May 04, 2013
By: Dr. Mohammed Benaissa, King Abdullah University of Science and Technology,
Date: Saturday, 4th May 2013,
Time: 12:00pm – 1:00pm,
Location: Building 9, Level 3, Room 3128,
Abstract:
The optoelectronic properties of devices based on quantum structures such as quantum dots and quantum wells are a function of composition, size and strain state around and within of the QDs/QWs. Tailoring and getting a thorough understanding of structure-property relationships of these confined nanostructures needs quantitative information about composition and microstructure on a nanometer scale. Such a performance requires the use of techniques with sub-Å spatial resolution and sub-eV energy resolution. A comprehensive study on GaN quantum dots/wells will be presented.
Biography:
Dr. Mohammed Benaissa is Senior Scientist and has more than 15 years’ experience in nanomaterials research. He has worked on wide bandgap semiconductors (GaN quantum dots/wells) during the last ten years using high-resolution microscopy/spectroscopy. His international experience includes work at the French CNRS; National Berkeley Lab (USA) and Max Planck Institute (Germany). He has published over 70 articles in peer review journals and international conference proceedings. He has been the head of the UATRS division (national facility at the National Research Center) for the past ten years.
April 27, 2013
By: Prof. Mostafa Kaveh, Centennial Professor of Electrical and Computer Engineering, Associate Dean for Research and Planning, College of Science and Engineering, University of Minnesota, USA,
Date: Saturday, 27th April 2013,
Time: 3:00pm – 4:00pm,
Location: Building 1, Level 3, Room 3119,
Abstract:
Signal processing techniques and technologies are truly ubiquitous in the devices and services that we take for granted in this age of information. The Field of Interest (FOI) of the IEEE Signal Processing Society http://www.signalprocessingsociety.org/about-sps/scope-mission/ succinctly describes the fundamental components and aims of what is, and likely to be in the foreseeable future, broadly defined as signal processing. This statement also highlights the blurred lines and convergence of approaches with a number of other fields such as computing, information theory, communications and networking, and machine intelligence.
This talk will provide a perspective on the history of the development of modern signal processing as manifested in the growth and technical diversification of the field and its professional portfolio. A number of examples are provided to illustrate the trends in the field and some likely future directions made possible by developments in sensing, computational and communication technologies, and opportunities ranging from entertainment togrand challenge problems in energy and health care.
Biography:
Mostafa Kaveh received his BS and PhD degrees in electrical engineering from Purdue University in 1969 and 1974, respectively, and his MS degree from the University of California at Berkeley in 1970. He is the Centennial Professor of Electrical and Computer Engineering, and the Associate Dean for Research and Planning for the College of Science and Engineering at the University of Minnesota. He served as the Head of his department from 1990 -2005. His research and educationalactivities have been on a variety of areas of signal and image processing and digital communications, including the processing of sensor array signals, image reconstruction and tomography and wireless communications.
Dr. Kaveh is the Past- President of the IEEE Signal Processing Society (SPS), and has served this Society in a number of editorial and leadership positions over the past three decades. His recognitions and honors from the IEEE include Fellow of the IEEE, authorship or co-authorship of three best paper awards from the IEEE Acoustics, Speech and Signal Processing Society (ASSP), the 1988 IEEE ASSP Meritorious Service Award, an IEEE Third Millennium Medal, and the 2000 Society Award of the IEEE Signal Processing Society. In 2002, he received an Outstanding Electrical and Computer Engineer Award from Purdue University.
April 27, 2013
By: Dr. Ayman Naguib, Qualcomm Corporate Research and Development, USA,
Date: Saturday, 27th April 2013,
Time: 12:00pm – 1:00pm,
Location: Building 9, Level 3, Room 3128,
Abstract:
Indoor positioning is the next frontier in location technology for mobile devices. The popularity of smartphones and location based applications is driving GPS attach rates on handsets to unprecedented levels. However a whole new world indoors, remains unexplored. New technology is needed for enabling positioning indoors and several new applications can benefit from the presence of such capability such as navigation and search, aisle level location of retail items, check-ins, gaming etc.
Indoor positioning is an extremely challenging problem since traditional positioning systems such as GPS either fail completely indoors or fail to provide the desired level of accuracy. This talk will discuss multiple sources of information including radio measurements, sensor data and building maps that can be used for indoor positioning and describe how probabilistic inference techniques can be used to combine these to obtain precise indoor location on a smartphone. This talk will also provide an overview of the indoor location, discusses several use cases, challenges and approaches to dealing with them.
