2005-2006 Abstracts
CPSC 681 Graduate Seminar
(only required for new graduate students):
Graduate Orientation I: Overview of Department Resources & Contacts,
Honor Code, and Student Organizations
MANDATORY FOR NEW GRAD STUDENTS (but not other CSPC 681 students)
4:00-5:00 p.m., Monday August 29, 2005
Room 124, Bright Building
Abstract
This meeting will concentrate on the essentials the students will need to
settle in. It will include an introduction to departmental administration
(staff who's who, payroll, mailboxes, phones), the computing resources
(computer use/accounts, printer quotas, lab access/tours),
the academic advising staff and resources,
the TAMU honor system,
and relevant student organizations (CSGSA,
AWICS,
TACS
(TAMU ACM and IEEE student chapter),
and UPE
).
MANDATORY FOR NEW GRAD STUDENTS (but not other CSPC 681 students)
CPSC 681 Graduate Seminar
(required for all new graduate students and all CPSC 681 students):
Graduate Orientation II:
Current Grad & Faculty Panels, Poster Session, & PIZZA!
MANDATORY FOR NEW GRAD STUDENTS and CPSC 681 STUDENTS
4:00-6:00 p.m., Wednesday August 31, 2005
Room 124, Bright Building
Abstract
- 4:00-4:30pm - Student Panel:
Current grad students share tips about how to succeed in graduate school.
- 4:30-5:00pm - Faculty Panel:
Faculty share their ideas about what they are looking for in a graduate
student.
- 5:00-6:00pm - Pizza & Current Student Poster Session - new students
can meet current grads and learn about ongoing research projects.
MANDATORY FOR NEW GRAD STUDENTS and CPSC 681 STUDENTS
CPSC 681 Graduate Seminar:
New Techniques for Building Large-Scale Evolutionary Trees
Dr. Tiffani Williams,
Assistant Professor of Computer Science, Texas A&M University
4:10 p.m., Wednesday September 7, 2005
Room 124, Bright Building
Abstract
Phylogenetic (or evolutionary) trees model the evolution of biological
species or genes from a common ancestor. Scientists are interested in
evolutionary trees for the usual reasons of scientific curiosity.
However, phylogenetic analysis is not just an academic exercise.
Phylogenies are the organizing principle for most biological knowledge.
As such, they are a crucial tool in identifying emerging diseases,
predicting disease outbreaks, and protecting ecosystems from invasive
species. The greatest impact of phylogenetics will be reconstructing the
Tree of Life, the evolutionary history of all-known organisms.
In this talk, I will focus on obtaining phylogenetic analyses of large
datasets under NP-hard optimization criteria (i.e., Maximum Parsimony and
Maximum Likelihood) quickly and accurately. Our current techniques are
able to analyze datasets containing thousands of taxa much faster than
traditional methods. I will also discuss promising work with parallel
computing, using the coordination language Linda, to integrate a multitude
of sequential phylogenetic algorithms for even greater performance.
Biography
Tiffani L. Williams is an Assistant Professor in the Department of Computer
Science at Texas A&M University. During the 2004-2005 academic year, she was
the Edward, Frances, and Shirley B. Daniels Fellow at the Radcliffe Institute
of Advanced Study at Harvard University. She earned her B.S. in computer
science from Marquette University and Ph.D. in computer science from
the University of Central Florida. Afterward, she was a postdoctoral fellow
at the University of New Mexico. Her honors include a Radcliffe Institute
Fellowship, an Alfred P. Sloan Foundation Postdoctoral Fellowship, and a
McKnight Doctoral Fellowship. Her research interests are in the areas of
bioinformatics and high-performance computing.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Knowledge Acquisition and Learning for Industrial Robots
Dr. Ismael Lopez,
CIATEQ (Center for Advanced Technologies), Mexico
4:10 p.m., Wednesday September 14, 2005
Room 124, Bright Building
Abstract
Robot performance during manipulative tasks has traditionally depended on
simple sensing systems and the robot manufacturers programming language.
However, this restricts the use of robots in complex manufacturing
operations. An alternative to robot programming is the creation of
self-adaptive robots based on Artificial Intelligence techniques.
The research presented in this talk shows how industrial robots can operate
autonomously in unstructured environments. This is achieved by providing
the robot with a primitive knowledge base (PKB) of the environment in
terms of visual and tactile information. This knowledge is gradually
enhanced on-line based on the contact force information acquired during
operations. The robot is able to recognize and learn different assembly
component parts and also able to grasp and to perform autonomously the
assembly operation.
When assembling the components, the robot resembles a blindfold person
performing the same task since no precise information is provided about
the localisation of the xed assembly component. The design of a novel
neural network controller (NNC) based on the Fuzzy ARTMAP network and
its implementation results on industrial robots are presented.
Finally, ongoing work looking towards the creation of a Multimodal
Architecture (M2ARTMAP) to integrate other sensorial information (e.g. odour
and taste), to reinforce the prediction capability is presented together
with simulated results.
Biography
Dr. Lopez-Juarez obtained a BEng in Mechanical and Electrical Engineering
from The National Autonomous University of Mexico (UNAM) in 1991.
He lectured at the Faculty of Engineering during 1991-1994 and also worked
as Research Assistant in the Department of Computing Systems and Automation
at The Institute of Research on Applied Mathematics and Systems (IIMAS-UNAM).
He obtained an MSc in Instrument Design and Application at UMIST and a PhD in
Intelligent Robotics at The Nottingham Trent University in collaboration
with Rolls Royce & Associates during 1996 and 2000, respectively.
Dr. Lopez-Juarez has published over forty papers in referred international
journals and proceedings in the area of Instrumentation, Self-adaptive
Industrial Robots and Neural Networks. He has also served as reviewer of
International Conferences and Journals. He is the founder and leader of
the Mechatronics and Intelligent Manufacturing Systems Research Group
(MIMSRG) at CIATEQ. He is responsible for several industrially and
government sponsored projects in the field of flexible manufacturing as
well as two projects with Texas A&M University and the German Academic
Interchange Service (DAAD) in the field of instrumentation and flexible
manufacturing. He is a founder member of the Mexican Society on Mechatronics
(AMM), member of the Mexican Society of Robotics (AmROB), member of the
Mexican Society for Computer Science (SMCC), member of the IEEE-Robotics
and Automation Society and also member of the IEEE-Computational
Intelligence Society.
