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 <channel>
  <title>URCS Seminars &amp; Talks</title>
  <link>http://www.cs.rochester.edu/dept/seminar</link>
  <description>Upcoming Seminars &amp; Talks from the Computer Science Department at the University of Rochester</description>
  <language>en-us</language>
  <image>
   <url>http://www.cs.rochester.edu/images/monalogo.jpg</url>
   <title>Computer Science Department, University of Rochester</title>
   <link>http://www.cs.rochester.edu/dept/seminar</link>
  </image>
  <lastBuildDate>Mon, 24 Nov 2008 12:25:41 -0500</lastBuildDate>
  
   <item>
    <title>Peter Clark: Some Explorations in using World Knowledge to improve Text Understanding</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/378</link>
    <description>[Monday, December 08, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] One reason text understanding is hard is because only a fraction of the 
knowledge the author intended to convey is explicitly stated. As
a result, for computers to correctly interpret text and &quot;fill in the gaps&quot;, 
a vast amount of lexical and world knowledge is needed. This challenge is 
present both in the small (Does a sentence reasonably follow from a text? 
The task of recognizing textual entailment), and in the large (What is a 
coherent representation of multiple texts about the same topic?). In this 
talk I will present some of our forays at Boeing into this task, in particular 
the Recognizing Texual Entailment challenge, in which we attempt to leverage 
three vast sources of knowledge (WordNet, 12 million paraphrases, and 
55 million &quot;tuples&quot;). I will discuss what worked, what didn&#39;t, and 
tentatively suggest some further small steps forward toward the AI dream 
of machines that can read for themselves.


Bio: Peter Clark is an Associate Technical Fellow in Boeing&#39;s Network Systems
Technology Organization in Seattle, WA, where he leads projects in the areas 
of knowledge-based systems, commonsense reasoning, and natural language 
processing, including for Vulcan&#39;s Project Halo and previously for IARPA&#39;s 
AQUAINT Program.

Refreshment will be provided at 10:45AM

</description>
    <pubDate>Mon, 24 Nov 2008 12:25:41 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/378</guid>
   </item>
  
   <item>
    <title>Dr. Mitsunori Ogihara: Computational Analysis of Digital Music Data</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/346</link>
    <description>[Monday, December 01, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] Recent advancements in digital music listening technologies have made possible for music listeners to have instant access to a vast amount of music with a few clicks of button.   This raises an issue of developing efficient computational technologies for organizing, searching and delivering various kinds of music data. Music information retrieval (MIR) is an area that aims at developing techniques for understanding music data and then developing such methods for music organization, search, and delivery.  In this talk, I will present some of my work in this area and discuss future problems.  The first topic is music classification based on audio signal data.  I will present a method for extracting features using wavelets and discuss the problem of calculating genre labels and mood labels.  The next topic is classification and clustering of lyrics, in particular, integration of lyrics and acoustic signals for classification.  This goal is achieved using a method that takes advantage of the existence of two heterogeneous data sources.  The last topic is clustering of acoustic signals using partial input from the user.  This is achieved by the use of constrained K-Means clustering.

Bio: Mitsunori Ogihara is Professor of Computer Science at the University of Miami and Director for Data Mining in the University&#39;s newly created Center for Computational Sciences.  He received his Ph.D. degree in Information Sciences from Tokyo Institute of Technology in 1993.  Between 1994 and 2007 he was a faculty member of the Department of Computer Science at the University of Rochester.  There he became Associate Professor in 1998 and became Full Professor in 2001.  He also served as chair of the department between 1999 and 2007.  He is a recipient of an NSF CAREER Award.  He is an ACM Distinguished Scientist Member.  Dr. Ogihara has published two books (one co-authored), more than 50 journal articles, and more than 80 conference articles.  He is currently on the editorial board of International Journal of Foundations of Computer Science (World Scientific Press) and Theory of Computing Systems (Springer).

