17 OCTOBER 2011
Speaker: Saman Amarasinghe, Professor, Department of Electrical Engineering and Computer Science, MIT
Title: PetaBricks: A Language and Compiler Based on Autotuning
Host School: NCSU
NCSU Host: Frank Mueller (mueller at cs.ncsu.edu)
Duke Host: Dan Corin (corin at ee.duke.edu)
UNC Host: Ketan Mayer-Patel (kmp at cs.unc.edu)

YouTube video of talk

Abstract:
The era of exponential improvement of processor performance without any programmer effort is over. Multicores put the onus of taking advantage of Moore’s law on the programmers. While architects have known how to build parallel processors for over a half a century, programmers’ inability to create scalable parallel programs has been the main stumbling block in mainstream use of parallelism. In the first part of the talk I will discuss the path to multicores, address why scalable parallel programming has been such a difficult problem to solve and speculate on our ability to crack it this time around.

Next I will discuss, the Petabricks Project, which attempts to alleviate part of this heavy burden we are placing on programmers. For a multicore application to keep-up with the exponential growth of Moore’s Law requires the algorithms in the application to efficiently scale from small to large numbers of cores. It is observed that for a given problem, different algorithms provide the best solution at different levels of parallelism. However, currently there is no simple way for the programmer to express or the compiler to take advantage of all the available algorithmic choices for a problem. PetaBricks is a new implicitly parallel language and compiler where having multiple implementations of multiple algorithms to solve a problem is the natural way of programming.  The PetaBricks compiler autotunes programs by making the best fine-grained algorithmic choices. Choices also include different automatic parallelization techniques, data distributions, algorithmic parameters, transformations, and blocking.

Biography:
Saman P. Amarasinghe is a Professor in the Department of Electrical Engineering and Computer Science. He leads the Commit compiler group. His research interests are in discovering novel approaches to improve the performance of modern computer systems and make them more secure without unduly increasing the complexity faced by the end users, application developers, compiler writers, or computer architects. Saman received his BS in Electrical Engineering and Computer Science from Cornell University in 1988, and his MSEE and Ph.D from Stanford University in 1990 and 1997, respectively.

http://people.csail.mit.edu/saman/
31 OCTOBER 2011
Speaker: Ravi Sandhu, Professor, Department of Computer Science, University of Texas at San Antonio
Title: The Data and Application Security and Privacy (DASPY) Challenge
Host School: NCSU
NCSU Host: Peng Ning (pning at ncsu.edu)
Duke Host: Landon Cox (lpcox at cs.duke.edu)
UNC Host: Mike Reiter (reiter at cs.unc.edu)

YouTube video of talk

Abstract:
TBA

Biography:
Ravi Sandhu is the Executive Director and Chief Scientist of the Institute for Cyber Security (ICS) at the University of Texas at San Antonio. He is also the Lutcher Brown Endowed Chair in Cyber Security, Professor of Computer Science, and has courtesy appointments in the Department of Electrical and Computer Engineering and Information Systems and Technology Management. He is the editor-in-chief of IEEE Transactions on Dependable and Secure Computing (TDSC), and founder and general chair of the ACM Conference on Data and Application Security and Privacy (CODASPY).

http://profsandhu.com/index.html

 

7 NOVEMBER 2011
Speaker: Victor Lesser, Professor, Department of Computer Science, University of Massachusetts at Amherst
Title: The CASA Severe Weather Radar Detection and Tracking System
Host School: NCSU
NCSU Host: Munindar Singh (singh at ncsu.edu)
Duke Host: Ron Parr (parr at cs.duke.edu)
UNC Host: Montek Singh (montek at cs.unc.edu)

YouTube video of talk

Abstract:
TBA

Biography:
Victor R. Lesser received his B.A. in Mathematics from Cornell University in 1966, and the Ph.D. degree in Computer Science from Stanford University in 1973. He then was a post-doc/research scientist at Carnegie-Mellon University, working on the Hearsay-II speech understanding system. He has been a professor in the Department of Computer Science at the University of Massachusetts Amherst since 1977, and was named Distinguished Professor of Computer Science in 2009.  His major research focus is on the control and organization of complex AI systems. He is considered a leading researcher in the areas of blackboard systems, multi-agent/ distributed AI, and real-time AI. He has also made contributions in the areas of computer architecture, signal understanding, diagnostics, plan recognition, and computer-supported cooperative work. He has worked in application areas such as sensor networks for vehicle tracking and weather monitoring, speech and sound understanding, information gathering on the internet, peer-to-peer information retrieval, intelligent user interfaces, distributed task allocation and scheduling, and virtual agent enterprises.