CPSC 681 Faculty Contact:
Ricardo Gutierrez-Osuna
(rgutier [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Locality of Fault Tolerance
Dr. Shay Kutten,
Professor of Industrial Engineering, The Technion, Israel
4:10 p.m., Monday September 19, 2005
Room 124, Bright Building
Abstract
Traditional fault tolerance methods are global in nature. Some involve
resetting all the network nodes. Others use time-outs that imply waiting
to the slowest and furthest node, etc.
Local detection of faults is based on the following observation: even
computations that cannot be performed locally, can be verified locally.
Hence, it is possible to verify locally (cooperating only with neighbors)
global correctness predicates. If the predicate does not hold, then measures
for correctness can be invoked.
The cost of correction can also be, sometimes, local to the faults, in the
sense that when the extent of the faults is lower, the cost of the recovery is
lower too.
The talk will mention results from several papers by several authors, including
a very recent paper.
Biography
Shay Kutten received his Master and his PhD in Computer Science from the
Technion, Israel, in 1984 and 1987 respectively. From 1987 to 1996 he was
with IBM T.J. Watson Research Center, as a post doctoral fellow, as a
project leader, as the manager of the Network Architecture and Algorithms
group, and as a Research Staff Member.
At the Technion he is now the coordinator of undergraduate studies of the
faculty of Industrial Engineering and Management. He won the Taub Award for
excellence in research, and the Mitchner Award for research on Quality
Sciences and Quality Management. He is an area editor (for security,
reliability, and availability) of the ACM's journal on Selected Topics in
Mobile Networks and Applications (MONET) and the Elsevier journal Computer
Networks. He is a senior member of the IEEE, and a member of ACM-SIGACT.
CPSC 681 Faculty Contact:
Jennifer Welch
(welch [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Generics in the REAL World
Kathleen Dollard,
Gendotnet
4:10 p.m., Wednesday September 21, 2005
Room 124, Bright Building
Abstract
The new generics feature of .NET 2005 has gotten a lot of press but what's
it actually good for? Walk through the syntax of generics and basic rules
regarding their use, and then explore how to integrate them into your
applications and architectures - both the new generic classes in the
framework and your own generic classes. Learn how to design generic classes
at the core of your infrastructure, and how to avoid dead ends where you
think generics will do something that they won't. The talk will compare,
contrast, and combine generics and OOP models such as inheritance and
interfaces to introduce the new architectural patterns available in .NET 2005,
as well as clarifying details such as how and when to use the new generic
collections and nullable classes.
Biography
Kathleen Dollard is a nationally recognized author, trainer, and speaker.
Microsoft has honored her with its "Most Valuable Professional" award every
year since 1998. INETA included her in its prestigious speaker's bureau.
She's written numerous articles and "Code Generation in Microsoft .NET"
(Apress, 2004). She also codes almost every day as a consultant or for her
own company GenDotNet. Her passion is helping programmers be smarter in how
they develop. She's currently working on full life cycle improvements, such
as better debugging and capturing business intent in metadata and test
definitions. She received her Masters of Science in Chemistry at Texas A&M
in 1983. She moved full time from chemistry to computers at the dawn of the
PC revolution while working in industry in the 1980's, and has been an
independent consultant since 1989.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Location-based and Location-free Routing in Ad Hoc Wireless Networks
Dr. Anxiao (Andrew) Jiang,
Assistant Professor of Computer Science, Texas A&M University
4:10 p.m., Monday September 26, 2005
Room 124, Bright Building
Abstract
One important routing method for large ad hoc wireless networks is geographic
routing. It uses the locations of routers and a packet's destination to make
packet-forwarding decisions. Geographic routing is efficient and scalable,
however the location information is often expensive or impossible to obtain.
Because of that, routing algorithms that generate 'virtual coordinates' of
routers based on known information --- e.g., connectivity --- have been
developed, thus avoiding the usage of true location information. In this talk,
I will overview the above location-based and location-free routing algorithms,
and then present a new and different location-free routing algorithm --- MAP ---
that uses the medial axis of the network to name routers and make routing
decisions.
I will show how location-based routing algorithms use planar spanning subgraphs
to guarantee delivery of messages. However, for such techniques to work, the
network needs to adhere to the very restrictive unit-disk graph model.
Also, they create unbalanced load for networks deployed in environments with
complex topologies. Location-free routing algorithms based on virtual coordinates
often do not guarantee delivery. MAP, on the other side, uses medial axis --- an
abstraction of the environment topology --- to enable an efficient and
load-balanced routing strategy that is not restricted to the unit-disk graph model.
Biography
Anxiao (Andrew) Jiang is an assistant professor in the Computer Science
Department of Texas A&M University. He received his Ph.D. and M.S. degrees
in electrical engineering from the California Institute of Technology in
2004 and 2000, respectively. He received his B.S. degree in electronic
engineering from Tsinghua University, Beijing, China in 1999. His research
interests include algorithms, wireless ad hoc communication and sensor networks,
file storage and retrieval, and distributed systems.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Interacting with Human Physiology
Dr. Ioannis Pavlidis,
Associate Professor, University of Houston
4:10 p.m., Monday October 3, 2005
Room 124, Bright Building
Abstract
People in the U.S. spend increasing amounts of their work and leisure
time in front of computers. The term "human computer interaction"
suggests a two-way exchange, with each participant aware of the other
and responding appropriately. In reality, computers may appear
frequently rude, frustrating, indifferent, and generally unpleasant.
Much of this can be attributed to the fact that current computers are
almost completely unaware of the actual state of the human user. The
research community has proposed methods for computers to understand and
respond to the computer user's feelings with mixed results. Emphasis has
been placed on stress and frustration - feelings often generated by the
use of the computer itself. There is no previous work, however, with
regard to monitoring the actual health of the user during computer use.
