PLENARY SPEAKERS

1. Prof. Maria Petrou
2. Prof. Erol Gelenbe
3. Prof. G. Giakos
4. Prof. Dirk van Ormondt
5. Prof. Irwin King
6. Dr. George Zentai
7. Dr. L.H. Tsoukalas

1. Prof. Maria Petrou
"A new imaging architecture and an alternative interpretation of the structure of the human retina"

Abstract
An architecture is proposed where the layers of cells that lie in front of the photosensitive cells of the human retina are interpreted to be estimators of the first and second order derivatives of the brightness of the imaged scene. Such architecture bypasses the problems of estimating derivatives from sampled and digitized data, as they are estimated directly from the scene. It also offers an explanation on why the photosensitive sensors of the human eye are placed at the back of the eye, behind four other layers of cells.

Short CV
Maria Petrou studied Physics at the Aristotle University of Thessaloniki, Greece, Applied Mathematics in Cambridge and she did her PhD in the Institute of Astronomy in Cambridge, UK. She obtained her DSc also from Cambridge in 2008. She is currently the Professor of Signal Processing and the Head of the Communications and Signal Processing Group at Imperial College London. She has published more than 300 scientific papers, on Astronomy, Remote Sensing, Computer Vision, Machine Learning, Colour analysis, Industrial Inspection, and Medical Signal and Image Processing. She has co-authored two books "Image Processing: the fundamentals" and "Image Processing: Dealing with texture" both published by John Wiley in 1999 and 2006, respectively. She has supervised to successful completion 39 PhD theses, and examined more than one hundred. She is a Fellow of the Royal Academy of Engineering, Fellow of IET, Fellow of IAPR, Fellow of the Institute of Physics, Senior member of IEEE and a Distinguished Fellow of the British Machine Vision Association. More information can be found in http://www.commsp.ee.ic.ac.uk/~mcpetrou

2. Prof. Erol Gelenbe
Imperial College, UK
"Network adaptivity through self-awareness: the CPN experience"

Abstract
The infinite size and great diversity of the Internet's physical substrates, and the diversity of the user population and its time-dependent traffic requirements, implies that the networks that different user communities or organizations may construct over this substrate should be able to self-organize in order to provide their users the best possible services. Communication is the key service that enables everything else, and the best quality of service should be available to users at the lowest possible cost. Our presentation will address means for users to dynamically improve the quality of service that they receive by being "smart consumers" who are aware of network state via observation of the routes and nodes that they use or which they may choose to use, and who adapt the paths that they use using information gathered and acted upon in real-time. The discussion will be illustrated with measurements from our Cognitive Packet Network test-bed.

Short CV
Prof. Erol Gelenbe of Imperial College is a native of Turkey and graduated from Ankara Koleji and the Middle East Technical University in Ankara. He is a Member of the French National Academy of Engineering (Acad?mie des Technologies), the Turkish Academy of Sciences, and the Academia Europaea. He is a Fellow of the ACM and of IEEE, and was awarded the IFIP Silver Core in 1980. In the justification for his recent reception of the ACM SIGMETRICS Achievement Award 2008, it is said that he is “the single individual who, over a span of 30 years, has made the greatest overall contribution to the field of Computer System and Network Performance Evaluation through original research, mentoring and doctoral training, creation and direction of world class research groups, wide ranging international collaboration, and professional service” and that he “has made decisive contributions to product form networks by inventing G-networks (Gelenbe-Networks) with totally new types of < <negative customers, triggers, and resets> >, which are characterized by non-linear traffic equations. He has made seminal contributions to random access communications, the optimization of reliability in database systems, the design of adaptive QoS-aware packet networks, diffusion models in performance analysis, and the performance of link control protocols.” Prof. Gelenbe has authored four books in English and French, two of which have been published in Japanese and Korean, one of which will soon appear in Chinese. He has graduated 58 PhD students and published some 125 journal articles. His honours include: Commander of Merit of the Republic of Italy, Grand Officer of the Star of Italy, Officer Order of Merit of France and Chevalier des Palmes Acad?miques, and "honoris causa" doctorates from the University of Rome Tor Vergata (1996), Bogazi?i University, Istanbul (2004), and the University of Li?ge, Belgium. He received the Science Award (1994) of the Parlar Foundation in Turkey, and was the first computer scientist to be awarded the Grand Prix France Telecom (1996) of the French Academy of Sciences. With very broad research interests, his recent publications include path finding algorithms in noisy and uncertain conditions, networked auctions, the use of neural networks to control routing in computer networks, as well as theoretical biology and theoretical chemistry including neural networks and gene regulatory networks. His work is funded by industry (GD, BAE Systems and QinetiQ), and EPSRC, MoD, DoD, EU FP6 and FP7.

