Event Location: NSH 1305
Bio: Emma Brunskill is an an Assistant Professor in the Computer Science
Department at Carnegie Mellon University. She was previously a NSF
Mathematical Sciences Postdoctoral Fellow at the University of California,
Berkeley. She completed her PhD in Computer Science at MIT on a NSF Graduate
Fellowship and her masters in Neuroscience at Oxford University as a Rhodes
Scholar. Her research interests include artificial intelligence, machine
learning, human-robot interaction and information communications technology
for international development.

Abstract: Making good sequential decisions under uncertainty is a core part of what it
means to be intelligent. In this talk I will discuss several algorithms that
leverage structure common in diverse problem classes in order to efficiently
make decisions in dramatically larger domains.
I will present results from my robotics work, and I will also share results
of a field study in Bangalore, India demonstrating that an adaptive tutoring
software game designed for low resource schools has the potential to
increase student engagement. This field trial is part of an ongoing research
thrust towards improving student learning by addressing the sequential
decision making challenges that arise in education.