People check their health status rarely or when they are symptomatic. A
typical health check features measurement of vital signs (e.g., pulse
and respiration) at a doctor's office. The value of this check is
limited by its isolated nature. This is especially true for chronic
ailments like heartbeat irregularities, headaches, or anxiety disorders,
which manifest themselves intermittently for short intervals in a
stochastic manner.
In this research effort we incorporate physiologic monitoring in the
human-computer interface (HCI). The sensing element is a thermal imaging
camera that is employed as a computer peripheral. Through bioheat
modeling of facial imagery almost the full range of vital signs can be
extracted, including blood flow, cardiac pulse, and breathing rate. This
nearly continuous physiological information can then be used to draw
inferences about a variety of health symptoms. Our research aims to
realize the notion of desktop health monitoring and create truly
collaborative interactions in which human and machines are both
observing and responding.
Biography
Dr. Pavlidis holds a Ph.D. and a M.S. degree in Computer Science from
the University of Minnesota, a M.S. degree in Robotics from the Imperial
College of the University of London, and a B.S. degree in Electrical
Engineering from the Democritus University in Greece. He joined the
Honeywell Laboratories immediately upon his graduation in January 1997.
His expertise is in the areas of Computer Vision beyond the Visible
Spectrum, Computational Physiology, and Software Engineering. Dr.
Pavlidis published extensively in these areas in major journals and
refereed conference proceedings over the past several years. His
publication record includes articles in the IEEE Proceedings, New
England Journal of Medicine, The Lancet, and Nature. He is also the
author of the book "Programming of Cameras and Pan-Tilts with DirectX
and Java" by Morgan Kaufmann.
Dr. Pavlidis is also the author of multiple patents, some of which
protect multi-million dollar products of Fortune 30 companies (e.g., DVM
of Honeywell). Dr. Pavlidis' research work was cited extensively in the
scientific literature and has been mentioned frequently by the
international media including CNN, The Reuters, The Time magazine, The
L.A. Times, and the Discover magazine. Dr. Pavlidis is a Fulbright
Fellow, a Senior Member of IEEE, and a member of ACM.
Dr. Pavlidis joined the Computer Science Department of the University of
Houston in September 2002, where he currently holds the position of
Associate Professor.
CPSC 681 Faculty Contact:
Ricardo Gutierrez-Osuna
(rgutier [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Pattern recognition for chemical sensor arrays
with neuromorphic models of the olfactory system
Dr. Ricardo Gutierrez-Osuna,
Assistant Professor of Computer Science, Texas A&M University
4:10 p.m., Monday October 10, 2005
Room 124, Bright Building
Abstract
The integration of gas sensor arrays and pattern-analysis techniques has
received much attention in recent years as a low-cost alternative to
odor measurement, conventionally carried out with analytical instruments
or human panels. When exposed to volatile compounds, the multivariate
response of an array of cross-selective sensors can be used as a digital
fingerprint, and processed with pattern recognition tools to predict
the identity and/or concentration of the volatiles.
To date, most of the pattern recognition for chemical sensor arrays has been
based on statistical techniques. The objective of our work is to develop
new algorithms inspired by the biological olfactory system. We will
present a review of the main computational principles in the olfactory
pathway, and describe their application to the processing of sensor-array
signals. We will also discuss the correlation of instrument data with
sensory analysis from human panels.
Biography
Ricardo Gutierrez-Osuna received the B.S. degree in Electrical Engineering
from the Polytechnic University of Madrid (Spain) in 1992, and the M.S.
and Ph.D. degrees in Computer Engineering from North Carolina State
University in 1995 and 1998, respectively. From 1998 to 2002 he served
on the faculty at Wright State University. He is currently an assistant
professor in the Department of Computer Science at Texas A&M University.
Dr. Gutierrez-Osuna is a recipient of the National Science Foundation
CAREER Award for his research on machine olfaction with chemical sensors
arrays. His research interests include pattern recognition, biological
cybernetics, sensor instrumentation, speech-driven facial animation,
and mobile robotics.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
On the Establishment of Distinct Identities in Overlay Networks
Dr. Rida Bazzi,
Associate Professor,
Arizona State University
4:10 p.m., Monday October 17, 2005
Room 124, Bright Building
Abstract
We study ways to restrict or prevent the damage that can be caused in a
peer-to-peer network by corrupt entities creating multiple pseudonyms
(Sybil attack). We show that it is possible to remotely issue certificates
that can be used to test the distinctness of identities. To our knowledge,
this is the first work that shows that remote anonymous certification of
identity is possible under adversarial conditions. Our certification protocols
are based on geometric techniques that establish location information in a
fault-tolerant and distributed fashion. They do not rely on a centralized
certifying authority or infrastructure that has direct knowledge of entities
in the system, and work in Euclidean or spherical geometry of arbitrary
dimension. Our protocols tolerate corrupt entities, including corrupt
certifiers as well as collusion by certification applicants and certifiers.
We consider both broadcast and point-to-point message passing models.
Biography
Rida Bazzi is an associate professor in the Computer Science and Engineering
department at Arizona State University. He received his PhD and
M.Sc. degrees in Computer Science from the Georgia Institute of Technology in
1994. His research is in the general area of reliability in distributed
systems including fault tolerance and security. Professor Bazzi was a
recipient of an NSF CAREER award.
CPSC 681 Faculty Contact:
Jennifer Welch
(welch [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Developing Mobile Applications in the .NET Compact Framework
Dr. Bradley Jensen,
Microsoft
4:10 p.m., Monday October 24, 2005
Room 124, Bright Building
Abstract
This talk is oriented towards those interested in a high level
overview of the Microsoft .NET Compact Framework and developing for
mobile devices. An introduction to the basic concepts of the .NET
Compact Framework will be presented and it will be shown how the
standard .NET Compact Framework integrates with mobile devices and
supports mobile application development. Attendees will learn the
basics of working with compact user interfaces, how to store and
retrieve data on the compact device, and how to deploy mobile
applications. This talk will be of interest to those working in
embedded systems.