Refreshments provided at 10:45 AM

</description>
    <pubDate>Mon, 17 Nov 2008 10:23:58 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/346</guid>
   </item>
  
   <item>
    <title>Anne Condon: Computational challenges and opportunities in RNA secondary structure prediction and design</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/376</link>
    <description>[Friday, November 21, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] DNA and RNA molecules have proven to be very versatile materials. Structures formed by RNA molecules play important regulatory and catalytic roles in the cell, and show promise in therapeutics. Molecular engineers can now design and realize nano-scale structures and sensors, and even simple machines with moving parts, built from DNA.  Function follows form in the molecular world, and so our ability to understand nucleic acid function in the cell, as well as to design novel structures, is enhanced by reliable means for structure prediction.

Computational work on RNA structure prediction has focused on secondary structure - the set of base pairs that form when the molecule folds on itself.  Algorithms which predict RNA and DNA secondary structure from the base sequence typically rely on models of the physical (thermodynamic) aspects of molecular folding.  In this talk, we will describe some algorithmic and inference problems that arise in DNA/RNA secondary structure prediction from the base sequence and progress in solving these problems. We will also describe ways in which such structures are being designed for novel functions, and new directions for research in modeling and analysis of such designs.




No prior biological background will be assumed for the talk.

Bio: Anne received her B.Sc. degree (1982) from University College Cork, Ireland and Ph.D. (1987) from U. Washington.  She was a faculty member at U. Wisconsin from 1987-1999.  She won an ACM Distinguished Dissertation Award, NSF National Young Investigator Award, and University College Cork Distinguished Alumna Award for her work.  She holds an NSERC/GM Canada Chair.

Refreshments will be provided at 10:45</description>
    <pubDate>Thu, 13 Nov 2008 08:35:59 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/376</guid>
   </item>
  
   <item>
    <title>Eby Friedman: Design Challenges in High Performance Three-Dimensional Circuits</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/377</link>
    <description>[Monday, November 24, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] The initial focus of the presentation will be on reviewing the fundamental trends specific to 3-D circuits and systems, including the many opportunities and challenges of this exciting new technology. A short review of the MIT Lincoln Laboratories 3-D manufacturing technology will follow. A summary of some primary issues in the physical design of 3-D systems will be reviewed, including some algorithmic research opportunites and low hanging fruit possibly germane to the computer science community. This discussion will be followed by a review of current research in the area of on-chip 3-D computer network topologies; specifically, 3-D networks-on chip.  A discussion of the so-called Rochester Cube will then be presented in the context of its relative impact and importance. Circuit design issues will be discussed and experimental results will be reviewed. The presentation will conclude with a review of some near-term and long term research problems, some of which are deeply relevant to the computer science community. 

	
Short Bio

Eby G. Friedman received the B.S. degree from Lafayette College in 1979, and the M.S. and Ph.D. degrees from the University of California, Irvine, in 1981 and 1989, respectively, all in electrical engineering. From 1979 to 1991, he was with Hughes Aircraft Company. He has been with the Department of Electrical and Computer Engineering at the University of Rochester since 1991, where he is a Distinguished Professor, and the Director of the High Performance VLSI/IC Design and Analysis Laboratory. He is also a Visiting Professor at the Technion - Israel Institute of Technology. His current research and teaching interests are in high performance synchronous digital and mixed-signal microelectronic circuit design. He is the author of more than 320 papers and book chapters, several patents, and the author or editor of ten books in the fields of high speed and low power CMOS design techniques, high speed interconnect, and the theory and application of synchronous clock and power distribution networks. He previously was the Editor-in-Chief of the IEEE Transactions on Very Large Scale Integration (VLSI) Systems, and a recipient of the University of Rochester Graduate Teaching Award, and a College of Engineering Teaching Excellence Award. Dr. Friedman is a Senior Fulbright Fellow and an IEEE Fellow. 

