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 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
Please note: This master’s thesis presentation will take place online.
Joohan Lee, Master’s candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Bernard Wong, Khuzaima Daudjee
Please note: This seminar will take place in DC 1304 and virtually over Zoom.
Jennifer Sun, PhD candidate
Computing and Mathematical Sciences, California Institute of Technology
Please note: This PhD defence will take place online.
Anurag Murty Naredla, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Anna Lubiw
Please note: This master’s thesis presentation will take place in DC 2310.
Mahsa Seifikar, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Charles Clarke
Please note: This master’s thesis presentation will take place in DC 3317.
Omar Naman, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Samer Al-Kiswany
Please note: This seminar will take place in DC 1304 and virtually over Zoom.
Reid McIlroy-Young, PhD candidate
Department of Computer Science, University of Toronto
Please note: This seminar will take place in DC 1304 and virtually over Zoom.
Yuntian Deng, PhD candidate
Harvard John A. Paulson School of Engineering and Applied Sciences
Please note: This master’s thesis presentation will take place online.
Xiang Zhou (Danny) Kong, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Richard Cleve
Please note: This master’s thesis presentation will take place online.
Wael Al-Manasrah, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Samer Al-Kiswany
Please note: This master’s thesis presentation will take place online.
Ehsan Jahangirzadeh Soure, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jian Zhao
Please note: This seminar will take place in DC 1304 and virtually over Zoom.
Daniela Opocenska, Exchange Graduate Student
Please note: You must register to attend this online seminar.
Yang Cao, Associate Professor
Graduate School of Information Science and Technology, Hokkaido University
Please note: This PhD seminar will take place online.
Anurag Murty Naredla, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Anna Lubiw
Please note: This master’s thesis presentation will take place online.
Arash Moayyedi, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Raouf Boutaba
Please note: This PhD defence will take place online.
Ji Xin, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Jimmy Lin, Yaoliang Yu
Please note: This PhD defence will take place in DC 2310.
Xiang Fang, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Stephen Mann
Please note: This distinguished lecture will take place in DC 1302 as well as livestreamed over Zoom.
Sheila McIlraith
Professor, Department of Computer Science, University of Toronto
Canada CIFAR AI Chair, Vector Institute for Artificial Intelligence
Associate Director and Research Lead, Schwartz Reisman Institute for Technology and Society
Please note: This PhD defence will take place online.
Peng Shi, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jimmy Lin
Please note: This PhD defence will take place online.
He (Richard) Bai, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Ming Li
This thesis is about modeling text and speech sequences to achieve lower perplexity, better generation, and benefit downstream language tasks; specifically, we address the problem of modeling natural language sequences (text and speech) with Transformer-based language models. We present three new techniques that improve sequence modeling in different ways.
Please note: This master’s thesis presentation will take place online.
Navid Malekghaini, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Raouf Boutaba