The 4th Workshop on
Ubiquitous
Computing and Emerging Intelligent Multimedia
Paradigms
A Part of the Winter seminar series at FCI
(One day invited speakers)
Cairo, Egypt, Dec. 15, 2007
Organized by:
Egyptian Rough
Sets Working Group
&
Faculty of Computer and
Information, Cairo University
Speakers
Professor Dr. Jemal Hussien Abbawajy
Deakin University
School of Engineering
and Information Technology
Geelong, VIC, 3072,
AUSTRALIA
Title : Secure Negotiation
Framework in Inter Grid Environments
Abstract:
Grid computing enables the creation of Cyber-infrastructure for
e-Research applications. It is recognized as one of the top
five emerging technologies that will have a major impact on the
quality of science and society over the next 20 years. Support for
complex multi-attribute business negotiations is a critical success
factor for the next generation of Grid computing. In this talk, I will
discuss an approach based on mobile-agent for secure electronic
negotiation in InterGrid environments.
  Biography
Dr. Jemal Hussien Abbawajy is a faculty member and
the deputy leader of the IT Security stream at Deakin University, Australia.
He is currently directing the Pervasive Computing & Networks and the Wireless
Sensor Networks research groups as well as serving as the principal supervisor
of 5 PhD and co-supervisor of 3 PhD students. He has published more than 100
articles in refereed journals and conferences. Dr. Abawajy is on the editorial
board of several international journals and edited several special
international journals and conference proceedings. Dr. Abbawajy has given many
keynote and invited talks nad he has been a member of the organizing committee
for over 60 international conferences and workshops serving in various capacity
including best paper award chair, general co-chair, publication chair,
vice-chair and program committee. He is a frequent reviewer for international
research Journals, research grant applications (e.g., Australian Research
Council) and PhD and Masters Degree examinations.
Dr. Mrs. P. P.
Rege
Professor and Dean
(Student Affairs)
Dept. of Electronics and Telecommunication
College of Engineering
(An Autonomous Institute of Govt. of Maharashtra)
Pune
Title: Recent
trends in image analysis
With the advent of Internet and
digital communication, the area of Digital Image Processing and analysis has
emerged as a subject of interdisciplinary study and research in Physics,
Chemistry, Biology, Engineering, Meteorology, Space Science and of course
Computer Science. Two Dimensional and three dimensional image processing today
forms a major area of research and development in the broad fields of pattern
recognition, computer vision, machine learning and also artificial Intelligence.
Main aim of the talk is to cover few applications of image
processing like Digital watermarking, Texture Analysis, and Document Analysis.
Digital data hiding has received increasing attention from the information
technology community. The talk would cover many aspects that are common to any
data hiding system. Data hiding in general, is an immature field, and that more
effective solutions will be developed in the years to come.
Image segmentation finds many applications in Industry and Biomedical field.
Texture Analysis is one of the methods for segmentation that enables us to
classify various regions based on the texture contents of the object. There is
an increasing need to digitally preserve and provide access to historical
document collections residing (and possibly decaying) in libraries, museums and
archives. To facilitate future automatic searching and analysis of the words and
content in the documents, it is necessary to separate the useful pixels
containing document content, such as handwriting, drawings, pictures and other
information representing useful artifacts, from the background pixels of the
paper. Document analysis is the process that performs the overall interpretation
of document images. Efforts will be to represents a good description of the
state of the art in these fields, and a good starting point for future research
as well as for the development of practical applications."
Biography
Priti Rege received her B.E (Bachelor in
Engineering) with distinction in 1983 and M.E degree with Gold medal
in 1985, both from Devi Ahilya University of Indore, India. She
received her doctoral degree from the Pune University, India in 2002.
She is a Professor at College of Engineering, Pune. Currently, she is
also working as Dean, Students affairs at the same Institute. She
has authored/coauthored over 45 research publications in peer-reviewed
journals and conference proceedings. She has worked
on advisory committee/ program committee of various conferences
and also as a reviewer for various
journals. She has also worked as chairperson at various sessions in
National and International conferences. She is a Senior Member of
IEEE, Life member of Institution of Electronics and Telecommunication
Engineers, India, Life member and Convener of Biomedical Engineer’s
Society of India. She has edited “Trends in Process Instrumentation
and control”, proceedings of International Conference on
Instrumentation INCON 2005. Her research interests
include, Digital Watermarking, Texture Analysis, Optical character
Recognition, Document enhancement and 3-D volume rendering. She has
contributed in research projects funded by Government and Industries
and has also received fellowship for carrying out research in the
field of image processing.