3. Prof. G. Giakos
"Novel Molecular Pathways from Photomedicine Imaging to Nanodevice Industry".

Abstract
The development of macroscopic and nanoinstrumentation-based imaging systems and techniques, capable to provide molecular, biochemical, physiological, and metabolic information for medical and biological applications is of paramount significance. Developing reliable imaging techniques with the potential to detect molecular signatures and disease precursors will not only offer the opportunity for efficient treatment at the earliest possible stages but will also prove useful for staging of tumors, and further identification of the molecular origins of cell anomalies. The author will present new experimental findings based on blending of multispectral polarimetric imaging, molecular nanophotonic principles, and metamaterials. Polarimetric imaging in combination with new molecular photosensitizers provides a sensitive and specific method to detect and prevent the progression of early diseases. The outcome of this study has significant impact on the exploration of molecular pathways and signatures for early detection of disease, tissue pathologies, enhanced anatomy, and treatment, as well as to the design of innovative molecular photonic and bioinspired nanophotonics devices.

Short CV
Professor Giakos is a faculty in the Department of Electrical and Computer Engineering, and Biomedical Engineering, at the University of Akron, OH, USA. In addition, he is the Director of Imaging Technologies and Surveillance Technologies, Molecular Nanophotonics, and Applied Nanosciences Laboratories. Prior joining the University of Akron, he has been an Associate Director of the Imaging Research Laboratory at the University of Tennessee, in the Department of Biomedical Engineering. On 1978, he received the Laurea Degree in Applied Physics from the Institute of Physics “A. Avogadro”, University of Turin, Italy, a graduate Degree in Nuclear Instrumentation from the University of Edinburgh (UK), a MS Degree in Nuclear Space Physics from Ohio University (1985), and a Ph.D. Degree in Electrical and Computer Engineering from Marquette University, Milwaukee, WI, (1991). Dr. Giakos research is articulated in the design of imaging systems, ladars and surveillance sensor platforms, for the Department of Defense and Homeland Security, multispectral polarimetry, exploration of molecular pathways and signatures for early detection of disease, tissue pathologies, and treatment, as well as in the design of innovative molecular photonic and bioinspired nanophotonics devices. His research group was the first in the US to pioneer the characterization of the detection and imaging characteristics of Cadmium Zinc Telluride semiconductor substrates for flat-panel digital radiography applications. Dr. Giakos, has fostered several breakthrough inventions which have been rewarded with fifteen (15) US and international Patent Awards and more than 150 peer-review articles and journal publications. He is the recipient of a Distinguished Faculty Fellow Award, from the Office of Naval Research. He received numerous prestigious research faculty fellowship awards from the Department of the Air Force, NASA, National Academy of Sciences, and Naval Research Laboratory. He maintains active research collaborations with the Air Force Research laboratory, Naval Research Laboratory, NASA, Varian Medical Systems, Lockheed Martin, and Cleveland Clinic. Dr. Giakos is the Editor in Chief, of the International Journal of Signal and Imaging Systems Engineering (IJSISE), Associate Editor of the IEEE Transactions on Instrumentation and Measurement, Chairman of the TC-19 IEEE Technical Committee on “Imaging Measurements”, and Member of the IEEE Virtual Reality Task Force for the Intelligent Systems Applications Technical Committee. In addition, he serves as the Organizer and General Chairman of the IEEE International Workshops on Imaging Systems and Techniques. He is the PI, for the University of Akron, of The Ohio BioMEMS Consortium on Medical Therapeutics Microdevices.

