Uploaded February 2024 | Updated September 2026, 2 weeks ago
Allen School graduate student Ather Sharif of the UW’s ACE Lab and DUB Group describes his work on VoxLens, a tool that makes online data visualizations accessible to people who use screen readers, and explains why UW is the best place to do accessibility research.
This video is closed captioned.
A version of this video with audio descriptions is available here: youtu.be/gtMoJAwW-Ms.
Allen School graduate student Ather Sharif of the UW’s ACE Lab and DUB Group describes his work on VoxLens, a tool that makes online data visualizations accessible to people who use screen readers, and explains why UW is the best place to do accessibility research.
This video is closed captioned.
A version of this video with audio descriptions is available here: youtu.be/gtMoJAwW-Ms.
![[Audio Descriptions] I Am CSE: Melanie Sclar](https://i.ytimg.com/vi/oXbk5FnpUnE/mqdefault.jpg "[Audio Descriptions] I Am CSE: Melanie Sclar
Melanie Sclar, a graduate student in the Allen School’s Natural Language Processing group, explains her work to advance the ability of large language models to engage in human-like reasoning known as “theory of mind” and why the Allen School is a big destination for researchers in AI.
This video is closed captioned.
A version of this video without audio descriptions is available here: https://youtu.be/OGQzgUVKwb0.")
![[ASL] Toward Total Scene Understanding for Autonomous Driving—Drago Anguelov (Waymo)](https://i.ytimg.com/vi/pK5ChzMsfE0/mqdefault.jpg "[ASL] Toward Total Scene Understanding for Autonomous Driving—Drago Anguelov (Waymo)
Ben Taskar Distinguished Memorial Lecture
Title: Toward Total Scene Understanding for Autonomous Driving
Speaker: Drago Anguelov (Waymo)
Host: Anat Caspi
Date: January 25, 2024
Abstract: Machine learning has proven to be a key ingredient in building a performant and scalable Autonomous Vehicle stack, spanning key capabilities such as perception, behavior prediction, planning and simulation and evaluation. I will describe recent Waymo research on performant ML models and architectures that help us handle the variety and complexity of real world environments. I will also discuss how progress in building Autonomous Driving agents can impact people with disabilities and cover some current open questions about how to further enhance embodied AI agent capabilities with ML.
Bio: Drago joined Waymo in 2018 to lead the Research team, which focuses on pushing the state of the art in autonomous driving using machine learning. Earlier in his career he spent eight years at Google; first working on 3D vision and pose estimation for StreetView, and later leading a research team which developed computer vision systems for annotating Google Photos. The team also invented popular methods such as the Inception neural network architecture, and the SSD detector, which helped win the Imagenet 2014 Classification and Detection challenges. Prior to joining Waymo, Drago led the 3D Perception team at Zoox.
This video is closed captioned.
A version of this video without ASL interpretation is available here: https://youtu.be/zCJO7ONdPZM.")