Professor Lesser is a Founding Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and an IEEE Fellow. He was General Chair of the first international conference on Multi-Agent Systems (ICMAS) in 1995, and Founding President of the International Foundation of Autonomous Agents and Multi-Agent Systems (IFAAMAS) in 1998. To honor his contributions to the field of multi-agent systems, IFAAMAS established the “Victor Lesser Distinguished Dissertation Award.” He received the UMass Amherst College of Natural Sciences and Mathematics (NSM) Outstanding Teaching Award (2004) and Outstanding Research Award (2008), and the Chancellor’s Award for Outstanding Accomplishments in Research and Creative Activity (2008). Professor Lesser was also the recipient of the IJCAI-09 Award for Research Excellence.

http://dis.cs.umass.edu/lesser.html

 

14 NOVEMBER 2011
Speaker: Susan Landau, Visiting Scholar, Department of Computer Science, Harvard University
Title: The Risks Posed by New Wiretapping Technologies
Host School: Duke
Duke Host:
 Landon Cox (lpcox at cs.duke.edu)
UNC Host: Sanjoy Baruah (baruah at cs.unc.edu)
NCSU Host:

YouTube video of talk

Abstract:
The United States has moved large portions of business and commerce, including the control of critical infrastructure, onto IP-based networks.  This reliance on information systems leaves the U.S. highly exposed and vulnerable to cyberattack, yet U.S. law enforcement remains focused on building wiretapping systems within communications infrastructure.  In embedding eavesdropping mechanisms into communications technology itself, we are building tools that could easily be turned against us. Indeed, such attacks have already occurred. In a world that has Al-Qaeda, nation-state economic espionage, and Hurricane Katrina, how do we get communications security right?

Biography:
Susan Landau is a Visiting Scholar in the Department of Computer Science at Harvard University, where she works on cybersecurity policy issues. In 2010-2011, Landau was a fellow at the Radcliffe Institute for Advanced Study at Harvard, while from 1999-2010 she was at Sun Microsystems, most recently as Distinguished Engineer. Before joining Sun, Landau taught at the University of Massachusetts and Wesleyan University and conducted research in algebraic algorithms. Landau’s book, Surveillance or Security? The Risks Posed by New Wiretapping Technologies has just been published by MIT Press; she is also co-author, with Whitfield Diffie, of the 1998 Privacy on the Line: The Politics of Wiretapping and Encryption. Landau testified in 2011 for the House Judiciary Committee on security risks in wiretapping, while in 2009 she testified for the House Science Committee on Cybersecurity Activities at NIST’s Information Technology Laboratory. Landau serves on the Computer Science and Telecommunications Board of the National Research Council and on the advisory committee for the National Science Foundation’s Directorate for Computer and Information Science and Engineering. Landau is the recipient of the 2008 Women of Vision Social Impact Award,a Fellow of the American Association for the Advancement of Science, and an ACM Distinguished Engineer.

http://privacyink.org/

 

21 NOVEMBER 2011
SpeakerVictoria Interrante, Associate Professor, Department of Computer Science and Engineering, University of Minnesota
Title: Enhancing Spatial Cognition in Immersive Virtual Environments
Host School: UNC
UNC Host: Russ Taylor (taylorr at cs.unc.edu)
Duke Host:
NCSU Host: Chris Healey (healey at csc.ncsu.edu)

YouTube video of talk

Abstract:
Immersive virtual environments technology offers the potential to enable people to experience a three-dimensional, computer-modeled space as if they were actually there.  As such, it has tremendous potential for a wide variety of applications in diverse fields from psychology to training to design and visualization.  A key concern in the use of virtual environments for design is ensuring that the spatial judgments people make about a computer model of a virtual place are equivalent to the judgments they would have made in reality.  A related concern is enabling people to derive an accurate spatial understanding of a large virtual space by actively exploring it.  In this talk I will describe the valuable role that virtual environments technology can play in architectural design and education, and will review the efforts that my colleagues and I, in the Digital Design Consortium at the University of Minnesota, have been pursuing to more effectively harness the full potential of immersive virtual environments technology for architectural design and related applications.