Biography
Bradley K. Jensen received his Ph.D. in Business Computer Information
Systems from the University of North Texas (UNT), with majors in
Business Computer Information Systems and Computer Science. He is a
Microsoft Corporation Academic Relationship Manager responsible for
Texas, Oklahoma, Arkansas, and Louisiana. Prior to Microsoft, he was
an Assistant Professor in Information Technology and Decision Sciences
and Assistant Director of the Information Systems Research Center at
UNT, and was also President of JMC Consulting Services, an executive
management consulting firm which provides strategic and tactical IT
consulting services. His research interests include privacy and
security, networking, human factors, e-commerce, and document
management. Dr. Jensen has been an executive and consultant with more
than 20 years of sales, marketing, and IT experience with several
Fortune 100 companies.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Multi Curve Resolution and trilinear methods applied to low cost chemical sensing:
options for blind source separation and drift correction
Dr. Santiago Marco,
Associate Professor, University of Barcelona
4:10 p.m., Wednesday November 2, 2005
Room 124, Bright Building
Abstract
Low cost chemical solid-state sensors or miniature spectrometers open new ways for
sensing in the field. In the talk, chemical sensing signal processing using bilinear
and trilinear models will be introduced. IMS (Ion Mobility Spectrometers) is an
established technology for the prevention of terrorist acts or law enforcement,
recently miniature ion mobility spectrometers have been presented in the literature.
At the talk the scaling behaviour of miniature IMS will be discussed and the options
for spectra signal processing will be introduced. In particular some space will be
devoted to the options offered by MCR (Multi Curve Resolution) for blind source
separation in comparison with SIMPLISMA or PCA. The conditions imposed will be
discussed and compared to those used in ICA. Results will show how MCR is able to
recover concentration profiles in a variety of settings of noise levels and peak
overlapping. Finally, It is well known that drift is always an issue in low cost
chemical sensing. In the talk a new procedure for drift counteraction based on
multi-way methods will be introduced and compared with component correction (CC).
Biography
Dr. Santiago Marco is associate Professor (Profesor Titular) at the Departament
d'Electronica of Universitat de Barcelona since 1995.
He received the degree in Physics from the Universitat
de Barcelona in 1988. From 1989 to 1990 he was working in the electro-optical characterization of
deep levels in GaAs. From 1990 to 1993 he was regular visitor of the Centro Nacional de
Microelectronica, Bellaterra, Spain. In 1993, he received his Ph.D. (honor award) degree from
the Departament de Fisica Aplicada i Electronica, Universitat de Barcelona, for the development
of a novel silicon sensor for in-vivo measurements of the blood pressure. In 1994, he was a
post-doc researcher at the Department of Electronic Engineering, Universita di Roma 'Tor Vergata',
working in Data Processing for Artificial Olfaction. He has published about 50 papers in
scientific journals and books, as well as more than 100 conference papers. His current research
interests are twofold: chemical instrumentation based on intelligent signal processing
and microsystem modeling.
CPSC 681 Faculty Contact:
Ricardo Gutierrez-Osuna
(rgutier [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Z-MAC: Hybrid MAC for Wireless Sensor Networks
Dr. Injong Rhee,
Associate Professor,
North Carolina State University
4:10 p.m., Wednesday November 9, 2005
Room 124, Bright Building
Abstract
In this talk, we present the design, implementation and performance
evaluation of a hybrid MAC protocol, called Z-MAC, for wireless sensor
networks that combines the strengths of TDMA and CSMA while offsetting
their weaknesses. Like CSMA, Z-MAC achieves high channel utilization
and low-latency under low contention and like TDMA, achieves high
channel utilization under high contention and reduces collision among
two-hop neighbors at a low cost. A distinctive feature of Z-MAC is
that its performance is robust to synchronization errors, slot
assignment failures and time-varying channel conditions; in the worst
case, its performance always falls back to that of CSMA. Z-MAC is
implemented in TinyOS.
This work is a result of collaboration with the following graduate
students: Ajit Warrior, Mahesh Aia and JK Min.
Biography
Injong Rhee received his PhD in Computer Science from the University
of North Carolina at Chapel Hill in 1994. After several years of
postdoctoral experience in Warwick University, UK and Emory
University, USA, we joined the Computer Science Department of North
Carolina State University in 1997 where he is currently associate
professor. From 2000 to 2002, Injong was on leave from his university
position to found Togabi Technologies, INC, a San Diego based startup
that specializes in developing and marketing wireless multimedia
applications and services for wireless Internet service providers. He
served as CTO/CEO of the company before returning to his academic
position in 2003. His main research area is in computer networks and
he is interested in developing scalable and practical network
protocols for congestion control, multimedia networking and wireless
networks.
He is a recipient of NSF CAREER award, 1998.
CPSC 681 Faculty Contact:
Jennifer Welch
(welch [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Combining Game-Theoretic Techniques and Social Network Analysis for Asymmetric Threat Detection
Dr. Timothy Darr,
Technical Team Lead,
21st Century Technologies, Inc.
4:10 p.m., Wednesday November 16, 2005
Room 124, Bright Building
Abstract
We present an approach for identifying and responding to asymmetric
threats against politically, culturally, and socially diverse
adversaries. This approach integrates state-of-the-art game theory
and simulation research with proven, powerful graph-matching and
Social-Network Analysis (SNA) methods to model and detect asymmetric
threat activities through multi-agent adversarial games.
Innovative aspects of this approach include: (1) culturally based
game-theoretic models of the asymmetric threat, (2) empirical
game-theoretic analysis of the asymmetric threat, (3) approximate
solutions for intractable games identifying plausible threat
strategies and profiles, (4) graph-based threat patterns and SNA
signatures derived from the game-theoretic simulation and analysis,
and (5) analysis of politically, socially, and culturally diverse
adversaries. This approach provides sophisticated technology to a
wide audience of potential users for enhanced national security
against asymmetric threats resulting in significant improvements in
our response capabilities against politically, socially, and
culturally diverse adversaries. Additionally, this approach will
have a wide range of important defense and commercial applications
including terrorist threat detection, industrial espionage detection,
financial fraud detection, and business intelligence.