Refreshments will be provided at 10:45</description>
    <pubDate>Wed, 12 Nov 2008 08:42:31 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/377</guid>
   </item>
  
   <item>
    <title>Tina Eliassi-Rad: Classification in Sparsely Labeled Networks</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/375</link>
    <description>[Monday, December 15, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] In this talk, I will address the problem of classification in partially labeled networks (a.k.a. within-network classification), where observed class labels are sparse. Recent work in statistical relational learning have been shown to perform well on network classification tasks by exploiting dependencies between class labels of neighboring nodes. However, relational classifiers can fail when unlabeled nodes have too few labeled neighbors to support learning (during the training phase) and/or inference (during the testing phase). This situation arises in many real-world tasks where observed labels are sparse (i.e., less than 10% of the total population). Examples include identification of suspicious blog postings, malicious web pages, and fraudulent cell phones.

I will motivate a novel approach to within-network classification that combines aspects of statistical relational learning and semi-supervised learning to improve classification performance in sparse networks. Our approach works by adding “ghost edges” to a network, which enable the flow of information from labeled to unlabeled nodes. Through experiments on real-world data sets, we demonstrate that our approach performs well across a range of conditions where existing approaches, such as collective classification and semi-supervised learning, fail. On all tasks, our approach improves classification performance by up to 15% over existing approaches. Furthermore, our approach runs in time proportional to L*E, where L is the number of labeled nodes and E is the number of edges. I will conclude by placing this work in the context of my research program on role discovery in dynamic heterogeneous networks.

Refreshments will be provided at 10:45AM</description>
    <pubDate>Tue, 11 Nov 2008 10:49:11 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/375</guid>
   </item>
  
   <item>
    <title>Dr. Madhu Sudan: Communicating Computers and Computing Communicators:</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/367</link>
    <description>[Monday, November 17, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] The theories of computing (Turing, ~1930s) and communication
(Shannon, Hamming ~1940s) have had a profound impact of the
development of the two fields and the resulting technologies have
drastically altered our lives today.

Part of the success of the two theories can be attributed to
a clean separation of the computing elements from the communicating
elements. Today, however, communication and computing are coming ever closer together, often leaving the human out of the loop. This merger is posing new challenges, definitional and algorithmic, to the theory of
communication. In this talk I will describe some of the concrete
challenges that we have looked at. I will also describe our attempts at
modelling these problems and, in some cases, describe some preliminary
solutions.

Bio:

Madhu  Sudan  received  his  Bachelor&#39;s  degree  from  the Indian Institute of Technology at New Delhi in 1987 and his  Ph.D.  from the University of California at Berkeley in 1992. From 1992-1997 he was a Research Staff Member at IBM&#39;s Thomas J. Watson Research Center. In 1997, he moved to MIT where he is now the Fujitsu Professor of Electrical Engineering and Computer Science, and an Associate Director of MIT&#39;s Computer Science and Artificial Intelligence Laboratory (CSAIL). He was a Fellow at the Radcliffe Institute for Advanced Study from 2003-2004, and a Guggenheim Fellow from 2005-2006.
Madhu Sudan&#39;s research interests include computational complexity
theory,  algorithms  and coding theory.  He is best known for his
works on  probabilistic  checking  of  proofs, and on the  design
of   list-decoding   algorithms   for  error-correcting codes.
In 2002 Madhu Sudan was awarded the Nevanlinna Prize, for outstanding contributions to the mathematics of computer science, at the International
Congress of Mathematicians in Beijing. Madhu Sudan&#39;s other awards include
the ACM Doctoral Dissertation Award (1992), the IEEE Information Theory Society Paper Award (2000) and the Godel Prize (2001),
Distinguished Alumnus Award of the University of California at Berkeley (2003), and Distinguished Alumnus Award of the Indian Institute of Technology at Delhi (2004).

