Events

Wednesday, August 12, 2020 — 10:00 AM EDT

PhD Defence • Human-Computer Interaction — Human-AI Interaction in the Presence of Ambiguity

Please note: This PhD defence will be given online.

Mike Schaekermann, PhD candidate
David R. Cheriton School of Computer Science

Tuesday, August 18, 2020 — 11:00 AM EDT

Master’s Thesis Presentation • Software Engineering — On the Relationship Between the Developer’s Perceptible Ethnicity and the Evaluation of Contributions in GitHub

Please note: This master’s thesis presentation will be given online.

Reza Nadri, Master’s candidate
David R. Cheriton School of Computer Science

Context: Open Source Software (OSS) projects are typically the result of collective efforts performed by developers with different backgrounds. Although the quality of developers’ contributions should be the only factor influencing the evaluation of the contributions to OSS projects, recent studies have shown that diversity issues affect the acceptance or rejection of the contributions. 

Tuesday, August 18, 2020 — 1:00 PM EDT

PhD Defence • Algorithms and Complexity — Higher Order Random Walks, Local Spectral Expansion, and Applications

Please note: This PhD defence will be given online.

Vedat Levi Alev, PhD candidate
David R. Cheriton School of Computer Science

Wednesday, August 19, 2020 — 10:00 AM EDT

Master’s Thesis Presentation • Human-Computer Interaction — Comparing Smartphone Speech Recognition and Touchscreen Typing for Composition and Transcription

Please note: This master’s thesis presentation will be given online.

Margaret Foley, Master’s candidate
David R. Cheriton School of Computer Science

Thursday, September 17, 2020 — 11:00 AM EDT

PhD Seminar • Natural Language Processing — Where’s the Question? A Multi-channel Deep Convolutional Neural Network for Question Identification in Textual Data

Please note: This PhD seminar will be given online.

Georgios Michalopoulos, PhD candidate
David R. Cheriton School of Computer Science

In this study, we investigated the key characteristics exhibited by questions in medical narrative data (e.g., review logs) in order to uncover the most impactful variables on data quality issues during the data entry and review process of a real-word clinical system.

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