Seminar

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 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.

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 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.