Refreshments will be provided at 10:45</description>
    <pubDate>Mon, 10 Nov 2008 09:27:20 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/367</guid>
   </item>
  
   <item>
    <title>Dr. Jan-Willem Maessen: Fortress: Parallel Programming Through Extensible Bulk Operations</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/366</link>
    <description>[Monday, November 10, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] The Fortress programming language (http://projectfortress.sun.com) has
a number of ambitious goals aimed at making it easier for ordinary
engineers, scientists, and programmers to write parallel code.  In
order to accomplish this goal, Fortress focuses on bulk operations on
parallel data structures---an approach that is at the core of most
successful models of parallel programming in widespread use.  This
talk will provide an overview of some of the novel features of the
Fortress language: flexible mathematical syntax with bulk operations
such as comprehensions and reductions, implicit parallelism, an
innovative type system, and library-based implementation of language
constructs.  More important, it will show how all these features combine
to allow programmers to extend the language with new bulk operations
and new sources of parallel data.


Short bio:

Jan-Willem Maessen has been part of Project Fortress since its
inception in 2002, and is presently the primary maintainer of the
libraries for the Fortress programming language.  He has been heavily
involved in the design of the Fortress language and in its
implementation, and drafted the original specifications of the
parallel portions of the language.  His many interests include
language design, memory consistency models, concurrent algorithms,
compilation, semantics, and architecture.

Prior to joining Sun, Jan developed Eager Haskell, a Haskell
implementation that executes programs using resource-bounded eager
evaluation rather than lazy evaluation.  He also contributed heavily
to the compiler and libraries for pH, an implicitly-parallel
programming language based on Haskell.

Refreshment will be provided at 10:45 AM</description>
    <pubDate>Mon, 03 Nov 2008 11:13:40 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/366</guid>
   </item>
  
   <item>
    <title>Dr. Paul Horn: The Changing Nature of Innovation</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/371</link>
    <description>[Thursday, October 30, 2008 at  4:00 PM in The Robert B. Goergen Hall Room 109] Paul Horn, who received a PhD in Physics from the University in 1974,
will deliver a talk entitled &quot;The Changing Nature of Innovation&quot; on
campus on Thursday, October 30 beginning at 4 pm. The lecture will
take place in the Fantone Room (Room 109) of The Robert B. Goergen
Hall for Biomedical Engineering and Optics. Members of the campus and
Rochester communities are invited to attend Dr. Horn&#39;s talk.

Dr. Horn recently retired as Senior Vice President for Research at IBM
Corporation and is now a Distinguished Scientist in Residence at New
York University. During his years at IBM, he directed the company&#39;s
worldwide research programs in five countries around the world. Under
his guidance, IBM created the Deep Blue and Blue Gene supercomputers
and other major innovations. He has been an avid champion for
translating technology based research into marketplace opportunities.

Born in New York City, Dr. Horn received his undergraduate training at
Clarkson College of Technology and his doctoral degree from Rochester.
Prior to joining IBM in 1979, Dr. Horn was a Professor of Physics in
the James Franck Institute and the Physics Department at the
University of Chicago. He is a Fellow of the American Physical Society
and the National Academy of Engineering.

He has been the recipient of numerous awards including the 1988
Bertram Eugene Award and the 2002 Hutchison Medal from the University
of Rochester. In 2003 he was named one of the top computing business
leaders in the United States by Scientific American magazine. He is a
member of the boards of Gallaudet University, the Committee for
Economic Development, Clarkson University, New York Polytechnic
University, UC Berkeley, and the New York Hall of Science.

This lecture is co-sponsored by the College Deans&#39; Office, the
Department of Physics, and the Department of Computer Science.

Please Plan to Attend!!

</description>
    <pubDate>Thu, 30 Oct 2008 09:01:40 -0400</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/371</guid>
   </item>
  
   <item>
    <title>Dr. Amnon Barak: The MOSIX Algorithms for Managing Clusters, Multi- clusters and Cloud Computing Systems                                                                                                            </title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/370</link>
    <description>[Monday, November 03, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] MOSIX is a management system  targeted  for  high  performance
  computing  on  Linux  clusters,  multi-cluster (organizational
  grids) and clouds.  It incorporates algorithms  for  automatic
  resource discovery and dynamic workload distribution, commonly
  found on single computers with multiple processors.

