Conferences, Lectures, & Seminars
Events for April
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CS Colloq: Jernej Barbic
Tue, Apr 14, 2009 @ 04:00 PM - 05:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Time: 4 PM - 5:30 PMLocation: SSL 150Talk Title: Real-time Deformable Objects: Graphics, Haptics, Sound, Control
Speaker: Jernej Barbic (MIT)
Host: Prof. Michael ZydaAbstract:
Real-time deformable objects are an exciting research area in computer graphics, with applications to computer games, movie industry, CAD/CAM, and virtual medicine. Deformable objects are well-understood in solid mechanics, however the standard simulation algorithms are too slow for interactive simulation with detailed geometry. How can we support real-time simulation on commodity workstations, while compromising physical correctness as little as possible?I will present reduced nonlinear deformable objects, a novel class of deformable objects obtained by applying statistical model reduction to finite element models of nonlinear elasticity. The idea is to replace the general degrees of freedom of a deformable object for a much smaller set of reduced degrees of freedom, thereby trading accuracy for speed. The reduced degrees of freedom incorporate geometric and material information, and can be chosen automatically from the first principles of continuum mechanics.I will also present a time-critical algorithm for deformable collision detection, and contact force computation between two reduced deformable (or rigid) objects with detailed geometry. The algorithm exploits reduction to achieve haptic update rates (1,000 Hz), and can be applied to deformable object path planning, virtual CAD/CAM, or other high update rate simulations in robotics.Reduction can also provide fast deformable models to drive real-time sound simulations. I will outline an algorithm where both the mechanical vibrations (deformations) that cause sound, and the sound propagation (wave equation) into the surrounding air for detailed geometries, are simulated at audio rates (44,100 Hz).Finally, I will discuss ongoing research on how model reduction can be used not only for fast forward simulation, but also for fast control.
Such control enables faster design of animations, and can provide directable real-time interaction in computer games.Bio:
Jernej Barbic received the computer science PhD degree from Carnegie Mellon University, in 2007. He is currently a postdoc in the MIT Computer Science and Artificial Intelligence Laboratory, The Stata Center, Cambridge, Massachusetts. His research interests include computer graphics, animation, real-time simulation, FEM deformable objects, haptic rendering of contact for geometrically rich scenarios, sound simulation, and model reduction and control of nonlinear systems.
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: CS Front Desk
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CS Colloq: Lingxiao Jiang
Wed, Apr 15, 2009 @ 04:00 PM - 05:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Time: 4 PM - 5:30 PMLocation: GFS 223Talk Title: Scalable Detection of Similar Code: Techniques and Applications
Speaker: Lingxiao Jiang (UC Davis)
Host: Prof. Nenad MedvidovicAbstract:
Similar code, commonly known as code clones, often occur in large programs because of various software development practices, such as copying and pasting code and n-version programming. Studies show that code duplication can incur higher maintenance costs and lead to subtle errors. Identifying similar code thus has many important applications, such as program understanding, refactoring, optimization, and bug detection. In this talk, I will present three pieces of my work on techniques and applications of scalable detection of both syntactic and semantic code clones.First, I will present Deckard, a scalable and accurate tree-based code clone detection technique. The key insight is to represent syntax trees of a program as structure-preserving characteristic vectors in the Euclidean space and employ efficient hashing algorithms to cluster these vectors. Our experiments showed that Deckard scales to billions of lines of code with few false positives. Also, Deckard is language-generic, applicable to any language with a formally specified grammar.Second, we will look at a novel application of Deckard to bug detection. In particular, I will describe a general notion of
context-based inconsistencies as strong indicators of clone-related bugs and the application of Deckard to identify such inconsistencies. Many previously unknown bugs in large projects such as the Linux kernel and Eclipse were discovered. These bugs exhibit diverse characteristics and are difficult to detect with any single previous bug detection technique.Third, I will describe EqMiner, the first scalable technique to detect functionally equivalent code for understanding code duplication at the semantic level. Inspired by Schwartz's randomized polynomial identity testing, EqMiner uses automated random testing to quickly determine the functional equivalence of arbitrary code fragments automatically extracted from a large program. Evaluated on the Linux kernel, EqMiner discovered many functionally equivalent code fragments that are syntactically different. I will conclude this talk by discussing future opportunities and challenges related to code clone detection.Bio:
Lingxiao Jiang is a Ph.D. candidate in Computer Science at University of California, Davis, where he specializes in software engineering. His current research focuses on techniques and tools for improving software quality and productivity. He received his M.S. in Applied Mathematics and B.S. in Information Science from Peking University, China.
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 223
Audiences: Everyone Is Invited
Contact: CS Front Desk
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CS Distinguished Lecture: Probabilistic Models for the Physical World
Thu, Apr 16, 2009 @ 03:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Prof. Daphne Koller (Stanford University)
Host: Prof. Fei ShaAbstract:
Over recent years, computer vision has made great strides towards annotating parts of an image with symbolic labels, such as object categories (things) or segment types (stuff). However, we are still far from the goal of providing a semantic description of an image, such as "a man, walking a dog on a sidewalk, carrying a backpack". In this talk, I will describe some projects we have done that attempt to use probabilistic models to move us closer towards the goal.The first part of the talk will present methods that use a more holistic scene analysis to improve our performance at core tasks such as object detection, segmentation, or 3D reconstruction. The second part of the talk will focus on finer-grained modeling of object shape, so as to allow us to annotate images with descriptive labels related to the object shape, pose, or activity (e.g., is a cheetah running or standing). These vision tasks rely on novel algorithms for core problems in machine learning and probabilistic models, such as efficient algorithms for probabilistic correspondence, transfer learning across related object classes for learning from sparse data, and more.Biography:
Daphne Koller is a Professor of Computer Science at Stanford University. Her main research focus is in developing and using machine learning and probabilistic methods to model and analyze complex systems, and she is particularly interested in using these techniques to understand biological systems and the world around us. Professor Koller is the author of over 100 refereed publications, which have appeared in venues that include Science, Nature Genetics, and the Journal of Games and Economic Behavior. She is a Fellow of the American Association for Artificial Intelligence, and has received a number of awards, including the Sloan Foundation Faculty Fellowship in 1996, the ONR Young Investigator Award in 1998, the Presidential Early Career Award for Scientists and Engineers (PECASE) from President Clinton in 1999, the IJCAI Computers and Thought Award in 2001, the Cox Medal for excellence in fostering undergraduate research at Stanford in 2003, the MacArthur Foundation Fellowship in 2004 and the first-ever ACM/Infosys award in 2008.Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: CS Colloquia