4. Prof. Dirk van Ormondt
 

Abstract
Magnetic Resonance Spectroscopy MRS is the only technique that enables non-invasive, in vivo measurement of metabolites in humans. Each metabolite contributes a unique signal (`fingerprint'). Since metabolites serve as biomarkers of disease, this is a very useful property. MRS signals are measured in the time domain. The dwell time of a human in the scanner being restricted by considerations of comfort and cost, the signal-to-noise ratio (SNR) is usually moderate to low. Basically, the concentrations of detected metabolites are estimated by nonlinear least-squares fitting of a model function to the signal (or to its FFT). On the one hand, ever increasing physical/chemical a priori knowledge about metabolite signals by quantum-mechanical computation improves the estimation. On the other hand, metabolite signals are perturbed by scanner imperfections and biological conditions. Presently, most perturbations can not yet be modeled. This calls for a semi-parametric approach. The aspects mentioned above will be reviewed.

Short CV
1959: MSc, Applied Physics, TUDelft
1968: PhD, Applied Physics, TUDelft
1969/1970: Postdoc with HA Buckmaster, Physics, U of Calgary, Canada
1970/1971: Postdoc with JM Baker, Physics, Clarendon Lab, U of Oxford, UK
1972/2001: Faculty member, Applied Physics, TUD
1994/2001: Coordinator of European HCM/TMR/Networks Project "Advanced Signal Processing for Medical MRI/MRS."
1994/2001: MRI reconstruction
1983/present: In vivo metabolite quantitation
1989/present: Involved in the free Metabolite Quantitation Software Package `MRUI', http://www.mrui.uab.es/mrui/
2002/present: Emeritus at Applied Physics, TUDelft
2006/present: Expert of EU Marie-Curie Research Training Network `FAST' (MRTNCT-2006-035801, 2006-2009), http://www.fast-mariecurie-rtn-project.eu/index.php .

5. Prof. Irwin King
"The New Paradigm Shift: The Emergence of Social Computing".

Abstract
The Web has changed the landscape of how humans interact socially. With the advent of Web 2.0, Social Computing has emerged as a new paradigm for computing relational information. Social Computing involves the investigation of collective intelligence by using computational techniques such as machine learning, data mining, natural language processing, etc. on social behavioral data collected from blogs, wikis, clickthrough data, query logs, tags, etc. In this talk, I will first introduce Social Computing by taking a short historical journey and elaborate on some of the unique characteristics and aspects that are found on the various social platforms. In addition, I will highlight some of the research work being done and the applications that are being created with the new paradigm. Lastly, we examine some current challenges and potential future promises of Social Computing.

Short CV
Dr. Irwin King is currently the Chinese University of Hong Kong. He received the BSc degree in Engineering and Applied Science from California Institute of Technology and his MSc and PhD degree in Computer Science from the University of Southern California. Dr. King's research interests include machine learning, web intelligence & social computing, and multimedia processing. In these research areas, Dr. King has published over 150 refereed journal and conference manuscripts. In addition, he has contributed over 20 book chapters and edited volumes. Moreover, Dr. King has over 30 research and applied grants. Dr. King is an Associate Editor of the IEEE Transactions on Neural Networks (TNN). He is a member of the Editorial Board of the Open Information Systems Journal, Journal of Nonlinear Analysis and Applied Mathematics, and Neural Information Processing–Letters and Reviews Journal (NIP-LR). He has also served as Special Issue Guest Editor for Neurocomputing, International Journal of Intelligent Computing and Cybernetics (IJICC), Journal of Intelligent Information Systems (JIIS), and International Journal of Computational Intelligent Research (IJCIR). He is a senior member of IEEE and a member of ACM, International Neural Network Society (INNS), and Asian Pacific Neural Network Assembly (APNNA). Currently, he is serving the Neural Network Technical Committee (NNTC) and the Data Mining Technical Committee under the IEEE Computational Intelligence Society (formerly the IEEE Neural Network Society). He is also a Vice-President and Governing Board Member of the Asian Pacific Neural Network Assembly (APNNA).