Biography: 
Associate Professor Interrante’s research specializes in visualization and computer graphics, with a focus on issues of perception and design. She received the Presidential Early Career Award for Scientists and Engineers (PECASE), the federal government’s highest honor for new scientists in 1999, and was awarded the McKnight Land-Grant Professorship in 2001-2003. She has played a key role in building interdisciplinary connections between the perception and graphics/visualization communities internationally, initiating the ACM/SIGGRAPH Symposium on Applied Perception and serving on the editorial board of the ACM Transactions on Applied Perception. She also enjoys numerous interdisciplinary collaborations with colleagues from a variety of departments across the University of Minnesota, including Architecture, Aerospace and Mechanical Engineering, and the Institute of Child Development.

http://www.cs.umn.edu/people/faculty/interran


5 DECEMBER 2011
Speaker: Somesh Jha, Professor, Department of Computer Science, University of Wisconsin at Madison
Title: Retrofitting Legacy Code for Security
Host School:
 UNC
UNC Host: 
Mike Reiter (reiter at cs.unc.edu)
Duke Host: Landon Cox (lpcox at cs.duke.edu)
NCSU Host: William Enck (enck at cs.ncsu.edu)

YouTube video of talk

Abstract:
Developing programs that securely implement complex functionality when executed on a conventional operating system is a near-impossible task. If an attacker compromises any module of a program that must be trusted, then the attacker typically has the privilege to perform arbitrary operations on the host system. To resolve this issue, the operating-systems community has, in recent years, proposed privilege-aware operating systems that allow programs to explicitly manage the privileges of each module. The developers of such systems have both rewritten complex programs originally written for conventional operating systems and written original programs that apply primitives provided by these operating system to satisfy strong security properties.  However, to date, such operating systems have not been adopted by developers outside the development community of each system. Moreover, even the system’s own developers often write programs for their system that they believe to be correct, only to realize later through testing that the rewritten program is insecure or does not demonstrate desired functionality of the original program.

Biography:
Somesh Jha received his B.Tech from Indian Institute of Technology, New Delhi in Electrical Engineering. He received his Ph.D. in Computer Science from Carnegie Mellon University in 1996. Currently, Somesh Jha is a Professor in the Computer Sciences Department at the University of Wisconsin (Madison), which he joined in 2000. His work focuses on analysis of security protocols, survivability analysis, intrusion detection, formal methods for security, and analyzing malicious code. Recently he has also worked on privacy-preserving protocols. Somesh Jha has published over 100 articles in highly-refereed conferences and prominent journals. He has won numerous best-paper awards.  Somesh also received the NSF career award in 2005.

http://pages.cs.wisc.edu/~jha/

 

23 JANUARY 2012
Speaker: Thomas G. Dietterich, Oregon State University Corvalis
Title: Machine Learning in Ecological Science and Environmental Management
Host School: Duke
Duke Host: Ronald Parr (parr at cs.duke.edu)
UNC Host: 
Vladimir Jojic (vjojic at cs.unc.edu)
NCSU Host:

YouTube video of talk

Abstract:
There are many problems in ecological science and ecosystem management that could be transformed by machine learning. This talk will give an overview of several research projects at Oregon State University in this area and discuss the novel machine learning problems that arise. These include (a) automated data cleaning and anomaly detection in sensor data streams, (b) species distribution modeling including modeling of bird migration from citizen science data, and (c) design of optimal policies for managing wildfires and invasive species. The machine learning challenges include flexible anomaly detection for multiple data streams, explicit models of sampling bias and measurement processes, combining probabilistic graphical models with non-parametric learning methods, and optimization of complex spatio-temporal Markov processes.