Biography
Tim Darr received his B.S.E. in Computer Engineering, M.S.E. in Computer
Science and Engineering, and Ph.D. in Computer Science from the University
of Michigan. While at the University of Michigan, he studied at the
Artificial Intelligence Lab, and held a post-doctoral appointment in the
School of Information. Past research interests include distributed
design, concurrent engineering and constraint-satisfaction. Current
research interests include knowledge representation and acquisition,
graph theory, SNA, and agent-based systems. Dr. Darr's publications have
appeared in IEEE Expert, AI EDAM, the AI in Design Conference, and the
ASME Design Engineering Technical Conference. His research has also appeared
in several invited workshops, and he has co-authored chapters in books on
concurrent engineering and expert systems. In addition, he was editor for
a special issue devoted to configuration design for the journal AI EDAM.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Methods and Tools for Knowledge-Based Applications
Dr. Perakath Benjamin,
Knowledge Based Sysstems, Inc.
4:10 p.m., Monday November 21, 2005
Room 124, Bright Building
Abstract
The seminar will describe innovative methods and tools for building knowledge-based
applications. Topics covered will include
- Methods and tools for knowledge management (including ontology capture and
analysis, knowledge representation, knowledge maintenance, and knowledge delivery).
- Ontology driven methods for information integration.
- Knowledge-based application examples.
Biography
As the Vice President for Research and Development at Knowledge Based Systems, Inc. (KBSI),
Dr. Perakath Benjamin manages and directs the R&D activities at KBSI. He has over 18 years
of professional experience in the design, development, and deployment of advanced systems
and applications. Dr. Benjamin has a Ph.D. in Industrial Engineering from Texas A&M
University. Dr. Benjamin has been responsible for the development of innovative methods
and tools that are being applied extensively throughout industry and government.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
How (not) to Crash a Dinner Party
Dr. Scott Pike,
Assistant Professor,
Texas A&M University
4:10 p.m., Wednesday November 30, 2005
Room 124, Bright Building
Abstract
We present theoretical and practical techniques for isolating partial
failures in distributed systems to small, local neighborhoods of impact.
Specifically, we present scalable algorithms for minimizing the impact of
crash faults in a broad class of static resource allocation problems. Our
particular lens of investigation focuses on the generalized dining
philosophers problem as a fundamental abstraction for distributed resource
allocation. Within this domain of inquiry, we construct fault-tolerant
algorithms that restrict the scope of failures precipitated by crash faults.
Additionally, we prove impossibility results for our techniques and
optimality results for our constructions under different models of mutual
exclusion and process synchronization. An overarching theme of this work is
the central role of locality in the construction of scalable algorithms that
support the survivability and availability of distributed systems.
Biography
Scott Pike is an Assistant Professor at Texas A&M University. He received
his Ph.D. and M.S. degrees in computer science from the Ohio State
University in 2004 and 2000, respectively, preceded by a B.A. in philosophy
from Yale University in 1996. His research interests focus on distributed
computing and software engineering, and, more concretely, on scalable
approaches to building agile, adaptive, and survivable components for
distributed systems.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
How Difficult is it to Take a Snapshot?
Dr. Faith Fich,
Professor,
University of Toronto
4:10 p.m., Wednesday January 18, 2006
Room 124, Bright Building
Abstract
The atomic snapshot object is an important and well-studied primitive
in distributed computing that allows processes to obtain a
consistent view of an entire block of shared memory, even if updates
are being performed concurrently. This talk will describe
applications of this object, present some implementations of it from
registers in both asynchronous and synchronous distributed systems,
and discuss some recent lower bounds.
Biography
Faith Ellen Fich is a Professor of Computer Science at the University
of Toronto. She received her Ph.D. in Computer Science from the
University of California, Berkeley, in 1982. From 1983 to 1986, she was
an assistant professor in the Computer Science Department at the
University of Washington. Then she joined the Department of Computer
Science at the University of Toronto. Professor Fich is also a member
of the Computing Research Association Committee for Women in Computing
Research and is the director of the Canadian Distributed Mentor Project.
Her research is in the area of complexity theory. She particularly
likes to prove lower bounds on the complexity of distributed computing
and data structure problems, with the goal of understanding how
parameters of various models affect their computational power.
CPSC 681 Faculty Contact:
Jennifer Welch
(welch [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Scalable Algorithms and Implementations, with
Application to the Analysis of Gene Co-Expression Data
Dr. Michael Langston,
Professor,
University of Tennessee
4:10 p.m., Monday January 23, 2006
Room 124, Bright Building
Abstract
In this talk I will discuss algorithmic methods based on the theory of
fixed-parameter tractability. Efficient techniques for problem reduction
and massively parallel algorithms for enumeration and search will be discussed.
The importance of maintaining a balanced decomposition of the search space
turns out to be critical to achieving scalability. Applications to
high-throughput computational biology will be stressed, with the analysis
of microarray data serving as a prime example. Using mRNA samples obtained from
recombinant inbred Mus musculus strains, we solve immense instances of the
clique problem to derive sets of putatively co-regulated genes. Techniques for
dealing with noisy data are important concerns. The depth of quantitative
genetic analysis we can perform is vastly enhanced by combining these results
with knowledge of cis-regulatory elements, ontological classifications, and
causal structures that may be imposed with quantitative trait locus mapping.
A long-term goal is gene regulatory network discovery.
Biography
Mike Langston received the PhD in Computer Science from Texas A&M University in 1981,
under the most excellent mentorship of Don Friesen. He currently holds the
position of Professor of Computer Science at the University of Tennessee, and
regularly consults in the Life Sciences, Chemistry, Computer Science and Mathematics
Divisions at Oak Ridge National Laboratory. His research is focused primarily on
efficient algorithm design, analysis and high performance implementations, with a
special emphasis on applications to computational biology. He has authored over
180 refereed publications. His research has been funded by the National Science
Foundation, the Department of Defense, the Department of Energy, the National
Institutes of Health, and a variety of other federal agencies. He has received
numerous awards, most recently the Distinguished Service Prize from the Association
for Computing Machinery Special Interest Group on Algorithms and Computation
Theory, and the Chancellors Award for Research Creativity at the University of
Tennessee.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Exploiting application parallelism with the Cell Broadband Engine
heterogeneous chip-multiprocessor
Dr. Michael Gschwind,
IBM Master Inventor and Power Architect,
IBM Thomas J. Watson Research Center
4:10 p.m., Wednesday February 1, 2006
Room 124, Bright Building
Abstract
The Cell Broadband Engine was designed to provide an order of magnitude
increase in computing performance over desktop systems shipping in 2005.
