Data-driven Decision-making
Monday, March 31, 2014 - 8:45am - 10:00am
KEC 1007
Scott Sanner
NICTA and the Australian National University
Abstract:
Social media is connecting all information, the Internet is becoming more
interactive and personalized, and every embedded system that impacts our lives
-- from our daily commute to our consumer needs -- is becoming increasingly
adaptive to our welfare and that of society. The wealth of structured,
real-time information that we can leverage for computationally automated
decision-making in these settings is unprecedented and requires a fundamental
reassessment of how we approach these problems from a data-driven perspective.
In this talk I will outline my contributions and lessons learned from working
on a variety of commercial and industrial data-driven decision-making problems
ranging from social media recommendation to traffic control. I will conclude
with a vision that unifies learning, inference, and optimal sequential
decision-making and suggest that between the two extremes of the most general
theoretical frameworks and existing specialized solutions, there lies a vast!
unexplored space of models and algorithms that promise to shape the future of
how computation interacts with the world.
Biography:
Scott Sanner is a Principal Researcher at NICTA Canberra (a research lab intended to incubate startups and foster collaboration between academia and industry) and Adjunct Faculty at the Australian National University where his research spans a broad range of topics from the data-driven fields of machine learning and information retrieval to the decision-driven fields of artificial intelligence and operations research. Scott has applied the analytic and algorithmic tools from these fields to diverse application areas such as social media recommendation, preference learning, and transport optimization. Scott earned a PhD in Computer Science from the University of Toronto, an MS in Computer Science from Stanford, and a double BS in Computer Science and Electrical and Computer Engineering from Carnegie Mellon. During his studies, Scott interned with numerous research institutions including Microsoft Research Cambridge, Toyota Technological Institute at Chicago, Sun Microsystems !
Research Labs, Lockheed Martin, and the National Cancer Institute.
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