  MOSIX is implemented as a software virtualization  layer  that
  allows applications to run in remote nodes, e.g. clouds, as if
  they run locally.  Users can start applications on  one  node,
  e.g. workstation, while MOSIX automatically seek resources and
  transparently allocate or migrate processes  to  other  nodes.
  Users  do not need to modify or link applications with special
  libraries, login or copy files to remote clusters.

  Process migration is supervised by a comprehensive set of  online  algorithms  that  monitor  the  state  of  resources and
  attempt to optimize a target  goal,  such  as  load-balancing,
  improved overall performance, avoid overheating, support green
  computing, fair-share node allocation, Grid economy  and  support of disruptive configurations.

  The  presentation begins with a brief overview of cluster management systems followed by an explanation of the MOSIX  algorithms, its cluster, multi-cluster and cloud services.


  Bio:

  Amnon  Barak is Strauss Professor of Computer Science and manager of the Distributed Systems research lab in the department
  of Computer Science at The Hebrew University of Jerusalem.  He
  received the B.S. degree in mathematics from the Technion, and
  the  M.S.  and Ph.D. degrees in computer science from the University of Illinois at Urbana-Champaign.  His research  interests include parallel and distributed systems, management systems for clusters and grids, dynamic resource allocation, grid
  economy  and competitive algorithms for resource management in
  clusters and grids.

   Refreshments will be provided at 10:45 AM
 </description>
    <pubDate>Tue, 28 Oct 2008 09:37:05 -0400</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/370</guid>
   </item>
  
   <item>
    <title>Dr. Henry Kautz: State of the Department</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/352</link>
    <description>[Monday, October 13, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] </description>
    <pubDate>Thu, 09 Oct 2008 15:53:54 -0400</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/352</guid>
   </item>
  
   <item>
    <title>Dr. George Ferguson: Intelligent Collaborative Assistants</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/351</link>
    <description>[Monday, October 20, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] Do you hate using computers? I know I do. Interfaces have barely changed since Xerox invented the GUI in the late 70&#39;s. More importantly, the only way to get computers to do anything is by programming them. While good for CS grads&#39; job security, this solution doesn&#39;t scale.

In this talk I will describe the work we are doing to develop intelligent collaborative assistants--software systems that work with users to help them solve problems. Among the topics that may be covered are: speech recognition, natural language understanding, intention recognition, collaborative behavior, multi-agent systems, agent-oriented programming, and the role of knowledge. I&#39;ll present examples from our work with web applications, desktop computing, and personal healthcare.

Bio:
George Ferguson is a Research Scientist in the Computer Science Department at the University of Rochester in Rochester, New York. He came to Rochester in 1989 after degrees at McGill University and the University of Alberta. He received his Ph.D. from the University of Rochester in 1995 and has continued his work on intelligent assistants ever since. Dr. Ferguson is also a founding member of the University&#39;s Center for Future Health, whose mission is to develop novel technologies and systems that empower people to take better care of their health.

Refreshments will be provided at 10:45am
</description>
    <pubDate>Mon, 06 Oct 2008 10:29:04 -0400</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/351</guid>
   </item>
  
   <item>
    <title>Dr. Daniel Gildea: Machine Translation</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/345</link>
    <description>[Monday, September 15, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] I will discuss the state of the art in machine translation, and
present recent work on the theoretical complexity of translation
with synchronous context-free grammars, as well as practical
algorithms for efficient MT.








