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Conferences, Lectures, & Seminars
Events for January
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CS Colloquium: Odest Chadwicke Jenkins (University of Michigan) - Semantic Robot Programming... and Maybe Making the World a Better Place
Tue, Jan 19, 2021 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Odest Chadwicke Jenkins, University of Michigan
Talk Title: Semantic Robot Programming... and Maybe Making the World a Better Place
Series: Computer Science Colloquium
Abstract: The visions of interconnected heterogeneous autonomous robots in widespread use are a coming reality that will reshape our world. Similar to "app stores" for modern computing, people at varying levels of technical background will contribute to "robot app stores" as designers and developers. However, current paradigms to program robots beyond simple cases remains inaccessible to all but the most sophisticated of developers and researchers. In order for people to fluently program autonomous robots, a robot must be able to interpret user instructions that accord with that user's model of the world. The challenge is that many aspects of such a model are difficult or impossible for the robot to sense directly. We posit a critical missing component is the grounding of semantic symbols in a manner that addresses both uncertainty in low-level robot perception and intentionality in high-level reasoning. Such a grounding will enable robots to fluidly work with human collaborators to perform tasks that require extended goal-directed autonomy.
I will present our efforts towards accessible and general methods of robot programming from the demonstrations of human users. Our recent work has focused on Semantic Robot Programming (SRP), a declarative paradigm for robot programming by demonstration that builds on semantic mapping. In contrast to procedural methods for motion imitation in configuration space, SRP is suited to generalize user demonstrations of goal scenes in workspace, such as for manipulation in cluttered environments. SRP extends our efforts to crowdsource robot learning from demonstration at scale through messaging protocols suited to web/cloud robotics. With such scaling of robotics in mind, prospects for cultivating both equal opportunity and technological excellence will be discussed in the context of broadening and strengthening Title IX and Title VI.
Register in advance for this webinar at:
https://usc.zoom.us/webinar/register/WN_qbP7OfXwQoqG2E5QQGhWJA
After registering, attendees will receive a confirmation email containing information about joining the webinar.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Odest Chadwicke Jenkins, Ph.D., is a Professor of Computer Science and Engineering and Associate Director of the Robotics Institute at the University of Michigan. Prof. Jenkins earned his B.S. in Computer Science and Mathematics at Alma College (1996), M.S. in Computer Science at Georgia Tech (1998), and Ph.D. in Computer Science at the University of Southern California (2003). He previously served on the faculty of Brown University in Computer Science (2004-15). His research addresses problems in interactive robotics and human-robot interaction, primarily focused on mobile manipulation, robot perception, and robot learning from demonstration. His research often intersects topics in computer vision, machine learning, and computer animation. Prof. Jenkins has been recognized as a Sloan Research Fellow and is a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE). His work has also been supported by Young Investigator awards from the Office of Naval Research (ONR), the Air Force Office of Scientific Research (AFOSR) and the National Science Foundation (NSF). Prof. Jenkins is currently serving as Editor-in-Chief for the ACM Transactions on Human-Robot Interaction. He is a Fellow of the American Association for the Advancement of Science, and Senior Member of the Association for Computing Machinery and the Institute of Electrical and Electronics Engineers. He is an alumnus of the Defense Science Study Group (2018-19).
Host: Heather Culbertson and Maja Mataric
Webcast: https://usc.zoom.us/webinar/register/WN_qbP7OfXwQoqG2E5QQGhWJALocation: Online Zoom Webinar
WebCast Link: https://usc.zoom.us/webinar/register/WN_qbP7OfXwQoqG2E5QQGhWJA
Audiences: Everyone Is Invited
Contact: Computer Science Department
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CS Colloquium: Allison Okamura (Stanford University) - Wearable Haptic Devices for Ubiquitous Communication
Thu, Jan 21, 2021 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Allison Okamura, Stanford University
Talk Title: Wearable Haptic Devices for Ubiquitous Communication
Series: Computer Science Colloquium
Abstract: Haptic devices allow touch-based information transfer between humans and intelligent systems, enabling communication in a salient but private manner that frees other sensory channels. For such devices to become ubiquitous, their physical and computational aspects must be intuitive and unobtrusive. The amount of information that can be transmitted through touch is limited in large part by the location, distribution, and sensitivity of human mechanoreceptors. Not surprisingly, many haptic devices are designed to be held or worn at the highly sensitive fingertips, yet stimulation using a device attached to the fingertips precludes natural use of the hands. Thus, we explore the design of a wide array of haptic feedback mechanisms, ranging from devices that can be actively touched by the fingertips to multi-modal haptic actuation mounted on the arm. We demonstrate how these devices are effective in virtual reality, human-machine communication, and human-human communication.
