Maryam Mehri Dehvani
Department of Electrical and Computer Engineering, Rutgers University
The emergence of stupendously large matrices in applications such as data mining and large-scale scientific simulations has rendered the classical software frameworks and numerical methods inadequate in many situations. In this talk, I will demonstrate how building domain-specific compilers and reformulating classical mathematical methods significantly improve the performance and scalability of large-scale applications on modern computing platforms.
Aayush Rajasekaran, Master's candidate
David R. Cheriton School of Computer Science
William Callaghan, Master’s candidate
David R. Cheriton School of Computer Science
Ahmed El-Roby, PhD candidate
David R. Cheriton School of Computer Science
Today, there is an abundance of structured data available on the web in the form of RDF graphs and relational (i.e., tabular) data. This data comes from heterogeneous sources, and realizing its full value requires integrating these sources so that they can be queried together. Due to the scale and heterogeneity of the data sources on the web, integrating them is typically an automatic process.
Thomas Steinke, Postdoctoral researcher
IBM Almaden Research Center
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.
Come out to The Critical Media Lab at 44 Gaukel Street in Kitchener is experience the first ever Computational Digital Art Capstone Exhibition, where you will see interactive and digital art pieces made by students from the University of Waterloo!
Featured artists
Erin Kim
Helga Jiang
Susie Su
Simon Yu
Bonnie Wu
Stephanie Lin
Saadiya Desai
Jennifer Wu
Jimmie Shan
Xiao-Bo Li, PhD candidate
David R. Cheriton School of Computer Science
Xiao-Bo Li, PhD candidate
David R. Cheriton School of Computer Science
Edward Zulkoski, PhD candidate
David R. Cheriton School of Computer Science
Edward Zulkoski, PhD candidate
David R. Cheriton School of Computer Science
Thad Starner, School of Interactive Computing
Georgia Institute of Technology
Hicham El-Zein, PhD candidate
David R. Cheriton School of Computer Science
We present succinct data structures for one-dimensional color reporting and color counting problems. We are given a set of $n$ points with integer coordinates in the range $[1,m]$ and every point is assigned a color from the set $\{\,1,\ldots,\sigma\,\}$. A color reporting query asks for the list of distinct colors that occur in a query interval $[a,b]$ and a color counting query asks for the number of distinct colors in $[a,b]$.
Feng-Xuan Choo, PhD candidate
David R. Cheriton School of Computer Science
Chengnian Sun, Software Engineer
Google Inc., Mountain View, USA
Dakshita Khurana, PhD candidate
Department of Computer Science, UCLA
Can we provably immunize protocols against coordinated attacks on the internet? Can we verify that computation is performed correctly while preserving the privacy of underlying data? Can we enable mutually distrusting participants to securely compute on distributed private data?
These are some of the core challenges that lie at the heart of modern cryptography and secure protocol design.
Jennifer Widom
Frederick Emmons Terman Dean, School of Engineering
Fletcher Jones Professor, Computer Science and Electrical Engineering
Stanford University
Xi He, PhD candidate
Computer Science Department, Duke University
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.
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?
Hicham El-Zein, PhD candidate
David R. Cheriton School of Computer Science
Daniel Recoskie, PhD candidate
David R. Cheriton School of Computer Science
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.
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.
Please note: This seminar has been cancelled
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.
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.
