Events

Filters
Export this event to calendar
iCal
RSS
RSS
Close X

Filter by:

Limit to events where the first date of the event:
Date range
Limit to events where the first date of the event:
Limit to events where the title matches:
Limit to events where the type is one or more of:
Limit to events tagged with one or more of:
Limit to events where the audience is one or more of:
Friday, December 11, 2020 12:30 pm - 12:30 pm EST (GMT -05:00)

Master’s Thesis Presentation • Machine Learning — Generalization on Text-based Games using Structured Belief Representations

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

Ashutosh Devendrakumar Adhikari, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Jimmy Lin

Friday, December 11, 2020 12:30 pm - 12:30 pm EST (GMT -05:00)

Master’s Research Paper Presentation • Software Engineering Investigating the Effectiveness of Pair Programming in Industrial Domains: A Systematic Literature Review

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

Alex Pawelczyk, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Daniel M. Berry

Monday, December 14, 2020 2:00 pm - 2:00 pm EST (GMT -05:00)

PhD Seminar • Artificial Intelligence — Approximating Dynamical Systems in Neural Networks: Constructing a Biologically Plausible Adaptive Filter Model of the Cerebellum

Please note: This PhD seminar will be given online.

Andreas Stöckel, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Chris Eliasmith

Thursday, January 14, 2021 11:30 am - 11:30 am EST (GMT -05:00)

Seminar • Software Engineering — Expanding the Reach of Fuzzing

Please note: This seminar will be given online.

Caroline Lemieux, Department of Computer Science
University of California, Berkeley

Software bugs are pervasive in modern software. As software is integrated into increasingly many aspects of our lives, these bugs have increasingly severe consequences, both from a security (e.g. Cloudbleed, Heartbleed, Shellshock) and cost standpoint. Fuzzing refers to a set of techniques that automatically find bug-triggering inputs by sending many random-looking inputs to the program under test.