Seminar • Scientific Computation — Local, Scalable and Interpretable Graph Analytics
Kimon Fountoulakis, Postdoctoral fellow and co-PI
University of California at Berkeley and International Computer Science Institute
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.
Thomas Steinke, Postdoctoral researcher
IBM Almaden Research Center, San Jose, California
As data is being more widely collected and used, privacy and statistical validity are becoming increasingly difficult to protect. Sound solutions are needed, as ad hoc approaches have resulted in several high-profile failures.
Rina Wehbe, PhD candidate
David R. Cheriton School of Computer Science
Why do we care if our teammates are not human? This study seeks to uncover whether or not the perception of other players as human or artificial entities can influence player experience. We use both deception and a between-participants blind study design to reduce bias in our experiment.
Haifeng Xu, PhD candidate
Computer Science Department, University of Southern California
Strategic interactions among self-interested agents (a.k.a., games) are ubiquitous, ranging from economic activity in daily life and the Internet to defender-adversary interactions in national security. A key variable influencing agents' strategic decision making is the information they have available about their environment as well as the preferences and actions of others.
Daniel Recoskie, PhD candidate
David R. Cheriton School of Computer Science
Hicham El-Zein, PhD candidate
David R. Cheriton School of Computer Science
What are we? By what processes and patterns did we originate and how do these patterns compare to the processes of the world around us, digital and biological, societal and fictional?
Charles Perin, Department of Computer Science
City, University of London
We live in an increasingly data-driven world, where commercial, societal, environmental, and political decisions are made based on data. However, we also live in a world where most people lack the literacy required to participate in the data-informed debates of modern society. Perhaps the main barrier to improving people’s data literacy is that data is often associated with complexity, large scale, corporatism, and dystopia.
But data is about people.
Xi He, PhD candidate
Computer Science Department, Duke University