Refreshments will be provided at 10:45AM</description>
    <pubDate>Wed, 10 Sep 2008 13:50:47 -0400</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/345</guid>
   </item>
  
   <item>
    <title>Jerod Weinman: Discriminative Probabilistic Models for Robust Scene Text Recognition</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/339</link>
    <description>[Monday, May 05, 2008 at  1:50 PM in Computer Studies Building, Room 703] A first-grader can still read better than the best character
recognition software. Why? The reasons for this are varied, but one limitation of many approaches is a feed-forward, bottom-up, pipelined architecture that isolates the many tasks and information involved in reading. The result is a system that commits errors from which it cannot recover and has components that lack access to relevant information. In this talk, we&#39;ll look at what it might take to develop a &quot;seeing eye computer&quot; that can read to the blind.</description>
    <pubDate>Mon, 05 May 2008 08:18:01 -0400</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/339</guid>
   </item>
  
   <item>
    <title>Dr. Max Alekseyev: Genome Rearrangements: from Biological Problems to Combinatorial Algorithms (and back)</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/321</link>
    <description>[Monday, April 07, 2008 at 11:00 AM in CSB 209] Recent large-scale sequencing projects fueled the comparative genomics studies and
revealed that some classical biological theories may be incomplete or even
incorrect. I describe three controversial and hotly debated topics: Whole
Genome Duplications, Random Breakage Model of Chromosome Evolution,
and Mammalian Phylogenomics, and three related challenging combinatorial problems:
Genome Halving Problem, Breakpoint Re-Use Problem,
and Multiple Ancestral Genomes Reconstruction Problem.
I have recently addressed these problems within a new &quot;Multi-Break Rearrangements&quot;
framework that simplified their analysis and led to efficient algorithmic solutions.
I have further applied the developed algorithms to sequenced mammalian genomes to study the
biological problems mentioned above.

Bio: Max Alekseyev is a Postdoctoral Fellow of Computer Science and Engineering at the University of California, San Diego. He received his PhD in Computer Science from UCSD in 2007. Prior to joining UCSD in 2001, he was a Lecturer and Researcher in th Department of Computational Mathematics &amp; Cybernetics at Nizhni Novgorod State University in Russia. His research interests include computational molecular biology/bioinformatics, comparative genomics, graph theory, combinatorics and discrete algorithms. He is a regular contributor to the Online Encyclopedia of Integer Sequences where he extended many computationally hard sequences, some of which also resulted in contributions to MathWorld, a famous web resource on mathematics.

Refreshments will be provided at 10:45

</description>
    <pubDate>Thu, 20 Mar 2008 09:34:21 -0400</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/321</guid>
   </item>
  
   <item>
    <title>Vinod Vaikuntanathan: New Results in Lattice-based Cryptography</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/313</link>
    <description>[Monday, March 24, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] In recent years, cryptography based on integer lattices
has emerged to be an attractive alternative to traditional,
number-theoretic cryptography. Lattice-based cryptographic
schemes are attractive for several reasons: their security
can be based on the worst-case hardness of problems, the
computations involved are simple and of low complexity and
the schemes, unlike number-theoretic ones, have thus far
resisted quantum attacks.

Unfortunately, the use of lattices in cryptography so far
has been limited to relatively simple primitives such as
one-way functions and public-key encryption.

In this talk, I will describe new ways to generate and
exploit *trapdoors* in lattices. The cryptographic
applications of our techniques are numerous: we design
various kinds of trapdoor functions, simple and efficient
digital signature schemes, general secure multiparty
computation, and identity-based encryption, all based on
the worst-case hardness of lattice problems.


Bio: Vinod Vaikuntanathan is currently a PhD candidate in
Computer Science at the Massachusetts Institute of
Technology, where he obtained his masters degree in
2005. He attended the Indian Institute of Technology
at Madras for his undergraduate studies.

He is interested in theoretical computer science and
in particular, cryptography, complexity theory and the
theory of distributed systems. Of late, he has been
studying the fruitful relationship between cryptography
and geometric objects called lattices.