6. Dr. George Zentai Varian Medical Systems, USA
"High resolution x-ray imaging"

Abstract
This presentation gives an overview of the present status of direct x-ray imagers. The spatial resolutions of the direct and indirect imagers are compared and it is pointed out that the lack of light scatter greatly improves the resolution. Moreover, opposite to the indirect imagers, the resolution does not degrade as layers of the X-ray detector materials get thicker for better X-ray absorption at higher X-ray energies. Different direct X-ray conversion materials are compared and how the physical properties influence the X-ray detection efficiency and imager stability are discussed. Ghosting and image lag properties are also weighted. Some X-ray sensitive photoconductor materials produce very high X-ray conversion efficiency. This feature improves the S/N (signal to noise) ratio at low dose fluoroscopy, to overcome the noise of the readout electronics and to get quantum noise limited detection. The manufacturing advantage of the direct imagers is also emphasized. The direct imagers do not need p-i-n photodiodes so the a-Si TFT matrixes for these arrays can be manufactured at any LCD manufacturing sites and not only at a few very specialized companies where the p layers for the photodiodes can be deposited for the indirect imagers.

Short CV
George Zentai joined Varian Medical Systems’ Ginzton Research Center (Mountain View, California) in 1998 and has been working as R&D Program Manager of Direct x-ray Sensor Development Projects. His team developed x-ray imagers both for medical and security applications, which went into production at Varian. He gave many conference presentations; some of them invited ones, wrote several publications, and have many patents in the x-ray imaging field. He has also been involved in the development of low noise readout electronics, ASICs for flat panel digital imagers and special electronic testing methods. He has many years experience in photoconductor based imagers. He has a Masters Degree in Electronics and a Ph.D. in Amorphous Semiconductors. Previously he was Manager of Flat Panel X-ray Sensor Development at OIS (Optical Imaging Systems) and a visiting scientist at Argonne National Laboratory. He is member of SPIE, senior member of IEEE and member of organizing and technical committees and co-chair of SPIE and IEEE conferences.

7. Dr. L. H. Tsoukalas Purdue University, USA
"From Smart Grids to Energy Internet: The Future of Energy Distribution Systems"

Abstract
With many energy observers raising concerns about a peak in global petroleum production and a scientific consensus favoring caps in the use of fossil fuels, consideration must be given to the successful technological convergence of energy and information technologies. The presentation will discuss how smart energy distribution can evolve into an energy internet. Pricing signals and short term elasticities can regulate energy flow to maintain the delicate equilibrium involved in generation, distribution and consumption. Intelligent forecasting approaches acting at multiple levels (including device or nodal levels) are the cornerstone of an energy internet. Future energy delivery networks will offer more transparent energy relations, higher efficiency and improved reliability.

Short CV
Dr. E. H. Tsoukalas received a PhD from the University of Illinois at Urbana-Champaign in 1989 and has served as Professor and Former Head of the School of Nuclear Engineering at Purdue University (West Lafayette, Indiana). Dr. Tsoukalas has nearly 25 years of experience in developing smart energy techniques and over 200 research publications in the area including a book titled “Fuzzy and Neural Approaches in Engineering,” (John Wiley & Sons, New York, 1997). Dr. Tsoukalas has served in advisory and consulting positions for the Ministry of Education, Ontario Canada; the International Atomic Energy Agency (IAEA), Vienna, Austria; the European Commission, Brussels, Belgium; the Agency for Science, Technology and Research (ASTAR) of the Government of Singapore; and the US Department of Energy. Dr. Tsoukalas is a Fellow of the American Nuclear Society and the 2009 recipient of the Humboldt Prize.