Kevin Warwick is a Professor of Cybernetics at the University
of Reading, UK where he carries out research in artificial intelligence,
control, robotics and cyborgs. He is also Director of the University
TTI Centre, which links the University with SME's and raises over
£2 million each year in research income.
Kevin was born in Coventry, UK and left school to join British
Telecom, at the age of 16. At 22 he took his first degree at Aston
University, followed by a PhD and research post at Imperial College,
London. He subsequently held positions at Oxford, Newcastle and
Warwick Universities before being offered the Chair at Reading,
at the age of 32.
As well as publishing over 400 research papers, Kevin has appeared,
on 3 separate occasions, in the Guinness Book of Records for his
robotics and Cyborg achievements. His paperback 'In the Mind of
the Machine' considered the possibility of machines in the future
being more intelligent than humans. His recent Cyborg experiments
however led to him being featured as the cover story on the US
Kevin has been awarded higher doctorates both by Imperial College
and the Czech Academy of Sciences, Prague. He was presented with
The Future of Health Technology Award in MIT and was made an Honorary
Member of the Academy of Sciences, St. Petersburg. In 2000 Kevin
presented the Royal Institution Christmas Lectures, entitled "The
Rise of the Robots".
Keynote Title: "Robot-Human Interaction: practical experiments
with a cyborg and a multsensory robot head"
In this presentation Kevin will describe the Cyborg experiments
carried out so far in which his nervous system was connected directly
to the internet by means of implant technology. With such an interface
it is shown how various robotic devices can be controlled, remotely
by an individual, through their own neural signals. Interaction
with a robot head, named Morgui, will also be described, not only
is this robot useful as a testbed for multisensor integration
but it is also interesting to examine how humans respond to a
robot that may not appear to be immediately friendly.
Bio of Prof. Kurosh Madani
Kurosh Madani received his Ph.D. degree in Electrical Engineering
and Computer Sciences from University PARIS XI (PARIS-SUD), Orsay,
France, in 1990. From 1989 to 1990, he worked as assistant professor
at Institut d’Electronique Fondamentale (Institute of Fundamental
Electronics) of PARIS XI University, Orsay, France. In 1990, he
joined Creteil-Senart Institute of Technology of University PARIS
XII – Val de Marne, Lieusaint, France, where he worked from 1990
to 1998 as assistant professor. In 1995, he received the DHDR
Doctorate degree (senior research doctorate degree) from University
PARIS XII – Val de Marne. Since 1998 he works as Chair Professor
in Electrical Engineering of Senart Institute of Technology of
University PARIS XII – Val de Marne. Since 1992 he is head of
Intelligence in Instrumentation and Systems Laboratory of PARIS
XII – Val de Marne University located at Senart Institute of Technology.
He has worked on both digital and analog implementation of processors
arrays for image processing by stochastic relaxation, electro-optical
random number generation, and both analog and digital Artificial
Neural Networks (ANN) implementation. His current research interests
include large ANN structures behavior modeling and implementation,
hybrid neural based information processing systems and their software
and hardware implementations, design and implementation of realtime
neuro-control and neural based fault detection and diagnosis systems.
Since 1996 he is a permanent member (elected Academician) of International
Informatization Academy. In 1997, he was also elected as Academician
of International Academy of Technological Cybernetics.
Keynote Title: "Real-world Industrial Applications of Artificial Neural
Networks, Illusion or Reality?"
Inspired from biological nervous systems and brain structure,
Artificial Neural Networks (ANN) could be seen as information
processing systems, which allow elaboration of many original techniques
covering a large field of applications.
Over the past decades, new approaches based on Artificial Neural
Networks have been proposed to solve problems related to optimization,
modeling, decision making, control, classification, data mining,
nonlinear functions (behavior) approximation etc.. Among their
most appealing properties, one can quote their learning and generalization
capabilities. If, over past decades, a large number of works have
concerned theoretical and implementation aspects of ANN, only
a few are available with reference to their real world industrial
The main goal of this paper is to present, through some of main
ANN models and based techniques, their real application capability
in real world industrial dilemmas. Several examples through industrial
and real world applications will be presented and discussed covering
"intelligent adaptive control", "fault detection and diagnosis",
"decision support", "complex systems identification" and "image
Dr.-Ing. F. Wolfgang Arndt
Bio of Prof. Dr.-Ing. F. Wolfgang Arndt
Dr.-Ing. F. Wolfgang Arndt got his Dipl.-Ing. in Telecommunications
in 1964 at the RWTH (Rheinisch-westfälische Technische Hochschule)
Aachen, Germany. He concluded, in 1968, his PhD in Computer Science
at the ESE (Ecole Supérieure d´Electricité)
Paris – Université de Paris, Faculté des Sciences.
