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Colloquia

Fall 2014 Colloquia

Check back soon for more information on the computer science seminar series. Unless otherwise noted, the seminars now meet on Mondays at 3pm in Stanley Thomas 302. If you would like to receive notices about upcoming seminars, you can subscribe to the announcement listserv.

September 15

Packing and Stacking: Algorithms and Complexity

Helmut Alt Freie Universität Berlin

Abstract: We consider the problem of placing geometric objects in two dimensions so that they occupy an area as small as possible. "Packing" means that the objects may overlap, "stacking" that they may not. Packing has important applications, e.g., in the clothing and steel industries. Reasonably efficient algorithms can be found if the number of objects to be placed is constant. If not, even the most simple variants of the problem are NP-hard, so it is important to find efficient approximation algorithms. In the talk, we will give an introduction into the problem, present its numerous variants, demonstrate its computational complexity, and present some approximation algorithms.


About the Speaker: Helmut Alt is a professor of computer science at Freie Universität Berlin, Germany. He obtained his doctorate from Universität des Saarlandes in 1976. He taught computer science at Universität Kaiserslautern, the Pennsylvania State University, Hochschule Hildesheim, and, since 1986, at Freie Universität. Dr. Alt's research is concerned with algorithms and data structures, in particular computational geometry, with an emphasis on geometric algorithms for pattern and shape comparison and analysis.
October 6

The New 'Shape' of Data and Its Application in Interactive Data Exploration

Chao Chen Rutgers University

Abstract: Biomedical imaging informatics has been rapidly developed in the past few decades. While many models used prior information of the shape of the target object/data, recently, many new applications arose in which the shape-prior is not available. These 'shapeless' data include the neuron structures from Electron Microscopy (EM) images and the fine trabeculae muscle structures within the human heart. When working with the macroscopic level, we face challenges in capturing the shape of data of extremely high dimension.

In this talk, I will discuss how to explore new 'shapes' of these data. To start with, we show that the topology of the data, e.g., handles and connected components, could be very useful priors. Furthermore, we show that the topographical landscape, namely, the mountains and valleys, of the data can help us in data acquisition and analysis.

The new shapes of data that we present also provide new opportunities for interactive exploration. In EM images, human interaction is inevitable due to the extremely high expectation of the accuracy of the extracted structure. In high dimensional data analysis, showing the shape of the data enables domain expert to explore the data and invent new hypothesis to verify.

Results in this talk have been published in NIPS, IPMI, MICCAI and CVPR.


About the Speaker: Dr. Chen obtained his PhD degree from Rensselaer Polytechnic Institute. He worked on computational topology with Prof. Herbert Edelsbrunner. Currently he is working with Prof. Dimitris Metaxas at Rutgers University on biomedical imaging informatics and machine learning.
October 13

Computational Thinking

Jeannette Wing Microsoft Research


Please note that this event will be held at Freeman Auditorium at 3:00 p.m. The Department of Computer Science is co-hosting this event with the Newcomb College Institute as part of the Dorothy K. Daspit Lecture Series.

Abstract: My vision for the 21st Century: Computational thinking will be a fundamental skill used by everyone in the world. To reading, writing, and arithmetic, we should add computational thinking to every child's analytical ability. Computational thinking involves solving problems, designing systems, and understanding human behavior by drawing on the concepts fundamental to computer science. Thinking like a computer scientist means more than being able to program a computer. It requires the ability to abstract and thus to think at multiple levels of abstraction. In this talk I will give many examples of computational thinking, argue that it has already influenced other disciplines, and promote the idea that teaching computational thinking can not only inspire future generations to enter the field of computer science, but benefit people in all fields.


About the Speaker: Jeannette M. Wing is Corporate Vice President, Microsoft Research. She joined MSR in 2013 from Carnegie Mellon University where she was President's Professor of Computer Science and twice served as the Head of the Computer Science Department. From 2007-2010 she was the Assistant Director of the Computer and Information Science and Engineering Directorate at the National Science Foundation.
October 20

FDR into The Cloud


A.W
. Roscoe University of Oxford

Abstract: In this talk I will report on a successful extension to the CSP refinement checker FDR3 that permits it to run on clusters of machines. FDR3 is able to scale linearly up to clusters of 64 16-core machines (i.e. 1024 cores), achieving an overall speed-up of over 1000 relative to the sequential case. This speed-up was observed both on dedicated supercomputer facilities, but more notably, also on a commodity cloud computing provider. This enhancement has enabled the verification of a system of 1012 states, which we believe to be the largest refinement check ever attempted by several orders of magnitude.

