Events

Please note: This PhD seminar will take place in DC 1304 and virtually over Zoom.

Yen-Ting (Allen) Yeh, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Daniel Vogel

Steven Jeromy Carriere
Senior Vice President, Engineering, Datadog

“Scale” is a complex notion that encompasses some easy-ish-to-measure factors such as the resource footprint or transaction rate of a system, but also substantially more subtle considerations such as service dependencies that influence the cost of making changes and team behaviors that affect how long it takes to resolve a production issue.

Please note: This seminar will take place in DC 1302 and virtually over Zoom.

Justin Zobel, Redmond Barry Distinguished Professor
Pro Vice-Chancellor, Graduate & International Research
School of Computing and Information Systems, University of Melbourne

Please note: This PhD seminar will take place online.

Zhiying Jiang, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Jimmy Lin

Please note: This PhD seminar will take place in DC 1304 and virtually over Zoom.

Kaiyu (Kevin) Wu, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor J. Ian Munro

We present succinct distance oracles for (unweighted) interval graphs and related classes of graphs, using a novel succinct data structure for ordinal trees that supports the mapping between preorder (i.e., depth-first) ranks and level-order (breadth-first) ranks of nodes in constant time.

Please note: This PhD seminar will take place in DC 1304 and virtually over Zoom.

Damien Masson, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Daniel Vogel

Please note: This PhD defence will take place online.

Khaled Ammar, PhD candidate
David R. Cheriton School of Computer Science

Supervisors: Professors M. Tamer Özsu, Semih Salihoglu

Please note: This seminar will take place in DC 1304 and virtually over Zoom.

Victor Zhong, PhD candidate
Natural Language Processing Group, University of Washington

Traditional machine learning systems are trained on vast quantities of annotated data or experience. These systems often do not generalize to new, related problems that emerge after training, such as conversing about new topics or interacting with new environments.

Please note: This seminar will take place in DC 1304 and virtually over Zoom.

Mariam Guizani, PhD candidate
Department of Electrical Engineering and Computer Science, Oregon State University

Diversity and Inclusion in Open-Source Software (OSS) has a significant impact on the OSS ecosystem and society. The low state of diversity and inclusion in OSS (e.g., women participation ranging from 1.5% to 11%) has unfortunate effects on OSS projects, individual contributors, and society.

Please note: This seminar will take place in DC 1304 and virtually over Zoom.

Jingbo Wang, PhD candidate
Department of Computer Science, University of Southern California

Security, robustness, and fairness are all important non-functional properties of critical systems, such as software applications in autonomous driving, healthcare, and finance. Unlike functional correctness, which has been the subject of extensive research, techniques that can formally guarantee these non-functional properties are still severely lacking.