Between 1969 and 1974 he was project manager in the area of process
automation at AEG – Telefunken Konstanz, Germany. During
four years, starting in 1975, he was Head of the group for process
automation in chemistry at the Department of Chemistry of the
University of Konstanz. Between 1979 and 1980 he was a Professor
in the Department of Computer Science at FHTE (Fachhochschule
für Technik, Esslingen) Germany. Currently, Prof. Dr.-Ing.
F. Wolfgang Arndt is a Professor in the Department of Computer
Science at the FHK (Fachhochschule Konstanz). Since 1985, he is
the Director of the Transferzentrum for System and Software Engineering
Konstanz of the Steinbeis Foundation for Industrial Cooperation,
where he is responsible for R&D projects with industry (AUDI,
BMW, VW, AEG, MTU, Siemens, etc.).
Keynote Title: The Digital Factory
Planning and Simulation of Production Lines in Automotive Industry
Automotive industry is in many areas of automation a forerunner.
This is due to some special characteristics of this industrial
area. To make profit each type of a car must be produced in a
great number of pieces, which makes it worth to automate production
as much as possible. The competition on the automotive market
is very hard and forces low retail prices. Larger design changes
of one type of a car necessitate a complete rebuilt of the production
line in the body shop and partially in the assembly area.
But changes of a production line are expensive, because a lot
of special equipment is needed and the installation of new equipment
is very labour intensive. Investments available to rebuild or
to change production lines are limited. Therefore any modification
of a production line must be planed very carefully. The planning
procedure involves a lot of different departments and is a relatively
time consuming task. On the other hand before the beginning of
the planning activities the day, when the new production has to
be started, the date of SOP (start of production) is defined .
All planning suffers therefore by a limited amount of investments
and a lack of time to do detailed planning. To overcome these
problems intensive engineering is done using simulation tools.
The presentation will first outline the traditional way planning
is done and give an example how the planning sequence is executed
in automotive industry. Then an overview is given of the possibilities
of simulation and the objectives for using this technique in the
automotive area. The features of some simulation tools will be
explained and an introduction into the simulation of material
flow on a production line in the body shop will be given using
the simulation tool eMPlant. Results of the use of this tool will
be presented. The final goal of all activities in this area is
the digital factory, a simulation of all activities, which are
taking place in a real factory. But the term digital factory means
more than only making use of simulation techniques. It imposes
new types of organisation and of collaboration. It will change
significantly the way planning is done in the production area.
During the final part some special applications will be explained
and demonstrated in real time as simulation techniques for robots,
simulation of transport systems and of car painting.
Bio of Dr. Albert Cheng
Dr. Albert M. K. Cheng is an Associate Professor in the Department
of Computer Science at the University of Houston, where he is
the founding Director of the Real-Time Systems Laboratory. He
has served as a technical consultant for several organizations,
including IBM, and was also a visiting faculty in the Departments
of Computer Science at Rice University and at the City University
of Hong Kong.
He is the author/co-author of over sixty refereed publications
in IEEE Transactions on Software Engineering (TSE), IEEE Transactions
on Knowledge and Data Engineering (TKDE), Real-Time Systems Symposium
(RTSS), Real-Time Technology and Applications Symposium (RTAS),
and other leading conferences. He is serving and has served on
the program committees of many conferences in his areas of research.
He is a frequent reviewer for the IEEE-CS Publications Office
as well as for many international journals and conferences, One
of his recent work presents a timing analysis of the X-38 Space
Station Crew Return Vehicle Avionics, which contains a fault-tolerant
Dr. Cheng has received numerous awards, including the National
Science Foundation Research Initiation Award (now known as the
NSF CAREER award). He has been invited to present seminars and
tutorials at over 25 conferences, including IEEE CAIA, IEEE COMPASS,
IEEE PDIS, IEEE SAST, IEA/AIE, SEKE, SEA, DAIS, IEEE CBMS, IEEE
IC3N, ICCIMA, EIS, ICPDCS, IEEE ICECCS, IEEE IPCCC, IEEE MASCOT,
ACM SAC, ICEIS, IEEE ICMCS, IEEE ISSRE, ACM CIKM, and IEEE IECON;
and has given invited seminars/keynotes at many universities and
He is an Associate Editor of the IEEE Transactions on Software
Engineering, a Guest Co-Editor of two IEEE TSE Special Issues
on Software and Performance (Nov. and Dec. 2000), an Associate
Editor of the International Journal of Computer and Information
Science, the work-in-progress program chair of the 2001 IEEE-CS
Real-Time Technology and Applications (RTAS), the invited special
panel chair for the software engineering for multimedia session
at the 1999 IEEE-CS International Conference on Multimedia Computing
Systems (ICMCS), and a Senior Member of the IEEE.