Supra Topological Approach for
Decision Making via Granular Computing
By
Dr. Tamer Medhat Mohammad
Ibrahim
(T. Medhat)
E-mail:
tmedhatm@yahoo.com
Homepage:
www.geocities.com/tamer_topology/
Granular
computing is a valid way to describe problem spaces or solve problems.
It enables us to perceive the real world under various grain sizes,
obtain only those useful or interesting things at different
granularities, and switch among different granularities to get various
levels of knowledge. The basic ideas of granular computing have
already been explored in many fields, such as soft computing,
knowledge discovery, machine learning, and web intelligence. At
present, there are several major research results shown as follows.
The topic of fuzzy information granulation was first proposed by
Professor L.A. Zadeh. Based on fuzzy set theory, he proposed a general
framework of granular computing. Granules are constructed and defined
based on the concept of equivalence, probability and fuzzy
relationship. Relationships between granules are represented in terms
of fuzzy graphs or fuzzy if-then rules. Its computation method is
computing with words. Rough set theory proposed by Professor Z. Pawlak
in 1982 has been applied to many fields. It is a valid mathematical
method to deal with imprecise, uncertain, and vague information, As a
concrete theory of granular computing, rough set theory enables us to
precisely define and analyze many notions of granular computing.
Professors Y.Y. Yao and Q. Liu study the partition model and logical
reasoning based on granular computing. Construction of granules and
representation of their relationships are described in terms of the
decision logic language. Professor T.Y. Lin has done a lot of work in
granular computing and its applications, including granular computing
on binary relations in data mining and neighborhood systems. Some
basic ideas of granular computing have been successfully explored in
image processing and machine learning in his work.
Professors
L. Zhang and B. Zhang developed the quotient space theory in 1992. It
is a novel theory of granular computing. Granules are constructed and
defined by collection, and relationships between granules are
represented in terms of collection calculation. An important property
of quotient space theory is the "false preserving" property. It means
that there will be no solution in the original fine-grained space if
there is no solution in a coarse-grained space. The quotient space
theory has been applied in wave analyzing and bioinformation
processing. Although there are differences among these theories of
granular computing in their formulation, i.e., construction of
granules and representation of their relationships, their core idea is
the same. That is, a problem space is firstly divided into some basic
granules. Then, these basic granules are further composed or
decomposed into new granules at different hierarchies. The above two
steps are repeated until these new granules could solve the problem
more valid. Since each theory has its advantages of solving the
problem in some field, it is very important to take advantages of each
theory to solve the problem in a more efficient way. We use granular
computing for converting the complicated information systems into
simple ones. The topological
approximation space which we used in our presentation is used for
decision making as reduction of superfluous attributes and determining
the upper approximation and lower approximation. This space is a
generalization of Pawlak's space and preferred than Yao's space by
increasing the lower approximation, decreasing the upper
approximation, and so decreasing the boundary region. Also it is used
for reduction in general binary relations, By making the reduction of
information system values we get the minimal information table. Also,
by converting any MVIS "multi-valued information system" to SVIS
"single valued information system", we can deal with all programs of
the equivalence relations. By calculating the degree of dependency and
taking the value of error ratio, we can eliminate some of attributes
with some approximation that we can't eliminate any of them using the
classical rough set techniques.
Biography
 Tamer
Medhat received his B.Eng. "Electronic Computer and Automatic Control"
in 1998 from Tanta University, Faculty of Engineering, Tanta, Egypt.
M.Sc. degree "Engineering Mathematics" in 2004, and PhD degree
"Engineering mathematics" in 2007, both from Tanta University, Faculty
of Engineering, Physics and Engineering Mathematics Department.
Tanta, Egypt. Currently, he is a lecturer of engineering mathematics
at Kafr Elsheikh University, Faculty of Engineering, Physics and
Engineering Mathematics Department. He has authored/coauthored over
10 research publications in peer-reviewed reputed journals and
conference proceedings. He has served as reviewer for some
international journals. Dr. T. Medhat was a member of the
International Rough Set Society. Also, he was a member of the
Egyptian Rough Set Group ERSG. His research interests include, rough
set theory, general topology, fuzzy set theory, neural network,
artificial intelligent, engineering mathematics and its applications.
DSRC: Towards Autonomous
Vehicular Communications
By
Dr. Y. L. Morgan
Faculty, of Engineering, Regina University, Canada
.
