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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.

Please note: This PhD seminar will take place in DC 2310 (not in DC 2584 as originally advertised) and virtually over Zoom. 

Joshua Jung, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Jesse Hoey

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

Nicole Wein, Simons Postdoctoral Leader
DIMACS, Rutgers University

The size and complexity of today’s graphs present challenges that necessitate the discovery of new algorithms. One central area of research in this endeavor is computing and estimating distances in graphs. In this talk I will discuss two fundamental families of distance problems in the context of modern graphs: Diameter/Radius/Eccentricities and Hopsets/Shortcut Sets.