risk-taking and those people who are not comfortable sitting
in the single discipline – those other the perfect students for our program. [Music]




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