The Dedicated Short-Range Communications (DSRC) is a new
wireless communication suite that is designed specifically for street
and vehicular communications. DSRC is built as a tweak of the
classical WiFi in order to provide solid communications at the street
level for both vehicle-to-vehicle and vehicle-to-roadside. DSRC has
built-in mechanisms for delivering public safety messages and
facilitates safer and richer driving experience. Over and above,
DSRC helps improving infrastructure utilization and maintenance. DSRC
is capable of delivering 27 Mbps data-rate over 5.9 GHz by using a two
way line-of-sight short-range radio which is significantly lower cost
compared to cellular, WiMax or satellite communications. Some of
the typical DSRC applications are listed below:
• Emergency warning system for vehicles
• Approaching emergency vehicle warning (Blue Waves)
• Vehicle safety inspection
• Transit or emergency vehicle signal priority
• Probe data collection
• Highway-rail intersection warning
• Public transport monitor
Biography
 Dr.
Y. L. Morgan received his Ph.D. from Carleton University and is
currently an Assistant Professor in University of Regina. Dr. Morgan
is focused on research related to mobile vehicular communications and
in specific the development of ITS infrastructure like DSRC and VII
initiatives. Dr. Morgan has been part of the IEEE 802.11p standards
group and the IEEE 1609.0/.1/.2/.3/.4/.5 groups as well. Dr. Morgan
has authored and co-authored more than twenty research papers
including contributions to standards like IEEE, IEEE-SA, IETF, and
3GPP. Dr. Morgan is also an active member and reviewer in the VTC and
the VTS societies that are focused on vehicular transportation systems
and applications. The objective of Dr. Morgan research is to develop
real-time effective and secure communications between vehicles and
between vehicles and roadside. This communication must be geared
towards enhancing transportation safety and quality while leaving room
for commercial aspects. Currently, Dr. Morgan is one of a group of
researchers pioneering the ONE-ITS initiative.
Resource-Adaptive Data Stream Processing
Dr. Mohamed Medhat Gaber
CSIRO, Australia
http://www.geocities.com/medhatgaber/
The need for
traditional data processing techniques had become increasingly
important with the evolution in databases and data warehousing
technologies. These
data
repositories have grown in size with the wide deployment of such
technologies. Scalability had been a major research challenge in
this area. Large data repositories
have been
queried and analysed/mined for knowledge for business value and
scientific discovery. Advances in both hardware and software
technologies have led to
fast data
generation. This introduces the area of data streams. Streaming data
is ubiquitous and there is a real challenge to store, query, analyze
and visualize such rapid large volumes of data. Resource constraints
of ubiquitous environments represent the main research issue to
realize such a potential field with various important applications.
Examples of such applications include processing data streams
produced from sensor networks, web clickstreams, ATM transactions,
stock market and many others. In this talk, we review the challenges
facing data stream processing. The need for resource-awareness and
adaptation is presented leading to an overview of our novel techniques
in mining/querying data streams. Applications of these techniques are
also presented. Finally the talk is concluded with future visions in
the area of data streams and resource-constrained processing
environments.
Biography:
 Dr. Mohamed
Medhat Gaber is a research scientist at CSIRO, Australia. He received
his PhD degree in 2006 from Monash University. His PhD thesis had been
nominated for Mollie Holman Award for best PhD theses. He has proposed
and developed novel adaptive and lightweight data stream mining
algorithms based on his novel Algorithm Output Granularity (AOG)
approach to enable "on-board" processing in resource constrained
devices such as handheld computers/sensors. He was awarded the
competitive and prestigious IBM Doctoral Internship at the IBM T.J.
