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Events for March 01, 2022
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CS Colloquium: Oded Stein (MIT) - Mathematical Foundations of Robust Geometry and Fabrication
Tue, Mar 01, 2022 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Oded Stein, MIT
Talk Title: Mathematical Foundations of Robust Geometry and Fabrication
Series: CS Colloquium
Abstract: Current geometry methods for creating and manipulating shapes on computers can sometimes be unreliable and fail unpredictably. Such failures make geometry tools hard to use, prevent non-experts from creating geometry on their computers, and limit the use of geometry methods in domains where reliability is critical. We will discuss my recent efforts in proving when existing methods work as intended, my work in making methods more robust to imperfect input, my work in the creation of new reliable tools with mathematical guarantees, and my future efforts towards a reliable geometry pipeline.
When used for computational fabrication, geometry methods can be expensive, finicky, and require a controlled environment. I will show how simple and economical manufacturing techniques can be used for computational fabrication by exploiting the geometric constraints inherent in specific materials and fabrication methods. We will take a look at how I create geometric tools to design for constrained fabrication techniques, and discuss how computational fabrication can be made both economical as well as accessible in difficult environments.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Oded Stein is a postdoc at MIT at the geometric data processing group. He obtained his MSc from ETH Zurich in 2015, and his PhD from Columbia University in 2020.
Oded is interested in geometry, computer graphics, and applied mathematics. He works on smoothness energies, partial differential equations, discretization of geometric quantities, and their applications to computer graphics and digital fabrication.
Host: Jernej Barbic
Location: Olin Hall of Engineering (OHE) - 132
Audiences: By invitation only.
Contact: Assistant to CS chair
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CS Colloquium: Amy Ousterhout (UC Berkeley) - Optimizing CPU Efficiency and Tail Latency in Datacenters
Tue, Mar 01, 2022 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Amy Ousterhout , UC Berkeley
Talk Title: Optimizing CPU Efficiency and Tail Latency in Datacenters
Series: CS Colloquium
Abstract: The slowing of Moore's Law and increased concerns about the environmental impacts of computing are exerting pressure on datacenter operators to use resources such as CPUs and memory more efficiently. However, it is difficult to improve efficiency without degrading the performance of applications.
In this talk, I will focus on CPU efficiency and how we can increase efficiency while maintaining low tail latency for applications. The key innovation is to reallocate cores between applications on the same server very quickly, every few microseconds. First I will describe Shenango, a system design that makes such frequent core reallocations possible. Then I will show how policy choices for core reallocation and load balancing impact CPU efficiency and tail latency, and present the policies that yield the best combination of both.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Amy is a postdoctoral researcher in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. She received her PhD in Computer Science from MIT and her BSE in Computer Science from Princeton University. Her research is on operating systems and distributed systems, and focuses on improving the efficiency, performance, and usability of applications in datacenters. She is a recipient of a Jacobs Presidential Fellowship at MIT, an NSF Graduate Research Fellowship, and a Hertz Foundation Fellowship.
Host: Barath Raghavan
Audiences: By invitation only.
Contact: Assistant to CS chair
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CS Colloquium: Dmitry Berenson (University of Michigan) - Learning Where to Trust Unreliable Dynamics Models for Motion Planning and Manipulation
Tue, Mar 01, 2022 @ 04:15 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dmitry Berenson, University of Michigan
Talk Title: Learning Where to Trust Unreliable Dynamics Models for Motion Planning and Manipulation
Series: Computer Science Colloquium
Abstract: **New time: 4:15pm-5:20pm, SGM 124**
The world outside our labs seldom conforms to the assumptions of our models. This is especially true for dynamics models used in control and motion planning for complex high-DOF systems like deformable objects. We must develop better models, but we must also accept that, no matter how powerful our simulators or how big our datasets, our models will sometimes be wrong. This talk will present our recent work on using unreliable dynamics models for motion planning and manipulation. Given a dynamics model, our methods learn where that model can be trusted given either batch data or online experience. These approaches allow imperfect dynamics models to be useful for a wide range of tasks in novel scenarios, while requiring much less data than baseline methods. This data-efficiency is a key requirement for scalable and flexible motion planning and manipulation capabilities.
Prof. Dmitry Berenson will give his talk in person at SGM 124 and we will also host the talk over Zoom.
Register in advance for this webinar at:
https://usc.zoom.us/webinar/register/WN_prfowdXjR7iOn1mPLTnXog
After registering, attendees will receive a confirmation email containing information about joining the webinar.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Dmitry Berenson is an Associate Professor in Electrical Engineering and Computer Science and the Robotics Institute at the University of Michigan, where he has been since 2016. Before coming to University of Michigan, he was an Assistant Professor at WPI (2012-2016). He received a BS in Electrical Engineering from Cornell University in 2005 and received his Ph.D. degree from the Robotics Institute at Carnegie Mellon University in 2011, where he was supported by an Intel PhD Fellowship. He was also a post-doc at UC Berkeley (2011-2012). He has received the IEEE RAS Early Career Award and the NSF CAREER award. His current research focuses on robotic manipulation, robot learning, and motion planning.
Host: Stefanos Nikolaidis
Webcast: https://usc.zoom.us/webinar/register/WN_prfowdXjR7iOn1mPLTnXogLocation: Seeley G. Mudd Building (SGM) - 124
WebCast Link: https://usc.zoom.us/webinar/register/WN_prfowdXjR7iOn1mPLTnXog
Audiences: Everyone Is Invited
Contact: Computer Science Department
