Please note: This PhD seminar will take place in DC 2310.
Ajay Singh, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Trevor Brown
In this presentation, we introduce Neutralization Based Reclamation (NBR), a novel technique that helps concurrent data structures with non-synchronized traversals to safely free objects. Additionally, we explore optimization possibilities, examining the efficiency of the technique.
Please note: This PhD seminar will take place in DC 3317.
Edward Lee, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Ondřej Lhoták
Reasoning about the use of external resources is an important aspect of many practical applications. Effect systems enable tracking such information in types, but at the cost of complicating signatures of common functions. Capabilities coupled with escape analysis offer safety and natural signatures, but are often overly coarse grained and restrictive.
Please note: This PhD seminar will take place online.
Nandan Thakur, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jimmy Lin
Please note: This seminar will take place in DC 1304.
Dinghuai Zhang, PhD candidate
Mila
Advancements in scientific discovery have always been at the forefront of human endeavor, particularly in complex domains such as molecule synthesis. The intrinsic challenges in these fields stem from two main factors: the vast and combinatorially complex high-dimensional search spaces, and the costly evaluation of scientific hypotheses. Therefore, leveraging machine learning offers a promising avenue to expedite the scientific discovery process.
Please note: This PhD seminar will take place online.
Ruixue Zhang, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Ming Li
Please note: This talk will take place in DC 1304 and online.
Alex Zhang, GFW Report
Please note: This seminar will take place in DC 1304.
Arun Jambulapati, Postdoctoral Researcher
Computer Science and Engineering, University of Michigan
Please note: This PhD seminar will take place online.
Kira Aveline Selby, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Pascal Poupart
Please note: This PhD seminar will take place online.
Aarti Malhotra, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jesse Hoey
Please note: This talk will take place in DC 1302 and online.
Yan Shvartzshnaider, Assistant Professor
Department of Electrical Engineering and Computer Science
Lassonde School of Engineering, York University
Please note: This seminar will take place in DC 1304.
Silvia Sellán, PhD candidate
Department of Computer Science, University of Toronto
Computer Graphics research has long been dominated by the interests of large film, television and social media companies, forcing other, more safety-critical applications (e.g., medicine, engineering, security) to repurpose Graphics algorithms originally designed for entertainment.
Please note: This seminar will take place in DC 1304.
Shiori Sagawa, PhD candidate
Department of Computer Science, Stanford University
Machine learning systems are powerful, but they can fail due to distribution shifts: mismatches in the data distribution between training and deployment. Distribution shifts are ubiquitous and have real-world consequences: models can fail on subpopulations (e.g., demographic groups) and on new domains unseen during training (e.g., new hospitals).
Please note: This PhD defence will take place in DC 3317 and online.
Nils Lukas, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Florian Kerschbaum
Please note: This PhD seminar will take place online.
Ryan Hancock, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Ali José Mashtizadeh
Please note: This master’s thesis presentation will take place online.
Seba Khaleel, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Samer Al-Kiswany
Please note: This PhD seminar will take place in DC 2310 and online.
Nils Lukas, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Florian Kerschbaum
Please note: This PhD seminar will take place in DC 1304.
Sheng-Chieh (Jack) Lin, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jimmy Lin
Contrastive learning is a commonly used technique to train an effective neural retrieval model; however, it requires much computation resources (i.e., multiple GPUs or TPUs).
Please note: This PhD seminar will take place in DC 3317 and online.
Robert Wang, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Lap Chi Lau
Please note: This seminar will take place in DC 1304.
Ibrahim Numanagić
Canada Research Chair in Data Science and Computational Biology
Assistant Professor, Department of Computer Science
University of Victoria
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 master’s thesis presentation will take place in DC 2310.
Prabhjot Singh, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Diogo Barradas
Although encrypted channels, like those provided by anonymity networks such as Tor, have been put into effect, network adversaries have proven their capability to undermine users’ browsing privacy through website fingerprinting attacks.
Please note: This master’s thesis presentation will take place online.
Fadhil Abubaker, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Khuzaima Daudjee
Please note: This seminar will take place in DC 1304 and online.
Chris Trevisan, Undergraduate student
David R. Cheriton School of Computer Science
Please note: This master’s thesis presentation will take place online.
Benyamin Jamialahmadi, Master’s candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Ali Ghodsi, Mohammad Kohandel
Please note: This PhD seminar will take place in DC 1304.
Xueguang Ma, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jimmy Lin
Neural retrieval systems have proven effective across a range of tasks and languages. However, creating fully zero-shot neural retrieval pipeline remains a challenge when relevance labels are not available.