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Wednesday, February 7, 2024 12:30 pm - 1:30 pm EST (GMT -05:00)

PhD Seminar • Information Retrieval | Natural Language Processing | Deep Learning • Heterogenous Benchmarking across Domains and Languages: The Key to Enable Meaningful Progress in IR Research

Please note: This PhD seminar will take place online.

Nandan Thakur, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Jimmy Lin

Wednesday, February 7, 2024 2:00 pm - 3:00 pm EST (GMT -05:00)

PhD Seminar • Programming Languages • Effects, Capabilities, and Boxes: From Scope-based Reasoning to Type-based Reasoning and Back

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.

Friday, February 9, 2024 1:30 pm - 2:30 pm EST (GMT -05:00)

PhD Seminar • Data Systems | Programming Languages • Reclaiming Memory in Concurrent Data Structures: A Neutralization-Based Approach

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.

Wednesday, February 14, 2024 10:30 am - 11:30 am EST (GMT -05:00)

Seminar • Bioinformatics • Applied Biological Sequence Analysis with a Theoretical Flavour

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

Jim Shaw, PhD candidate
Department of Mathematics, University of Toronto

DNA is life’s instruction manual, but mathematically, DNA is simply a string over an alphabet of four letters. DNA can now easily be read into a computer, and the associated string-processing algorithms are being leveraged by biologists for exciting discoveries. However, this has created a flood of data in the petabytes, requiring modern and faster tools.