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Friday, February 16, 2024 11:00 am - 12:00 pm EST (GMT -05:00)

Master’s Thesis Presentation • Data Systems • Cardinality Estimation in Streaming Graph Data Management Systems

Please note: This master’s thesis presentaton will take place in DC 1304.

Kerem Akillioglu, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor M. Tamer Özsu

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.

Monday, February 12, 2024 1:00 pm - 2:00 pm EST (GMT -05:00)

PhD Seminar • Bioinformatics • Anti-Cancer Peptides Identification and Activity Type Classification with Protein Sequence Pre-training

Please note: This PhD seminar will take place online.

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

Supervisor: Professor Bin Ma

Friday, February 9, 2024 4:00 pm - 5:00 pm EST (GMT -05:00)

Master’s Thesis Presentation • Artificial Intelligence • Traffic Rule Checking and Validation

Please note: This master’s thesis presentation will take place online.

Connor Stewart, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Krzysztof Czarnecki

Thursday, March 14, 2024 5:30 pm - 8:30 pm EDT (GMT -04:00)

PhD Defence • Artificial Intelligence | Affective Computing • Emotions and Context in Decision-making for a Socially Intelligent Agent

Please note: This PhD defence will take place online.

Aarti Malhotra, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Jesse Hoey

Wednesday, February 7, 2024 10:30 am - 11:30 am EST (GMT -05:00)

Seminar • Artificial Intelligence • Learning Generative Models from a Control Perspective for Scientific Discovery

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.