Dr. Cheng received the B.A. with Highest Honors in Computer Science,
graduating Phi Beta Kappa, the M.S. in Computer Science with a
minor in Electrical Engineering, and the Ph.D. in Computer Science,
all from The University of Texas at Austin, where he held a GTE
Foundation Doctoral Fellowship. He is the author of the new senior/graduate-level
textbook entitled Real-Time Systems: Scheduling, Analysis, and
Verification (John Wiley & Sons) ISBN # 0471-184063, 2002.
Keynote Title: What's real in "real-time control systems"?
Applying real-time rule-based systems and formal verification
methods to control systems and robotics.
Engineers focus on the dynamics of control systems and robotics,
addressing issues such as controllability, safety, and stability.
To facilitate the control of increasingly complex physical systems
such as drive-by-wire automobiles and fly-by-wire airplanes, high-performance
networked computer systems with numerous hardware and software
components are increasingly required.
However, this complexity also leads to more potential errors and
faults, during both the design/implementation phase and the deployment/runtime
phase. It is therefore essential to manage the control system's
complexity with the help of smart information systems and to increase
its reliability with the aid of mechanical verification tools.
This keynote explores the use of rule-based systems in control
systems and robotics, and describes the latest computer-aided
verification tools for checking their correctness and safety.
Rosalind W. Picard
Bio of Prof. Rosalind W. Picard
W. Picard is founder and director of the Affective
Computing Research Group at the Massachusetts Institute
of Technology (MIT) Media Laboratory and is co-director of the
Things That Think Consortium. In 1984, she earned a Bachelors
in Electrical Engineering with highest honors from the Georgia
Institute of Technology and was named a National Science Foundation
Graduate Fellow. She worked as a Member of the Technical Staff
at AT&T Bell Laboratories from 1984-1987, designing VLSI chips
for digital signal processing and developing new methods of
image compression and analysis. Picard earned Master and Doctorate
degrees, both in Electrical Engineering and Computer Science,
from the Massachusetts Institute of Technology (MIT) in 1986
and 1991, respectively. In 1991 she joined the MIT Media Laboratory
as an Assistant Professor, and in 1992 was appointed to the
NEC Development Chair in Computers and Communications. She was
promoted to Associate Professor in 1995, and awarded tenure
at MIT in 1998.
The author of over a hundred peer-reviewed scientific articles
in pattern recognition, multidimensional signal modeling, computer
vision, and human-computer interaction, Picard is known internationally
for pioneering research into digital libraries and content-based
video retrieval. She is co-recipient with Tom Minka of a "best
paper" prize (1998) from the Pattern Recognition Society for
their work on interactive machine learning with multiple models.
Dr. Picard guest edited the IEEE Transactions on Pattern Analysis
and Machine Intelligence special issue on Digital Libraries:
Representation and Retrieval, and edited the proceedings of
the First IEEE International Workshop on Content-Based Access
of Image and Video Libraries, for which she served as Chair.
She has served two terms as Associate Editor of IEEE Trans.
on Pattern Analysis and Machine Intelligence, and is active
on several scientific program committees and review boards.
Her award-winning book, Affective Computing, (MIT Press, 1997) lays the groundwork
for giving machines the skills of emotional intelligence.
Picard works closely with industry, and has consulted with companies
such as Apple, AT&T, BT, HP, and i.Robot. She has been a keynote
or plenary speaker at dozens of scientific and industry gatherings,
including AAAI, HCI, ICASSP, IMAGINA, ACME, User Modeling, Illinois
CYBERFEST, WETICE, Future of Health Technology, and The Club
of Rome, as well as an invited speaker and distinguished lecturer
at numerous university colloquia. Her group's work has been
featured in national and international forums for the general
public, such as The New York Times, The London Independent,
Scientific American Frontiers, NPR's Tech Nation and The Connection,
ABC's Nightline and World News Tonight with Peter Jennings,
Time, Vogue, Voice of America Radio, New Scientist, and BBC's
"The Works" and "The Big Byte." Picard lives in Newton, Massachusetts
with her husband and three sons.
Keynote Title: "Toward Machines with Emotional Intelligence"
Over 70 studies on human-machine interaction in the last decade
have pointed to an intriguing phenomenon: People tend to interact
with machines in a way that is very similar to how they interact
with each other, even when the machine is not a robot, agent,
or other kind of obviously social actor. This finding holds
true even for intelligent science and engineering students who
know that machines don't have feelings. The finding suggests
that many of the more subtle skills critical for human-human
interaction are also significant for human-computer interaction.
The skills of "emotional intelligence" have been argued to be
among the most important for people, even more important than
mathematical and verbal intelligences. Emotional intelligence
includes the ability to recognize emotion -- to see if you're
irritated or annoyed someone, pleased or displeased them, bored
or interested them. It includes the ability to know when to
show emotion (or not), and how you should respond to another's
emotions, as well as many other skills.
