Xiao-Bo Li, PhD candidate
David R. Cheriton School of Computer Science
Xiao-Bo Li, PhD candidate
David R. Cheriton School of Computer Science
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
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.
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.
William Callaghan, Master’s candidate
David R. Cheriton School of Computer Science
Aayush Rajasekaran, Master's candidate
David R. Cheriton School of Computer Science
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.
Hicham El-Zein, PhD candidate
David R. Cheriton School of Computer Science
Magnus Madsen
Aalborg University, Denmark
Most software contains bugs, unintended behavior that causes the program to misbehave or crash. Developers wish to avoid bugs, but are easily led astray by the complexity of modern programming languages. How can we help them? A possible solution is to develop program analysis techniques that can automatically reason about the behavior of programs and pinpoint potential problems.