Watson Research Centre in 2005. He has published more than 50 papers
including 4 book chapters and 7 journal articles. Mohamed is the
co-editor of the book: “Learning from Data Streams: Processing
Techniques in Sensor Networks”, published by Springer in 2007. He
is also the co-editor of: Proceedings of International Workshop on
Knowledge Discovery from Ubiquitous Data Streams, and
Proceedings of First International Workshop on Knowledge Discovery
from Sensor Data (Sensor-KDD '07). He had 5 successful Masters
supervision and an Honours one at both Monash University and
University of Sydney. He is currently co-supervising a PhD student at
Monash University. His profile was selected for inclusion in Monash
Research Graduate School Annual Report in 2004 and the university
scholarship guide for students starting in 2006. Mohamed was nominated
and included in Who's Who of Emerging Leaders - 2007, 1st Edition. He
is a member of the International Panel of Expert Advisers for
Australasian Data Mining Conferences. Mohamed was the co-chair of:
International Workshop on Knowledge Discovery from Sensor Data, held
in conjunction with the Thirteenth ACM SIGKDD International Conference
on Knowledge Discovery and Data Mining 2007, International Workshop on
Knowledge Discovery from Ubiquitous Data Streams, held in conjunction
with ECML/PKDD 2007, and IEEE International Workshop on Mining
Evolving and Streaming Data, held in conjunction with ICDM'06. He
served in the program committees of : ACM Symposium on Applied
Computing - Data Streams Track 2008, Second International Workshop on
Web Mining for Ecommerce and E-services (WMEE2008), Sixth Australasian
Data Mining Conference 2007, Second International Workshop on
Integrating AI and Data Mining 2007, International Workshop on
Learning from Massive Data 2007, First International Workshop on Web
Mining for E-commerce and E-services (WMEE2007), ACS/IEEE
International Conference on Computer Systems and Applications, AICCSA
2007, ACM Symposium on Applied Computing - Data Streams Track 2007,
Fifth Australasian Data Mining Conference 2006, Workshop on
Integrating AI and Data Mining 2006, Fourth International Workshop on
Knowledge Discovery from Data Streams 2006, Third International
Workshop on Knowledge Discovery from Data Streams 2006, Fourth
Australasian Data Mining Conference 2005, Second International
Workshop on Knowledge Discovery from Data Streams 2005 and Third
Australasian Data Mining Conference 2004. Mohamed was also invited as
a journal reviewer for papers in: Data Mining and Knowledge Discovery,
Springer, International Journal on Very Large Data Bases (VLDB),
Journal of Information Science, Journal of New Generation Computing:
Special Issue on Knowledge Discovery from Data Streams, Journal of
Intelligent Data Analysis (IOS Press): Special Issue on Knowledge
Discovery from Data Streams, Journal of Intelligent Information
Systems: Special Issue on Mining Spatio-Temporal Data, Journal of
Universal Computer Science, Special Issue on Knowledge Discovery in
Data Streams, and Computational Statistics, Special Issue on
Statistical Analysis of Interval Data.
Unsupervised statistical learning in
causal models
of visual and audio perception
by
Professor Mariofanna Milanova
Computer Science Department, University of Arkansas at Little Rock
In recent years, it has become clear that many problems in perception
organization are difficult to solve without introducing the contextual
information. We see and hear the world in terms of meaningful causal
interactions – a vase crashing to the ground, a father beckoning to
his daughter – rather than raw lights and sounds. What is the role of
causal inference in perception, and in bridging perception to
cognition? How can computational frameworks for causal reasoning and
learning be mapped onto –and perhaps enriched by models of neural
computation? To answer these questions different models of perceptual
learning are developed. Barlow’s hypothesis is that the purpose of
early visual processing is to transform the highly redundant sensory
input into more efficient factorial code. A perceptual system should
be organized to transmit maximum information. Among existing
techniques for modeling multi-resolution decomposition are principal
component (PCA) and independent component analysis (ICA). We
propose to improve the effectiveness of decomposition algorithms by
providing them with “classification-awareness.” Combining
decomposition and classification is one of the main points of the
proposed research methodology. The link between the stimulus and a
given neuron action potential source can be verified by designing a
classifier that is able to “predict” under which condition a given
signal has been registered, solely based on the discovered independent
components. The idea is to look for basis functions whose coefficients
allow for an accurate classification while preserving the
reconstruction. The proposed framework was
tested using neurobiological (event-related potentials ERPs) data and
behavioral (eye tracking) data. We also discuss challenging direction
for future research in perception.
Biography:
Dr. Mariofanna Milanova is Associate Professor of Computer Science
Department University of Arkansas at Little Rock, USA. She received
the M. Sc. degree in Expert Systems and AI in 1991 and the Ph.D degree
in Computer Science in 1995 from Technical University, Sofia,
Bulgaria. She did her post-doctoral research in visual perception in
University of Paderborn, Germany. She has extensive
academic experience at various academic and research organizations
including the Navy SPAWARS System
Center,
San Diego, USA, University of Louisville, USA, National Polytechnic
Institute Research Center, Mexico City,
Mexico, Technical University of Sofia, Bulgaria, University of Sao
Paulo, Brazil, University of Porto, Portugal, Polytechnic University
of Catalunya, Spain, University of Paderborn, Germany. She has been
granted from German Research Foundation
(Deutsche Forschungsgemeinschaft),
FAPESP State of Sao Paulo Research Foundation.