In this talk, I'll describe how we're giving computers new skills
of intelligence, specifically the ability to recognize and respond
appropriately to human emotion. I'll show examples of systems
that try to assess interest, frustration, stress, and a range
of other states that occur when interacting with computers.
These systems involve new kinds of sensing for desktop, wearable,
and other environmental interfaces, as well as the development
of new pattern recognition and machine learning algorithms for
drawing inferences about the multimodal data.
Current applications include human learning, usability feedback,
health behavior change, and human-robot interaction.
Nuno Cintra Martins
Bio of Eng. Nuno Cintra Martins
C. Martins obtained his Ph.D. in Electrical Engineering and Computer
Science, minor in Mathematics, from M.I.T in 2004 and the "Licenciado"
and Msc. Degrees both in Electrical Engineering and Computer Science
from the Technical University of Lisbon. In 2004, he has also
completed a degree, from the Sloan School of Management, entitled
Financial Technology Option.At the age of 18, he was distinguished
with an honor mention by the Digital Corp. (only recipient - "Network
Application Support" contest). He has also shared a first prize
(with 3 other recipients), awarded by the Siemens/Emptel Corp.
In 1994, he received a best paper award (prize given by the IEEE
and Slovak Academy of Sciences) at the IMEKO- TC13 conference.
He was awarded the following fellowships: 2 PRAXIS XXI (Portuguese
Government and European Union), 1 Gulbenkian Foundation (Private),
1 PRODEP (Government) and 1 Luso-American Foundation (Government).
In 1992, Nuno C. Martins was invited to join the Center for Systems
and Signal Processing (Lisbon) at the Institute of Systems and
Computers and in 1994 he was with the Turkish IBM development
center. Later, in the same year, he moved to the Telecommunications
Institute/Technical University of Lisbon. In 1995, he was one
of the five founders of the LaSEEB - Evolutionary Systems and
Biomedical Engineering Laboratory, located in the Institute for
Systems and Robotics (Lisbon). He joined the Polytechnic Institute
of Setubal as a Faculty member in 1995, where, in 1998, he was
the youngest ever to be promoted to a position equivalent to Adjoint
Professor. In 1997 he joined the Control Systems Group, part of
the Institute of Systems and Computers, as an invited researcher.
Starting in September, 2004, he will be a Post-Doctoral fellow
at the Laboratory for Information and Decision Systems at MIT.
He has worked in several international projects, both Scientific
and Educational. In 1993 he was invited to be one of the authors
of the CEE-Computer Based Training Project. He was also an author
in the European project entitled "Leonardo da Vinci" in the area
of Signal Processing. In 1996 he was invited to be part of the
Science Alive project in the area of Physics (Portuguese Ministry
of Science). In 1996, he was the coordinator of the LaSEEB participation
in the signal processing module of the European Neurological Network
project. His Masters Thesis was used directly as part of the project.
His work was one of the 25 selected worldwide (only student; only
2 Portuguese submissions accepted) to be included in the prestigious
volume "Spatiotemporal Models in Biological and Artificial Systems,
IOS Press 1997", F.H. Lopes da Silva et all. (eds). In 1999, already
at the Laboratory of Information and Decision Systems - MIT, he
played a major role in a DARPA project in the area of distributed
resource allocation in adversarial environments. At the moment
he is working in the MURI project entitled "Cooperative Control
of Distributed Autonomous Vehicles in Adversarial Environments".
His research interests are mainly in the Information Theoretical
aspects of Estimation and Control of Stochastic Systems.
Keynote Title: "Stochasticity and Fundamental Limitations of Performance
in the Presence of Finite Capacity Feedback - Communication/Computational
Nuno Martins will talk about the control of stochastic systems
in the presence of communication/computational constraints. Focus
of intense research, this class of problems appears in remote
control as well as in channel/processor allocation for distributed
control. It is also essential in the construction of failure recovery
and supervision systems. The talk comprises two main sections:
In the first part, the effects of communication networks and computational
limitations in the feedback loop is modeled as a digital link
that sends words whose size is governed by a random process. Such
"channel" is used to transmit state measurements between the plant
and the controller. He studies the fundamental limitations generated
by the proposed framework. In accordance with previous works,
stability of unstable plants is possible if and only if the channel's
Shannon capacity is above given critical values. These will depend
on the system's stochastic behavior and the channel statistics
as well as on the stability criteria. In the second part, he departs
from the assumption of a specific channel.A new fundamental limitation
of Performance is presented. It parallels the famous Bode-integral
formula and the water-bed effect. Such new result dictates a trade-off
between disturbance rejection and channel capacity, for general