Biography:
Dr. Dietterich (AB Oberlin College 1977; MS University of Illinois 1979; PhD Stanford University 1984) is Professor and Director of Intelligent Systems in the School of Electrical Engineering and Computer Science at Oregon State University, where he joined the faculty in 1985. In 1987, he was named a Presidential Young Investigator for the NSF. In 1990, he published, with Dr. Jude Shavlik, the book entitled Readings in Machine Learning, and he also served as the Technical Program Co-Chair of the National Conference on Artificial Intelligence (AAAI-90). From 1992-1998 he held the position of Executive Editor of the journal Machine Learning. The Association for the Advancement of Artificial Intelligence named him a Fellow in 1994, and the Association for Computing Machinery did the same in 2003. In 2000, he co-founded a new, free electronic journal: The Journal of Machine Learning Research and he is currently a member of the Editorial Board. He served as Technical Program Chair of the Neural Information Processing Systems (NIPS) conference in 2000 and General Chair in 2001. He is Past-President of the International Machine Learning Society, a member of the IMLS Board, and he also serves on the Advisory Board of the NIPS Foundation.

http://web.engr.oregonstate.edu/~tgd/

 

27 FEBRUARY 2012
Speaker: David E. Shaw, Chief Scientist at D.E. Shaw Research
Title: Anton:  A Special-Purpose Machine That Achieves a Hundred-Fold Speedup in Biomolecular Simulations
Host School: UNC
UNC Host: Stan Ahalt (ahalt at cs.unc.edu)
Duke Host:
NCSU Host:

YouTube video of talk

Abstract:
Molecular dynamics (MD) simulation has long been recognized as a potentially transformative tool for understanding the behavior of proteins and other biological macromolecules, and for developing a new generation of precisely targeted drugs.  Many biologically important phenomena, however, occur over timescales that have previously fallen far outside the reach of MD technology.  We have constructed a specialized, massively parallel machine, called Anton, that is capable of performing atomic-level simulations of proteins at a speed roughly two orders of magnitude beyond that of the previous state of the art.  The machine has now simulated the behavior of a number of proteins for periods as long as two milliseconds — approximately 200 times the length of the longest such simulation previously published — revealing aspects of protein dynamics that were previously inaccessible to both computational and experimental study.  The speed at which Anton performs these simulations is in large part the result of a tightly coupled codesign process in which the machine architecture was developed in concert with novel algorithms, including an asymptotically optimal parallel algorithm (with highly attractive constant factors) for the range-limited N-body problem.

Biography:
David E. Shaw serves as chief scientist of D. E. Shaw Research and as a senior research fellow at the Center for Computational Biology and Bioinformatics at Columbia University.  He received his Ph.D. from Stanford University in 1980, served on the faculty of the Computer Science Department at Columbia until 1986, and founded the D. E. Shaw group in 1988.  Since 2001, Dr. Shaw has been involved in hands-on research in the field of computational biochemistry.  His lab is currently involved in the development of new algorithms and machine architectures for high-speed biomolecular simulations, and in the application of such simulations to basic scientific research and computer-assisted drug design.  The special-purpose supercomputer he designed, along with its use to answer longstanding open questions about the process of protein folding, were selected by the journal Science as one of the ten most important scientific breakthroughs of the year 2010.

Dr. Shaw was appointed to the President’s Council of Advisors on Science and Technology by President Clinton in 1994, and again by President Obama in 2009.  He is a fellow of the American Academy of Arts and Sciences and of the American Association for the Advancement of Science, a member of the Computer Science and Telecommunications Board of the National Academies, and a winner of the ACM Gordon Bell Prize.