About the Speaker:

Bill Roscoe
Bill Roscoe is Professor of Computing Science at the University of Oxford, UK, and a Fellow of the Royal Society of Engineering. Bill is the foremost expert on the process calculus CSP, which was devised by Tony Hoare and two of his students - Bill and Steve Brookes. FDR is the failures-divergences refinement model checker designed for CSP processes; it was designed and implemented by Bill and his team. CSP and FDR are used to design, specify, refine and verify concurrent processes, and they have been applied effectively in a broad range of areas, from VLSI design to security protocol verification. Bill recently stepped down as the Head of the Computer Science department at Oxford, after two terms during which he oversaw the rapid growth and expansion of the department.






October 27

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Abstract: TBA.

November 3

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November 13

Sampling-Based Motion Planning: From Intelligent CAD to Crowd Simulation to Protein Folding

Nancy M. Amato tEXAS a & m UNIVERSITY


This event will be held on Thursday, 11/13/2014, at 11:00 a.m. in Stanley Thomas, Room 102. Please note the special weekday and time for this event. We are inviting her as part of the ACM Distinguished Speakers Program:

Abstract: Motion planning arises in many application domains such as computer animation (digital actors), mixed reality systems and intelligent CAD (virtual prototyping and training), and even computational biology and chemistry (protein folding and drug design). Surprisingly, one type of sampling-based planner, the probabilistic roadmap method (PRM), has proven effective on problems from all these domains.

In this talk, we describe the PRM framework and give an overview of some PRM variants developed in our group. We describe in more detail our work related to virtual prototyping, crowd simulation, and protein folding. For virtual prototyping, we show that in some cases a hybrid system incorporating both an automatic planner and haptic user input leads to superior results. For crowd simulation, we describe PRM-based techniques for pursuit evasion, evacuation planning and architectural design. Finally, we describe our application of PRMs to simulate molecular motions, such as protein and RNA folding. More information regarding our work, including movies, can be found at http://parasol.tamu.edu/~amato/.

About the Speaker:


Nancy M. Amato is Unocal Professor of Computer Science and Engineering at Texas A&M University where she co-directs the Parasol Lab. Her main areas of research focus are motion planning and robotics, computational biology and geometry, and parallel and distributed computing. She has graduated 16 PhD students, with all but two going on to careers in academia or research labs, 25 masters students, and has worked with more than 100 undergraduates and 10 high school students.

Amato received undergraduate degrees in Mathematical Sciences and Economics from Stanford University, and M.S. and Ph.D. degrees in Computer Science from UC Berkeley and the University of Illinois, respectively. She was an AT&T Bell Laboratories PhD Scholar, received an NSF CAREER Award, is an ACM Distinguished Speaker, and was an IEEE RAS Distinguished Lecturer (2006-2007). Amato is program chair for IEEE ICRA 2015 and RSS 2016, and served as the Editor-in-Chief of the IEEE/RSJ IROS CPRB (2011-2013). She is a member (elected) of the CRA Board of Directors (2014-2017), is co-Chair of CRA-W (2014-2017), was co-chair of the NCWIT Academic Alliance (2009-2011), and is a member of the CRA-E and the CDC.

Amato received the 2014 CRA Haberman Award, the inaugural NCWIT Harrold/Notkin Research and Graduate Mentoring Award in 2014, the IEEE HP/Harriet Rigas Award in 2013, a Texas A&M AFS university-level teaching award in 2011, and the Unterberger Award for Outstanding Service to Honors Education at Texas A&M in 2013. She is a AAAS Fellow and an IEEE Fellow.
November 17

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Abstract: TBA.

November 24

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December 1

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School of Science and Engineering, 201 Lindy Boggs Center, New Orleans, LA 70118 504-865-5764 sse@tulane.edu