Sangho Lee, Postdoctoral fellow
School of Computer Science, Georgia Institute of Technology
Drop by MC third floor, outside Math C&D for photo opportunities with Professor Stephen M. Watt, Dean of Mathematics, and other Math faculty members to commemorate supporters of the HeForShe campaign.
Time: 11:30 a.m. to 1:30 p.m. (or until the cupcakes last!)
Show your commitment and join the movement ... #COUNT ME IN
Free cupcakes for participants.
IMPACT 10x10x10
Ashvin Goel, Associate Professor
Electrical and Computer Engineering and Computer Science, University of Toronto
Pedram Ghodsnia, PhD candidate
David R. Cheriton School of Computer Science
James Wright, Postdoctoral researcher
Microsoft Research, New York
Rina Wehbe, PhD candidate
David R. Cheriton School of Computer Science
Designing difficulty levels in platformer games is a challenge for game designers. It is important because design decisions that affect difficulty also directly affect player experience. Consequently, design strategies for balancing game difficulty are discussed by both academics and game designers.
Chenyan Xiong, PhD candidate
Carnegie Mellon University
Search engines and other information systems have started to evolve from retrieving documents to providing more intelligent information access. However, the evolution is still in its infancy due to computers’ limited ability in representing and understanding human language.
Michael Abebe, PhD candidate
David R. Cheriton School of Computer Science
Cloud storage systems typically choose between replicating or erasure encoding data to provide fault tolerance. Replication ensures that data can be accessed from a single site but incurs a much higher storage overhead, which is a costly downside for large-scale storage systems. Erasure coding has a lower storage requirement but relies on encoding/decoding and distributed data retrieval that can result in increased response times.
Kimon Fountoulakis, Postdoctoral fellow and co-PI
University of California at Berkeley and International Computer Science Institute
Cong Guo, PhD candidate
David R. Cheriton School of Computer Science
Consolidation of multiple workloads is cost-effective for system operators. However, it is difficult to determine how to share resources among multiple tenants to achieve both performance isolation and work conservation. The primary shared resource in the server are the CPU cores. We show that current solutions cannot handle CPU sharing very well in various multi-tenancy scenarios.