Seminar

Please note: This PhD seminar will take place online.

Shaokai Wang, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Bin Ma

Please note: This half-hour seminar will take place in DC 1304.

Ahmed Alquraan, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Samer Al-Kiswany

Please note: This half-hour seminar will take place in DC 1304.

Emil Tsalapatis, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Ali Mashtizadeh

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

Sujaya Maiyya, Assistant Professor
Cheriton School of Computer Science

Please note: This PhD seminar will take place in DC 3102.

Mengxiao (Max) Zhang, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Chengnian Sun

Please note: This seminar will take place in M3 4206 and virtually.

Roei Tell, Assistant Professor
Department of Computer and Mathematical Sciences, University of Toronto

Please note: This PhD seminar will take place in DC 2102.

Andrew Na, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Justin Wan

Please note: This PhD seminar will take place in M3 4206 and online.

Cameron Seth, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Eric Blais

Please note: This PhD seminar will take place online.

Marvin Pafla, PhD candidate
David R. Cheriton School of Computer Science

Supervisors: Professors Kate Larson, Mark Hancock

With the rise of large language models (LLMs) like GPT, the field of eXplainable artificial intelligence (XAI) has exploded and produced a plethora of methods  (e.g., saliency-maps) to gain insight into deep neural nets. However, human-participant studies question the efficacy of these methods, particularly when the AI output is wrong.

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

Mrinal Kumar, Faculty member
School of Technology and Computer Science, Tata Institute of Fundamental Research