Register in advance for this webinar at:
https://usc.zoom.us/webinar/register/WN_u9NWPx3ZS2GK70dtN6-1ZA
After registering, attendees will receive a confirmation email containing information about joining the webinar.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Allison M. Okamura received the BS degree from the University of California at Berkeley and the MS and PhD degrees from Stanford University, all in mechanical engineering. She is currently Professor in the mechanical engineering department at Stanford University, with a courtesy appointment in computer science. She is an IEEE Fellow and Editor-in-Chief of the journal IEEE Robotics and Automation Letters. Her awards include the 2020 IEEE Engineering in Medicine and Biology Society Technical Achievement Award, 2019 IEEE Robotics and Automation Society Distinguished Service Award, and 2016 Duca Family University Fellow in Undergraduate Education. Her academic interests include haptics, teleoperation, virtual environments and simulators, medical robotics, neuromechanics and rehabilitation, and soft robotics. She is passionate about engineering education and diversifying STEM. Outside academia, she enjoys spending time with her husband and two children, running, and playing ice hockey. For more information about her research, please see the Collaborative Haptics and Robotics in Medicine (CHARM) Laboratory website: http://charm.stanford.edu.
Host: Heather Culbertson and Maja Mataric
Webcast: https://usc.zoom.us/webinar/register/WN_u9NWPx3ZS2GK70dtN6-1ZALocation: Online Zoom Webinar
WebCast Link: https://usc.zoom.us/webinar/register/WN_u9NWPx3ZS2GK70dtN6-1ZA
Audiences: Everyone Is Invited
Contact: Computer Science Department
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CS Distinguished Lecture: Dan Roth (University of Pennsylvania) - It's Time for Reasoning
Tue, Jan 26, 2021 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dan Roth, University of Pennsylvania
Talk Title: It's Time for Reasoning
Series: Computer Science Distinguished Lecture Series
Abstract: The fundamental issue underlying natural language understanding is that of semantics -“ there is a need to move toward understanding natural language at an appropriate level of abstraction in order to support natural language understanding and communication with computers.
Machine Learning has become ubiquitous in our attempt to induce semantic representations of natural language and support decisions that depend on it; however, while we have made significant progress over the last few years, it has focused on classification tasks for which we have large amounts of annotated data. Supporting high level decisions that depend on natural language understanding is still beyond our capabilities, partly since most of these tasks are very sparse and generating supervision signals for it does not scale.
I will discuss some of the challenges underlying reasoning -“ making natural language understanding decisions that depend on multiple, interdependent, models, and exemplify it using the domain of Reasoning about Time, as it is expressed in natural language.
Register in advance for this webinar at:
https://usc.zoom.us/webinar/register/WN_DbjnVhUcQG-HIHt6eLQCYQ
After registering, attendees will receive a confirmation email containing information about joining the webinar.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Dan Roth is the Eduardo D. Glandt Distinguished Professor at the Department of Computer and Information Science, University of Pennsylvania, and a Fellow of the AAAS, the ACM, AAAI, and the ACL.
In 2017 Roth was awarded the John McCarthy Award, the highest award the AI community gives to mid-career AI researchers. Roth was recognized "for major conceptual and theoretical advances in the modeling of natural language understanding, machine learning, and reasoning."
Roth has published broadly in machine learning, natural language processing, knowledge representation and reasoning, and learning theory, and has developed advanced machine learning based tools for natural language applications that are being used widely. Until February 2017 Roth was the Editor-in-Chief of the Journal of Artificial Intelligence Research (JAIR).
Roth has been involved in several startups; most recently he was a co-founder and chief scientist of NexLP, a startup that leverages the latest advances in Natural Language Processing (NLP), Cognitive Analytics, and Machine Learning in the legal and compliance domains. NexLP was sold to Reveal in 2020.
Prof. Roth received his B.A Summa cum laude in Mathematics from the Technion, Israel, and his Ph.D. in Computer Science from Harvard University in 1995.
Host: Xiang Ren
Webcast: https://usc.zoom.us/webinar/register/WN_DbjnVhUcQG-HIHt6eLQCYQLocation: Online Zoom Webinar
WebCast Link: https://usc.zoom.us/webinar/register/WN_DbjnVhUcQG-HIHt6eLQCYQ
Audiences: Everyone Is Invited
Contact: Computer Science Department
