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Friday, February 3, 2023 2:00 pm - 5:00 pm EST (GMT -05:00)

PhD Defence • Data Systems | Data Management, Graph Processing, Parallel Systems • Systems and Algorithms for Dynamic Graph Processing

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

photo of Professor Khuzaima Daudjee
Thursday, December 15, 2022

ACM names Khuzaima Daudjee Distinguished Member

The Association for Computing Machinery has named Cheriton School of Computer Science Professor Khuzaima Daudjee a Distinguished Member for his outstanding scientific contributions to computing.

“On behalf of ACM and the Distinguished Member Committee, I am delighted that you are among the inductees honored with this designation and congratulate you on this well-deserved recognition,” wrote Geraldine Fitzpatrick, Chair of the ACM Distinguished Member Committee, in her letter to Professor Daudjee.

Thursday, January 26, 2023 9:30 am - 12:30 pm EST (GMT -05:00)

PhD Defence • Algorithms and Complexity | Computational Geometry • Algorithms for Geometric Facility Location: Centers in a Polygon and Dispersion on a Line

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

Tuesday, January 3, 2023 11:00 am - 12:00 pm EST (GMT -05:00)

Master’s Thesis Presentation • Systems and Networking • Adapting to Data Drift in Encrypted Traffic Classification Using Deep Learning

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

Wednesday, January 11, 2023 10:30 am - 12:00 pm EST (GMT -05:00)

DLS: Sheila McIlraith — Reward Machines: Formal Languages and Automata for Reinforcement Learning

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

Tuesday, January 10, 2023 9:00 am - 12:00 pm EST (GMT -05:00)

PhD Defence • Natural Language Processing • Novel Methods for Natural Language Modeling and Pretraining

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.

Friday, December 9, 2022 10:00 am - 11:00 am EST (GMT -05:00)

Master’s Thesis Presentation • Machine Learning • Prompt-tuning in Controlled Dialogue Generation

Please note: This master’s thesis presentation will take place online.

Runcheng (Irene) Liu, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Pascal Poupart

Friday, December 16, 2022 11:30 am - 12:30 pm EST (GMT -05:00)

Master’s Thesis Presentation • Software Engineering • Measuring the Performance of Code Produced with GitHub Copilot

Please note: This master’s thesis presentation will take place online. Please also note that the start time has changed from 11:00 to 11:30 a.m.

Daniel Erhabor, Master’s candidate
David R. Cheriton School of Computer Science

Supervisors: Professors Mei Nagappan, Samer Al-Kiswany

Tuesday, December 13, 2022 10:30 am - 11:30 am EST (GMT -05:00)

Seminar • Systems and Networking • Large-scale Environmental Sensing of Remote Areas on a Budget

Please note: This seminar will take place in DC 1304 and online.

Jörg Liebeherr, Professor
Department of Electrical and Computer Engineering, University of Toronto

By enabling large-scale in-situ environmental monitoring of remote areas, the Internet-of-Things (IoT) can play a crucial role in quantifying and responding to climate change. Sensing of uninhabited and many rural regions creates a need for inexpensive battery-powered IoT systems that can be deployed across large areas. Today, such systems are woefully unavailable.