To accomplish this goal in the presence of the diminishing returns of
investing in uni-thread performance, the key was to address next
generation architecture challenges. Cell addresses the major pressing
issues in modern architecture -- the memory wall, the power wall, and
the frequency wall -- by shifting the compute paradigm from a uni-processor
design to an efficient chip multiprocessor. The Cell Broadband Engine
implements a heterogenous chip multiprocessor to deliver a quantum leap
in performance by exploiting application parallelism at all levels, i.e.,
thread level parallelism, instruction level parallelism and data-level
parallelism. .
The main source of computing power in the Cell Broadband Engine are 8
Synergistic Processor Elements (SPEs) based on a novel SIMD architecture.
SPEs support instruction-level parallelism with a statically scheduled
microarchitecture, and data-level paralel parallelism with a pervasively
data parallel SIMD architecture. The Synergistic Processor Architecture is
based on a streamlined and optimized architecture following RISC principles
to implement efficient high-performance pirmitives and use the compiler to
layer other computation often implemented in hardware. By streamlining the
architecture and exploiting compiler technology to move complexity from
runtime to compile time, core efficiency was dramatically increased in terms
of power and area usage. This in turn allowed to place one IBM 64-bit
Power Architecture(TM) with VMX and 8 SPE cores on a single chip to
provide thread-level parallelism to scalar and data-parallel programs.
Based on these choices, we will discuss how compiler technology and
streamlined hardware allow to deliver superior performance in Cell.
Biography
Dr. Michael Gschwind is an IBM Master Inventor, an IBM Power architect and
a logic design lead for a future IBM System. He was one of the initiators
and a leading contributor to the Cell Broadband Engine system architecture
definition as well as a lead architect of the Synergistic Processor
architecture. During the definition of the Synergistic Processor
architecture, Michael also developed the first Cell Broadband Engine
compiler. Michael joined the IBM TJ Watson Research Center, Yorktown
Heights, NY, in 1997. He has held leadership positions in several seminal
projects, including the DAISY dynamic compilation project where he was a
lead architect for the BOA high-frequency statically scheduled architecture,
and was a leading contributor to the development of pioneering dynamic
compilation techniques. Michael was also a leading contributor to seminal
work on power/performance trade-offs in microprocessor designs which
formalized the futility of the frequency-centric uniprocessor design
approach used in the industry at the time, an insight that had already
guided the design of the Cell Broadband Engine.
Michael's contributions to IBM systems and technology have been recognized with
several corporate awards. In addition to his contributions to the design and
implementation of IBM systems, he is the author of over 75 papers, covering
hardware/software co-design, compiler technology, multimedia processing, and
high-performance computer architecture, and has received key patents for his
inventions in these areas. In addition to his corporate contributions, Michael
has been a faculty member at Technische Universitt Wien, Vienna, Austria, and
a visiting faculty member at Princeton University where he has taught classes on
advanced computer architecture. Michael received PhD and MS degrees in
computer science from Technische Universitt Wien, Vienna, Austria.
CPSC 681 Faculty Contact:
Lawrence Rauchwerger
(rwerger [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Archetest: A Tool for Model-Based Test Generation
Dr. Clay Williams,
Manager, Software Quality and Testing,
IBM Thomas J. Watson Research Center
4:10 p.m., Monday February 6, 2006
Room 124, Bright Building
Abstract
The automatic creation of test cases from models or specifications of a
system is a long-standing area of research within the software engineering
community. The two major approaches are test derivation from algebraic
specifications, and test generation from models, which are typically based
on finite state machines. This talk will start by discussing common
weaknesses in algebraic and finite state-based approaches, and will next
propose a new paradigm for generating test cases. At the heart of this
paradigm are three innovations: a precise form of use case modeling, a
novel approach for automatically creating testing goals based on model
analysis, and a new approach to test case generation based on AI planning.
These three areas will be discussed in detail using a consistent example
to illustrate technical highlights. The talk will conclude with a
discussion of extensions and related research.
Biography
Clay Williams is a Research Staff Member and the Manager of the Software
Quality and Testing Research group at the IBM Watson Research Center.
He has a PhD in computer science from Texas A&M University. His
scientific interests include software engineering and software
quality, complex systems, and bioinformatics.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Learning about the Outside World, Trapped within Your Brain
Dr. Yoonsuck Choe,
Assistant Professor of Computer Science, Texas A&M University
4:10 p.m., Wednesday February 15, 2006
Room 124, Bright Building
Abstract
What is available to developmental programs in autonomous mental
development, and what should be learned at the very early stages of mental
development? Our observation is that sensory and motor primitives are the
most basic components present at the beginning, and what developmental
agents need to learn from these resources is what their internal sensory
states stand for. In this talk, we investigate the question in the context
of a simple biologically motivated visuomotor agent. We observe and
acknowledge, as many other researchers do, that action plays a key role in
providing content to the sensory state. We propose a simple, yet powerful
learning criterion, that of invariance, where invariance simply means that
the internal state does not change over time. We show that after
reinforcement learning based on the invariance criterion, the property of
action sequence based on an internal sensory state accurately reflects the
property of the stimulus that triggered that internal state. That way, the
meaning of the internal sensory state can be firmly grounded on the
property of that particular action sequence. The idea was tested on
natural images with varying degrees of noise, and the results confirmed
our main thesis. We expect the framing of the problem and the proposed
solution presented in this work to help shed new light on autonomous
understanding in developmental agents.
This is joint work with S. Kumar Bhamidipati and Stuart B. Heinrich.
