Please note: This PhD seminar will be given online.
Alister Liao, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Peter van Beek
Please note: This master’s thesis presentation will be given online.
Hossein Keshavarz, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Mei Nagappan
Please note: This master’s thesis presentation will be given online.
Saiyue Lyu, Master’s candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Mark Giesbrecht, Arne Storjohann
Please note: This master’s thesis presentation will be given online.
Soroosh Gholamizoj, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Bin Ma
Please note: This seminar will be given online.
Vahid Asadi, PhD candidate
David R. Cheriton School of Computer Science
We present a new framework for designing worst-case to average-case reductions. For a large class of problems, it provides an explicit transformation of algorithms running in time T that are only correct on a small (subconstant) fraction of their inputs into algorithms running in time O(T \log T) that are correct on all inputs.
Please note: This master’s research paper presentation will be given online.
Tamal Adhikary, Master’s candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Khuzaima Daudjee, Semih Salihoglu
Please note: This master’s thesis presentation will be given online.
Xinda Li, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Florian Kerschbaum
Please note: This master’s thesis presentation will be given online.
Teodor Alexandru Ionita, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Martin Karsten
Please note: This PhD seminar will be given online.
Charupriya Sharma, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Peter van Beek
Please note: This seminar will be given online.
Daniel Grier, Postdoctoral Researcher
Institute for Quantum Computing, University of Waterloo
Please note: This master’s thesis presentation will be given online.
Lizhe Chen, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Olga Veksler
In recent research, the self-supervised video representation learning methods have achieved improvement by exploring video’s temporal properties, such as playing speeds and temporal order. These works inspire us to exploit a new artificial supervision signal for self-supervised representation learning: the change of video playing speed.
Please note: This seminar will be given online.
Shahab Asoodeh, Assistant Professor
Department of Computing and Software, McMaster University
Please note: This master’s thesis presentation will be given online.
Chengcheng Hu, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jimmy Lin
Please note: This seminar will be given online.
Andrew Begel, Principal Researcher
Human-AI eXperiences Team, Microsoft Research
Assistive technologies help people with disabilities to adapt to a world that is not designed to accommodate them. My research aims to create the socio-technical infrastructure underpinning accessible technology and inclusive workplaces to provide opportunity, eliminate bias, and empower people with disabilities to fully engage and collaborate equitably with their non-disabled colleagues.
Come see six groups of fourth-year CS and SE students who took CS 497: Computing and Discrimination — a unique course offered for the first time this Winter by Computer Science Professors Dan Brown and Maura R. Grossman — as they showcase their final projects.
Learn more about this course from its instructors.
Please note: This seminar will be given online.
Hasti Seifi, Assistant Professor
Department of Computer Science, University of Copenhagen
Please note: This seminar will be given online.
Mohammadkazem (Kazem) Taram, PhD candidate
Department of Computer Science and Engineering, University of California, San Diego
The tension between security and performance has become more painful in recent years. In the context of processor architecture, we are observing a large influx of new attacks that appear regularly, each exploiting a crucial performance optimization, threatening to unwind decades of architectural gains.
Please note: This talk will be given online.
Smith Oduro-Marfo, University of Victoria
Please note: This PhD defence will be given online.
Fatema Tuz Zohora, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Ming Li
Please note: This seminar will be given online.
Alane Suhr, PhD candidate
Department of Computer Science, Cornell University
Please note: This master’s thesis presentation will be given online.
Rebecca Santos, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Gladimir Baranoski
Please note: This PhD seminar will be given in person.
Zhongwen (Rex) Zhang, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Yuri Boykov
Please note: This seminar will be given online.
Sepehr Assadi, Assistant Professor
Department of Computer Science, Rutgers University
Please note: This seminar will be given online.
Qian Zhang, Postdoctoral Researcher
Computer Science Department, University of California, Los Angeles
Emerging hardware is shaping the future of heterogeneous computing; however, the use of such extraordinary computing power is restricted to a few software developers with hardware expertise. My research designs software developer tools to democratize heterogeneous computing.