NSF, European Community, NATO and Department of Homeland Security.
Dr
Milanova is a Senior Member of the IEEE and Computer Society, member
of IAPR, member of the IEEE Women in Engineering, member of Society of
Neuroscience and a member of the Cognitive Neuroscience Society.
Milanova serves as book editor of two books and associate editor of
several international conference proceedings including the ICMLA
International Conference on Machine Learning and Application and the
METMBS Mathematics and Engineering Techniques in Medicine and
Biological Sciences. Milanova chaired ICMLA’05 Conference. Milanova
chaired the series of the IEEE International Conference on Information
Reuse and Integration (2001, 2003-2006) and the MEMBS’ 01 and MEMBS’
03. Her main research interests are in the areas of
artificial intelligence, biomedical signal
processing and computational neuroscience, computer vision and
communications, machine learning, privacy and security based on
biometric research She has published and co-authored more than
60 publications, over 33 journal papers, 6 book chapters, 2 patents
and numerous conference papers.
BIO-INSPIRED INTELLIGENT INTEGRATED SYSTEMS
Professor Hoda S.
Abdel-Aty-Zohdy, Ph.D
Director of the
Microelectronics System Design Lab
Department of Electrical and
Computer Engineering
Oakland University
E-mail:
zohdyhsa@oakland.edu
ABSTRACT:
Bio inspired systems
provide novel approaches to intelligent signal processing by mimicking
the intelligence of living biological systems and then implement it
with controllable high speed and density, on integrated chip packages
for wide scope of applications.
Bio-Inspired Systems
integrate the various available intelligent processing approaches such
as: Neural Networks (NNs), Evolutionary Programming such as Genetic
Algorithms (GAs), and Fuzzy Logic. We capitalize on the inherent
advantages and limitations of each approach, with selection guidelines
and criteria for specific embedded applications. Abdel-Aty-Zohdy’s
lecture will elucidate observations and motivations to mimic
biological systems, and will focus on applications of bio-inspired
intelligence including multi-media polymorphic computational biology,
and the mammalian olfactory system -- an electronic nose, based on .
She will also discuss the most recent scientific discoveries gleaned
from the study of spikes in the brain activity of monkeys, which have
introduced the concept of plasticity in synapses. Biological memory
and collaborative man–machine interfaces will be touched upon in terms
of future bio-intelligence challenges. Examples of embedded
bio-inspired approaches will be discussed and presented with emphasis
on systems for recent bio-chemical sensing and detection (Electronic
Nose), temperature prognosis, and applications towards bio computing.
These include our Spiking NN system with 128 inputs and 8-outputs on
an area of 0.118 square mm using the 0.16um CMOS technology.
Bio-inspired, silicon-based systems integration with organic and
inorganic media via multi-phase, and multi-domain possible interface
and integration promise to achieve intelligent, secure, compact, and
real time applications.
Biography:
 Prof.
Hoda Abdel-Aty-Zohdy received the B.A.Sc. degree (with First Class
Honors) from Cairo University, the M.A.Sc. and the Ph.D. degrees from
the University of Waterloo, all in Electrical Engineering. She is the
Founder and Director of the Microelectronics System Design Laboratory,
Coordinator of the Engineering Physics Program, and Professor in the
department of Electrical and Systems Engineering at Oakland
University. She has authored 135 refereed publications, and about 100
technical presentations. Dr. Abdel-Aty-Zohdy has been an AFOSR/IF
Visiting Faculty Research Fellow (2003 and 2002), a National Academy
of Science/National Research Council Fellow (2000 and 2001), a Faculty
Intern at the Chrysler Technology Center, Advanced Manufacturing
Engineering, 1998 and 1997, Consultant to Fanuc-Berkeley MEMS Lab,
1996, DARPA supported Visiting Professor at The University of
Michigan, Ann Arbor, Center for Integrated Sensors and Circuits, 1995;
Consultant to General Motors Research Labs, ITT, and a visiting
professor at the Institute for Computer Research, at the University of
Waterloo. Dr. Abdel-Aty-Zohdy is elected to the Distinguished Lecture
Program of the IEEE Circuits and Systems Society (2004-2005 and 2006).