Note: This talk presents significantly new results compared to the
681 talk I gave in Fall 2003.
Biography
Yoonsuck Choe is an assistant professor in the Department of Computer
Science at Texas A&M University. He is also serving as the director of the
Brain Networks Laboratory in the department. He received his B.S. degree
in Computer Science from Yonsei University (Korea) in 1993, and his M.S.
and Ph.D. degrees in Computer Sciences from the University of Texas at
Austin in 1995 and 2001. His current research areas include computational
neuroanatomy, computational modeling of the brain, computational and
biological vision, thalamocortical basis of analogy and cortical
integration, and autonomous semantics in sensorimotor agents.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Collaborative Systems: Some Experiences and Lessons
Dr. Du Li ,
Assistant Professor of Computer Science, Texas A&M University
4:10 p.m., Monday February 20, 2006
Room 124, Bright Building
Abstract
The whole human society is a collaborative system. People interact, work, play, fight, and
share information with each other as a necessity of life. Today human beings are increasingly
more expensive resources than machines. Groupware in general aims to make a "better" utilization
of human resources such that some collaboration activities are more productive and successful.
The design and evaluation of groupware must consider both social and technical factors as well
as their subtle interaction. This talk tells a story of several groupware projects that the speaker
and his students experienced. Some of the lessons should be of common interest to faculty and
students in related and other areas, simply because any professional stakeholder or activity is
contextualized in some collaborative systems in the small and in the large.
Biography
Dr. Du Li joined the Department of Computer Science, Texas A&M University as an Assistant Professor
in 2000. His research focuses on collaborative systems, addressing a wide spectrum of systems,
algorithms, and user interfaces issues. He received a NSF CAREER award in 2002 and has been well
established in his research field, computer-supported cooperative work (CSCW). For more
information, visit http://www.csdl.tamu.edu/~lidu.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Robot Cameras for Rediscovery of Ivory Billed Woodpecker
Dr. Dezhen Song ,
Assistant Professor of Computer Science, Texas A&M University
4:10 p.m., Monday March 20, 2006
Room 124, Bright Building
Abstract
Our broad goal is to combine robotics, cameras, sensors, actuators, and
human input to observe and record detailed animal behavior in remote
settings.
I'll describe a new project that is just getting started: we are
assisting the Cornell team that is searching the Arkansas Big Woods
for the elusive Ivory Billed Woodpecker, thought extinct since 1940s
but recently sighted. Our goal is defined by the title above.
I'll present recent results on robots collaboratively controlled by
humans via networks and describe the issues most relevant to computer
vision. The NSF project will investigate the algorithmic foundations
for such observatories: new metrics, models, data structures, and
algorithms, that will comprise a robust, mathematical framework for
collaborative observation. Newly available robotic cameras offer pan,
tilt, and extreme zoom capabilities with built-in network servers at
low cost. These cameras motivate the Single Frame Selection (SFS)
problem, where n users share control of a single robotic
camera. I'll present several algorithms, O(n^2 m) for a set of m
zoom levels, and O((n + 1/epsilon^3) log^2 n) for an infinite set
of zoom levels. The algorithms can be distributed to run in O(nm)
time at each client and in O(nlogn) time at the server. The new
project will produce working prototypes that will be accessible via
the internet to scientists, students, and the public worldwide. Our
first online prototype is available for public use at:
http://www.c-o-n-e.org/
Ken Goldberg, Judith Donath, Sariel Har-Peled, Vladlen Koltun, and Frank
van der Stappen have contributed to this work.
Biography
Dezhen Song is an Assistant Professor with Texas A&M University,
College Station, Texas, TX, USA. Song received his Ph.D. in 2004 from
University of California, Berkeley. Song's primary research area is
networked robotics, computer vision, optimization, and stochastic
modelling. He received the Kayamori Best Paper Award of the 2005 IEEE
International Conference on Robotics and Automation (With J. Yi and S.
Ding). http://faculty.cs.tamu.edu/dzsong
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Bandwidth Estimation Using End-to-End Packet-Train Probing: Stochastic Foundation
Dr. Xiliang Liu,
City University of New York
4:10 p.m., Monday April 3, 2006
Room 124, Bright Building
Abstract
In recent years, bandwidth estimation based on end-to-end packet-train
probing has attracted significant research interest. A number of
techniques have been proposed to measure the bottleneck bandwidth
and cross-traffic rate of an Internet path; however, most of these
techniques are based on a fluid queuing model that assumes
deterministic cross-traffic arrival at each router and a single-hop
network path. In this talk, we present a novel approach to bandwidth
estimation that models both bursty (i.e., stochastic) traffic arrival
and cases of arbitrarily routed flows in general multi-hop networks.
We show that the traditional fluid model usually does not serve as
a valid first-order approximation to the stochastic response curve of
an end-to-end path and that this difference can cause a significant
measurement bias to some of the existing techniques. We also show that
a certain portion of the deviation between stochastic and fluid models
(and the resulting measurement bias) vanishes as packet-train length
increases. We conclude the talk by introducing a new methodology for
measuring the bottleneck link capacity and overcoming some of the
limitations of previous fluid-based approaches.
Biography
Dr. Xiliang Liu received his Ph.D. in computer science from The City
University of New York in 2005. His current research interests include
network measurement and monitoring, bandwidth estimation, overlay
networks, and stochastic modeling.
CPSC 681 Faculty Contact:
Dmitri Loguinov
(dmitri [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Randomized Motion Planning:
From Intelligent CAD to Computer Animation to Protein Folding
Nancy Amato,
Professor of Computer Science, Texas A&M University
4:10 p.m., Monday April 10, 2006
Room 124, Bright Building
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, a single
class of planners, called probabilistic roadmap methods (PRMs), have
proven effective on problems from all these domains. Strengths of PRMs,
in addition to versatility, are simplicity and efficiency, even in
high-dimensional configuration spaces.