Refreshments  will be provided at 10:45</description>
    <pubDate>Tue, 18 Mar 2008 10:34:54 -0400</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/313</guid>
   </item>
  
   <item>
    <title>Dr. Eric Vigoda: Random Colorings: Phase Transitions and Rapid Mixing</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/314</link>
    <description>[Friday, March 21, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] A key property (and justification for) models of interest in statistical physics
is that they exhibit phase transitions, as occur in nature when a small
change in some parameter controlling microscopic interactions
of the system causes a dramatic change (in fact a discontinuity)
in the macroscopic properties of the system (e.g., the density of water
as the temperature passes through the boiling point).

In this talk we&#39;ll look at several examples of phase transitions
for the case of random colorings.  We&#39;ll look at algorithms for
studying these models, namely algorithms for efficiently generating
a random coloring and approximately counting the
number of such colorings.  The overall theme will be possible
connections between phase transitions and the efficiency of
related algorithms.

Bio: Dr. Eric Vigoda is an associate professor of Computer Science at Georgia Institute of Technology. He received his PhD in Computer Science from UC Berkeley in 1999. Prior to joining Georgia Tech in 2004, he was a faculty member at the University of Chicago. His research focuses on randomized algorithms. His work with M. Jerrum and A. Sinclair on approximating the permanent was a co-winner of the 2006 Fulkerson prize, which is awarded triennially for outstanding publications in discrete mathematics.

Refreshments will be provided at 10:45</description>
    <pubDate>Thu, 13 Mar 2008 15:17:25 -0400</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/314</guid>
   </item>
  
   <item>
    <title> Virginia Vassilevska: Algorithms for Path Problems</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/320</link>
    <description>[Monday, March 03, 2008 at 11:00 AM in CSB 209] My talk will discuss two variants of the shortest paths problem, which
optimize different measures.  One variant maximizes the minimum edge
on the path (instead of minimizing the sum of edge weights), and the
other minimizes the last edge on a path with the additional condition
that the consecutive edge weights on the path form a nondecreasing
sequence.  Finding best paths with respect to these measures has many
applications, e.g., creating good flight itineraries and maximizing
bandwidth in packet routes, even has applications in fuzzy logic.
Furthermore, my work has shown that one can obtain really efficient
algorithms for these problems.  The goal of the talk is to show some
of my techniques on attacking path problems.  As an example for a
single source path problem, I will concentrate on minimum
nondecreasing paths.  This is based on my recent sole-authored paper
that appeared in SODA08.  As an example for an all-pairs path problem,
I will outline the first subcubic algorithm for all-pairs maximum
bottleneck paths.  This work is joint with Ryan Williams and Raphael
Yuster and appeared in STOC07.

Bio: Virginia Vassilevska is currently a computer science graduate
student at Carnegie Mellon University, from which she also received
her M.S.  Her thesis will be on ``Efficient Algorithms for Path
Problems in Weighted Graphs,&#39;&#39; and her advisor is Prof. Guy Blelloch.
Her undergraduate work was done at the California Institute of
Technology, where she graduated with honors in 2003 with a double
major in mathematics and engineering and applied science (CS).  She is
broadly interested in algorithms, data structures, and
approximability, with a particular focus on graph algorithms.
 


Refreshments will be provided at 10:45</description>
    <pubDate>Wed, 27 Feb 2008 10:26:15 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/320</guid>
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   <item>
    <title>Daniel Golovin: Uniquely Represented Data Structures with Applications to Privacy</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/315</link>
    <description>[Monday, March 17, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] A uniquely represented data structure has a unique physical state to encode each logical state of its abstract data type.
In this talk I will discuss new efficient uniquely represented versions of popular data structures (including hash tables, binary search trees, and queues), how these data structures work, and how they can be used to improve the security and privacy of real-world applications.

As an example application, consider a typical system with some internal data structures.  If the memory representations of those internal data structures are inspected, they may leave significant clues to the past use of the system.  For example, a data structure with lazy deletions might retain an object that the user believes was deleted long ago; this is problematic in environments requiring high security or strict privacy guarantees.  Uniquely represented data structures eliminate such problems entirely by storing exactly the information specified by an
abstract data type, and nothing more. 
 

