Thesis defence

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 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 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 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 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 online.

Navid Malekghaini, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Raouf Boutaba

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.