Seminar • Algorithms and Complexity • The Basis Number of 1-planar Graphs
Please note: This seminar will take place in DC 1302 and online.
Bobby Miraftab, Postdoctoral Researcher
Algorithms, Graphs, and Geometry Lab, Carleton University
Bobby Miraftab, Postdoctoral Researcher
Algorithms, Graphs, and Geometry Lab, Carleton University
Just months ago, an international team of four that includes Cheriton School of Computer Science Professor Craig Kaplan discovered a single shape that tiles the plane — an infinite, two-dimensional surface — in a pattern that can never be made to repeat.
The discovery mesmerized mathematicians, tiling enthusiasts and the public alike.
The shape, a 13-sided polygon they called “the hat,” is known to mathematicians as an aperiodic monotile or an “einstein,” the German words that mean “one stone.”
Andrew Na, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Justin Wan
Damien Masson, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Daniel Vogel, Géry Casiez, Sylvain Malacria
Ahmed Alquraan, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Samer Al-Kiswany
Bio: Ahmed is a 5th-year PhD student working with Samer Al-Kiswany. His work focuses on utilizing new data center technologies to build efficient and reliable data stores.
Kasper Hornbæk, Professor of Human-Centred Computing
Department of Computer Science, University of Copenhagen
Theory is supposed to be central to science. Yet the field of human-computer interaction (HCI) seems confused about what theory is and what to do with it.
Researchers at the Cheriton School of Computer Science have discovered a method of attack that can successfully bypass voice authentication security systems with up to a 99% success rate after only six tries.
Voice authentication — which allows companies to verify the identity of their clients via a supposedly unique voiceprint — has increasingly been used in remote banking, call centres and other security-critical scenarios.
Bailey Kacsmar, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Florian Kerschbaum
Privacy in machine learning holds great promise for enabling organizations to analyze data they and their partners hold while maintaining data subjects’ privacy.
Ishaq Aden-Ali, PhD candidate
Electrical Engineering and Computer Sciences
University of California, Berkeley
Shadi Ghasemitaheri, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Lukasz Golab
Accurate forest monitoring data are essential for understanding and conserving forest ecosystems. However, the remoteness of forests and the scarcity of ground truth make it hard to identify data quality issues.