In this talk, we describe the PRM framework and give an overview of
several PRM variants developed in our group. We describe in more detail
our work related to virtual prototyping, computer animation, 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 computation animation, we describe new
PRM-based techniques for planning for deformable objects and for planning
sophisticated group behaviors (flocking and herding). Finally, we describe
our application of PRMs to protein folding where we construct a map of
the protein's potential landscape which can be used to generate transitional
motions of a protein to the native state from unstructured conformations
or between specified conformations. More information regarding our work,
including movies, can be found at
http://parasol.tamu.edu/groups/amatogroup/
Biography
Nancy M. Amato is a professor of Computer Science at Texas A&M University.
She received B.S. and A.B. degrees in Mathematical Sciences and Economics,
respectively, from Stanford University, and M.S. and Ph.D. degrees in
Computer Science from UC Berkeley and the University of Illinois at
Urbana-Champaign, respectively. She was an AT&T Bell Laboratories PhD
Scholar, she is a recipient of a CAREER Award from the National Science
Foundation. She served as an Associate Editor of the IEEE Transactions
on Robotics and Automation, is currently an Associate Editor of the
IEEE Transactions on Parallel and Distributed Systems, she serves on
review panels for NIH and NSF, and she regularly serves on conference
organizing and program committees. She is a member of the Computing
Research Association's Committee on the Status of Women in Computing
Research (CRA-W) and she co-directs the CRA-W's Distributed Mentor Program
(http://www.cra.org/Activities/craw/dmp/).
Her main areas of research focus are motion planning, computational
biology and geometry, and high-performance computing. Current projects
include the development of a new technique for approximating protein
folding pathways and energy landscapes, and STAPL, a parallel C++ library
enabling the development of efficient, portable parallel programs.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
C++ Library for Multi-Core Programming, or Why Threads Are a Bad Way to Thread a Program
Dr. Arch D. Robison,
Intel Corporation
4:10 p.m., Wednesday April 12, 2006
Room 124, Bright Building
Abstract
With multi-core microprocessors becoming ubiquitous, parallel programming for shared-memory
machines must evolve from an esoteric specialty to mainstream practice. Though threads are
a popular means of shared-memory parallel programming, they are a low-level unstructured
construct whose undisciplined use can cause both correctness and performance problems. This
talk explains the performance problems, and a solution based on generic programming with a
C++ template library. The programmer specifies patterns of logical tasks, not threads, and
lets the library schedule the tasks onto processors. The library can deliver a higher level
of abstraction and performance than typical hand-threaded code.
Biography
Arch D. Robison was the lead developer for KAI C++. Before that, he worked at Shell on
massively parallel codes for seismic imaging. He received his Ph.D. from the University of
Illinois. He is currently working on a template-based library for multi-core programming.
CPSC 681 Faculty Contact:
Lawrence Rauchwerger
(rwerger [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Secure Cluster Design
Dr. Eun Jung Kim,
Assistant Professor of Computer Science, Texas A&M University
4:10 p.m., Wednesday April 19, 2006
Room 124, Bright Building
Abstract
Widespread use of cluster systems in a diverse set of applications has
spurred significant interest in designing such servers, considering
performance, scalability, and Quality-of-Service (QoS). However, numerous
security loopholes of cluster servers come to the forefront and
subsequently the design of secure clusters have recently surfaced as a
critical issue.
In this talk, first I will introduce these vulnerabilities from three
classical security aspects: availability, confidentiality, and
authentication in the InfiniBand Architecture (IBA) framework that may
emerge as the de facto standard for designing future system area networks
(SANs) for clusters. For better availability of IBA, we propose an
efficient implementation method using trap messages. For confidentiality,
we encrypt only secret keys to minimize performance degradation. I also
present a new authentication mechanism that treats the Invariant CRC
(ICRC) field as an Authentication Tag. Finally I will present a
deterministic distance packet marking (DDPM) scheme to identify the source
nodes generating spoofed IP packets in cluster interconnects. Our
simulation results indicate that our methods enhance security in IBA with
marginal performance overhead.
Biography
Dr. Eun Jung Kim is an assistant professor in the Department of Computer
Science at Texas A&M University. Her research interests include Computer
Architecture, Power Efficient Systems, Parallel/Distributed Systems,
Cluster Computing, and Security.
She received a Ph. D degree in the Department of Computer Science and
Engineering at the Pennsylvania State University, an MS degree in Computer
Science from Pohang University of Science and Technology, Korea and a BS
degree in Computer Science from Korea Advanced Institute of Science and
Technology, Korea. More information about her research is available at
http://faculty.cs.tamu.edu/ejkim.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
CPSC 681 Graduate Seminar:
Associated Types and Constraint Propagation --
Improving Object-Oriented Generics
Dr. Jaakko Jarvi,
Assistant Professor of Computer Science, Texas A&M University
4:10 p.m., Monday May 1, 2006
Room 124, Bright Building
Abstract
Support for object-oriented programming has become an integral part of
mainstream languages, and more recently generic programming has gained
widespread acceptance as well. A natural question is how these two
paradigms, and their underlying language mechanisms, should interact.
One particular design option, that of using subtyping to constrain the
type parameters of generic functions, has been chosen in the generics
of Java and C#. Certain shortcomings have previously been identified
in using subtyping for constraining parametric polymorphism in the
context of generic programming. To address these, we propose extending
object-oriented interfaces and subtyping to include associated types
and constraint propagation. Associated types are type members of
interfaces and classes. Constraint propagation allows certain
constraints on type parameters to be inferred from other constraints
on those parameters and their use in base class type expressions.
We present these extensions in the context of C#, describing a
translation of the extended features to C#, and providing a formalism
proving their safety. The formalism is applicable to other mainstream
object-oriented languages supporting F-bounded polymorphism, such as Java.
Biography
Jaakko Jarvi is an assistant professor in the Department of Computer Science
at Texas A&M University. He has a Ph.D. in Computer Science from the University
of Turku, Finland. His research interests include generic programming,
programming languages, and software construction in general. He actively
participates in the C++ standards committee and is a contributing member of
the C++ Boost community. See http://faculty.cs.tamu.edu/jarvi for more
information.
CPSC 681 Faculty Contact:
Nancy Amato
(amato [at] cs.tamu.edu)