 

12 MARCH 2012 – CANCELLED
Speaker: Insup Lee, Professor, Department of Computer and Information Science, School of Engineering and Applied Science, University of Pennsylvania
Title: Challenges and Research Directions in Medical Cyber-Physical Systems
Host School:
 UNC
UNC Host: 
Sanjoy Baruah (baruah at cs.unc.edu)
Duke Host:
NCSU Host: 

 

Abstract:
Medical cyber-physical systems (MCPS) are life-critical, context-aware, networked systems of medical devices. These systems are increasingly used in hospitals to provide high-quality continuous care for patients. The need to design complex MCPS that are both safe and effective has presented numerous challenges, including achieving high assurance in system software, interoperability, context-aware intelligence, autonomy, security and privacy, and device certification. In this talk, I discuss these challenges in developing MCPS and present some of our work in addressing them, and several open research issues.

Biography:
Insup Lee is Cecilia Fitler Moore Professor of Computer and Information Science and Director of PRECISE Center at the University of Pennsylvania. He also holds a secondary appointment in the Department of Electrical and Systems Engineering. He received the B.S. in Mathematics from the University of North Carolina, Chapel Hill and the Ph.D. in Computer Science from the University of Wisconsin, Madison. His research interests include cyber physical systems (CPS), real-time embedded systems, formal methods and tools, high-confidence medical device systems, and trust management. The theme of his research activities has been to assure and improve the correctness, safety, and timeliness of life-critical embedded systems, especially in the area of medical cyber physical systems. He has served on many program committees and chaired many international conferences and workshops. He has also served on various steering and advisory committees of technical societies, including CPSWeek, ESWeek, ACM SIGBED, IEEE TC-RTS, RV, ATVA. He has served on the editorial boards of the several scientific journals and is a founding co-Editor-in-Chief of KIISE Journal of Computing Science and Engineering (JCSE). He was Chair of IEEE Computer Society Technical Committee on Real-Time Systems (2003-2004) and an IEEE CS Distinguished Visitor Speaker (2004-2006). He with his student received the best paper award in RTSS 2003. He was a member of Technical Advisory Group (TAG) of President’s Council of Advisors on Science and Technology (PCAST) Networking and Information Technology (NIT), 2006-2007. He is IEEE fellow and received IEEE TC-RTS Outstanding Technical Achievement and Leadership Award in 2008.

http://www.cis.upenn.edu/~lee/home/home.html
23 APRIL 2012
Speaker: Daniel Spielman, Professor, Applied Mathematics and Computer Science, Yale University
Title: Approximating Graphs and Solving Systems of Linear Equations
Host School: 
Duke
Duke Host: 
Pankaj Agarwal (pankaj at cs.duke.edu)
UNC Host: 

NCSU Host:

YouTube video of talk

Abstract:
We survey recent advances in the design of algorithms for solving linear equations in the Laplacian matrices of graphs. These algorithms motivate and rely upon fascinating concepts in graph theory, the most important of which is a definition of what it means for one graph to approximate another. This definition leads to the problem of sparsification: the approximation of one graph by a sparser graph.

The sparsest possible approximation of a graph is a spanning tree. The average stretch of a spanning tree will be revealed to be a good measure of its approximation quality. We explain how every graph on n vertices can be well-approximated by a graph with O (n) edges. To solve linear equations, we will require something in between: approximations by graphs with n + O (n / log n) vertices. To build these sparse approximations, we employ low-stretch spanning trees, random matrix theory, spectral graph theory, and graph partitioning algorithms.

Biography:
Daniel Alan Spielman received his B.A. in Mathematics and Computer Science from Yale in 1992, and his Ph.D in Applied Mathematics from M.I.T. in 1995. He spent a year as a NSF Mathematical Sciences Postdoc in the Computer Science Department at U.C. Berkeley, and then taught in the Applied Mathematics Department at M.I.T. until 2005. Since 2006, he has been a Professor of Applied Mathematics and Computer Science at Yale University. The awards he has received include the 1995 ACM Doctoral Dissertation Award, the 2002 IEEE Information Theory Paper Award, the 2008 Godel Prize and the 2009 Fulkerson Prize. His main research interests include the design and analysis of algorithms, graph theory, machine learning, error-correcting codes and combinatorial scientific computing.

http://www.cs.yale.edu/homes/spielman/