She served on numerous IEEE committees including: The Chairperson in
2005-06 and a member 2004 -2005 for the IEEE G. R. Kirchhoff’s Award
Committee; The elected Chair for the IEEE/South East Michigan
Section-Chapter-I on Circuits and Systems, Signal Processing,
Information Theory, and Control since 2000; The Chair of future
symposia committee, general cochair, track chair, session organizer,
and speaker for the IEEE Midwest Symposium on Circuits and Systems
since; The Organizer and General Chair of the Educational program for
the IEEE Custom Integrated Circuits Conference (CICC88). She served as
the General Chair for the first Collaborative Technologies Workshop in
1999, at Oakland University. She presented the Oakland
University President’s Colloquium, April 1st, 2005, Keynote, and
plenary lectures at: the International Conference on
Telecommunications (ICT05) South Africa, 2005; IEEE NEWCAS 2004, in
Montreal Canada; IEEE MWSCAS 2003, Cairo, Egypt; IEEE ECCTD 2003 in
Krakow, Poland; and the ICCC 2001, in Hamammat, Tunisia.
(One day invited speakers)
Cairo, Egypt, Dec. 18, 2007
Knowledge Maps =
Stable Pattern Languages
Professor Mohamed E. Fayad, PhD
mefayad@gmail.com, m.fayad@sjsu.edu
Pattern languages
form the strong groundwork for any discipline understanding. Its uses
have spilled over to the software engineering field, to precisely
describe past experiences and better understand software architectures
conceptualization and realization, along with, how their building
blocks are insightfully woven seamlessly to satisfy a determined
purpose resolution. Current representations of pattern languages [5,
6, 7] strives hard in providing the sufficient means or guidelines to
build software architecture out of patterns; bringing as a consequent
problems, such
as poor
traceability [3], lack of stability, poor adaptability, out of context
understanding realization, are more prominent within the pattern
language implementation.
To overcome
these problems in traditional pattern languages, we have provided both
a set of quality factors to evaluate pattern language definition,
accuracy, and application; and also a newly enhanced Pattern Language
representation, driven by Software Stability Concepts [8, 9, 10],
called Knowledge Map, which provides many significant benefits to the
software architecture’s development practices.
Resource Management in Heterogeneous
Wireless Networks –
Challenges and Opportunities
by
Professor Hossam Hassanein
Telecommunications Research Lab
Queen’s University
Abstract: This talk describes our efforts in addressing the
challenges to Resource Management (RM) in Heterogeneous Wireless
Networks (HWNs). Our understanding is that establishing a
comprehensive RM framework for such networks requires the
consideration of elements in two dimensions – the access level and the
end-to-end level. It is also crucial to accommodate the unique
characteristics of HWNs. In the talk we, will detail our efforts
in three main directions. The first comprises establishing a framework
overlooking the interactions of network levels (network, path, link
and access) in end-to-end service delivery. We describe practical
mechanisms for multi-metric routing, in addition to inter-level
mapping of end-to-end QoS requirements. We also describe generalized
access scheduling techniques with economic considerations. The second
direction entails the introduction of novel and non-traditional RM
mechanisms that exploit characteristics specific to HWNs. We show how
technologies within a HWN can be enhanced through joint
functionalities. The third direction shows how vertical handoffs,
despite their challenges, can be used to the benefit of the service
provider; and how the use of wireless multihop communication can be
utilized in a structurally-hybrid environment to maintain a robust
network operation.
Biography:
Hossam Hassanein is a leading researcher in the School of
Computing at Queen's University in the areas of broadband, wireless
and variable topology networks architecture, protocols, control and
performance evaluation. Before joining Queen's University in 1999, he
worked at the department of Mathematics and Computer Science at Kuwait
University (1993-1999) and the department of Electrical and Computer
Engineering at the University of Waterloo (1991-1993). Dr. Hassanein
obtained his Ph.D. in Computing Science from the University of Alberta
in 1990. He is the founder and director of the Telecommunication
Research (TR) Lab
http://www.cs.queensu.ca/~trl in the School of Computing at
Queen’s. Dr. Hassanein has more than 300 publications in reputable
journals, conferences and workshops in the areas of computer networks
and performance evaluation. Dr. Hassanein has organized and served on
the program committee of a number international conferences and
workshops. He is a senior member of the IEEE and serves as the
Secretary of the IEEE Communication Society Technical Committee on Ad
hoc and Sensor Networks (TC AHSN). Dr. Hassanein is the recipient of
Communications and Information Technology Ontario (CITO) Champions of
Innovation Research award in 2003.
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