 Bio: Daniel Golovin is a Ph.D. candidate at Carnegie Mellon University
under the supervision of Guy Blelloch.  His research interests include
approximation and online algorithms, using novel data structures to
improve privacy, and provably good ways of dealing with uncertainty.
He received his B.S. from Cornell University in 2003 and his M.S. from
Carnegie Mellon University in 2006.

Refreshments will be served at 10:45</description>
    <pubDate>Tue, 26 Feb 2008 09:10:09 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/315</guid>
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   <item>
    <title> Dr. Ryan Williams: Clique Problems and Applications</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/308</link>
    <description>[Monday, February 18, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] 


The problem of finding large cliques in a graph is a
fundamental NP-complete problem with many applications in the
sciences. I will examine different approaches to finding cliques as
well as some new applications, illustrating some of our work in
algorithms and complexity theory in the process. If there is time, I
will also discuss some recent work on &quot;applying practice to theory&quot;,
in which one uses fast problem solvers from practice to attack
interesting theoretical problems.

Bio: Ryan Williams is currently a postdoctoral research fellow
at Carnegie Mellon University, where he received his PhD in August
2007, advised by Manuel Blum. He received M.Eng. and A.B. degrees
from  Cornell University. His primary interests are in algorithms and
complexity theory, with secondary interests in artificial intelligence and computational notions of privacy. He has received three Best
Student Paper awards at major conferences.

Refreshments will be provided at 10:45 AM</description>
    <pubDate>Wed, 13 Feb 2008 11:21:18 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/308</guid>
   </item>
  
   <item>
    <title>Dr. Barbara Ryder: Experiences with Peer-led Team Learning (PLTL)</title>
    <link>http://www.cs.rochester.edu/dept/seminar/view/293</link>
    <description>[Monday, February 11, 2008 at 11:00 AM in Computer Studies Bldg. Room 209] Rutgers Emerging Scholars in Computer Science program (RESCS) is a program designed to recruit top incoming freshmen with strong math/science backgrounds, from groups currently underrepresented in Computer Science, to enroll in an introductory Computer Science course that includes a special additional discussion section. In the two hour weekly discussion session, participating students work in small groups on challenging problems designed to help them gain a thorough and in-depth understanding of the class material, under the guidance of peer leaders.  This effort is supported by a collaborative NSF grant that established a consortium of 8 colleges and universities (i.e.,
Beloit, Duke, Georgia Tech, Loyola (MD), Purdue, Rutgers, University of Wisconsin – Madison, University of Wisconsin – Milwaukee).   

This talk will discuss our experiences running RESCS at Rutgers in our CS1 course, since Fall 2005 as part of this consortium.  We will present how we organized the effort, how the experimental pedagogy was setup at our institution, (some) quantitative and (more) qualitative results, and our conclusions.

Our website is http://rescs.rutgers.edu.  My collaborators in this project at Rutgers are Pradip Hari, co-ordinator of our CS1 course, and the peer leaders who have worked with me over the past 4 years, Aneta Biesiadecka, Sara Hahn, Helen Nayfeld, Emily Rodriguez, Tom Schirripa, Mai Elsamahy, Alex Luchansky, Mariya Nagorna, Khrystyne Williams.
 

BIO: Dr. Barbara G. Ryder is a Professor of Computer Science at Rutgers University.  She received her Ph.D degree  in Computer Science at Rutgers in 1982.  She previously worked in the 1970’s at AT&amp;T Bell Laboratories in Murray Hill, NJ.  Dr. Ryder’s research interests focus on static and dynamic program analyses for object-oriented systems, focusing on usage in practical software tools.

Refreshments provided at 10:45</description>
    <pubDate>Wed, 30 Jan 2008 14:29:57 -0500</pubDate>
    <guid>http://www.cs.rochester.edu/dept/seminar/view/293</guid>
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