Biography:
Dr. Ayman Naguib is a Director of Engineering at Qualcomm Corporate Research and Development, where he is leading the indoor positioning and navigation research in Qualcomm’s CR&D. Dr. Naguib has over 17 years of experience in wireless systems research and design. Dr. Naguib received his the B.S. and M.S. in electrical in engineering from Cairo University in 1987 and 1990 resp., and M.S. in Statistics and the Ph.D. in Electrical Engineering from Stanford University in 1993 and 1995 resp. Dr. Naguib has over 50 journal and papers publications in international conferences and journals and 3 book chapters. Dr. Naguib won two IEEE best paper awards and was named an IEEE fellow in Dec 2006 for his pioneering work on space-time coding and signal processing. Dr. Naguib has 46 granted US Patents and over 90 other pending patent applications.
April 24, 2013
By: Prof. Fadhel Ghannouchi, Professor, Alberta Innovates Strategic Chair and Canada Research Chair in Green Radio Systems.
Department of Electrical and Computer Engineering, University of Calgary, Canada,
Date: Wednesday, 24th April 2013,
Time: 10:00am – 11:00am,
Location: Building 3, Level 5, Room 5220,
Abstract:
Data traffic and wireless applications have experienced exponential growth; and, in order to cope with the demand for higher capacity, the numbers of base stations and networks are increasing rapidly. This increase raises several cost and environmentally related challenges for wireless network infrastructure providers and operators, as well safety related concerns forusers and government regulators. In order to reduce operating costs and minimize the carbon dioxide (CO2) emission footprint of communication networks, many wireless infrastructure providers and operators have been highly active in investigating new approaches and techniques to reduce energy consumption ofbase stations, mobile terminals and communication networks with the aim of implementing and deploying power-efficient “green” radio architectures and smart-grid wireless communication networks. This talk will highlight the why it important to reduce power consumption of communications network and how we can achieve it by adopting a holistic and end-to-end-comprehensive approach, crossing the different layers of the Open System Interconnection (OSI) model.
Biography:
Fadhel M. Ghannouchi is currently a professor, Alberta Innovates Technology Futures Strategic Chair and Senior Canada Research Chair in Green Radio Systems and Founding Director of the iRadio Laboratory(
www.iradio.ucalgary.ca) in the Department of Electrical and Computer Engineering at the University of Calgary, Alberta His research interests are in the areas of RF and wireless communications, nonlinear modeling of microwave devices and communications systems, design of power- and spectrum-efficientradio systems and design of SDR systems for wireless and satellite communications applications and sensors networks. His research has led to over 600 refereed publications and 14 US patents (6 pending), 3 books and 3 spun-off companies.
April 14, 2013
By: Prof. Geert Leus, Delft University of Technology, Netherlands,
Date: Saturday, 14th April 2013,
Time: 9:00am – 10:00am,
Location: Building 1, Level 2, Room 2202,
Abstract:
The problem of source localization from time-difference-of-arrival (TDOA) measurements is in general a non-convex and complex problem due to its hyperbolic nature. This problem becomes even more complicated for the case of multi-source localization where TDOAs should be assigned to their respective sources. We simplify this problem to an l1-norm minimization by introducing a novel TDOA fingerprinting and grid design model for a multi-source scenario. Moreover, we propose an innovative trick to enhance the performance of our proposed fingerprinting model in terms of the number of identifiable sources. An interesting by-product of this enhanced model is that under some conditions we can convert the given underdetermined problem to an overdetermined one and efficiently solve it using classical least squares (LS) approaches. Finally, we also tackle the problem of off-grid source localization as a case of grid mismatch. Our extensive simulation results illustrate a good performance for the introduced TDOA fingerprinting.
Biography:
Prof. Geert Leus received the electrical engineering degree and the PhD degree in applied sciences from the Katholieke Universiteit Leuven, Belgium, in June 1996 and May 2000, respectively. Currently, Geert Leus is an "Antoni van Leeuwenhoek" Full Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science of the Delft University of Technology, The Netherlands. His research interests are in the area of signal processing for communications. Geert Leus received a 2002 IEEE Signal Processing Society Young Author Best Paper Award and a 2005 IEEE Signal Processing Society Best Paper Award. He is a Fellow of the IEEE. Geert Leus was the Chair of the IEEE Signal Processing for Communications and Networking Technical Committee, and an Associate Editor for the IEEE Transactions on Signal Processing, the IEEE Transactions on Wireless Communications, and the IEEE Signal Processing Letters. Currently, he is a member of the IEEE Sensor Array and Multichannel Technical Committee and serves as the Editor in Chief of the EURASIP Journal on Advances in Signal Processing.
April 13, 2013
By: Prof. Geert Leus, Delft University of Technology, Netherlands,
Date: Saturday, 13th April 2013,
Time: 12:00pm – 1:00pm,
Location: Building 9, Level 3, Room 3128,
Abstract:
Spectrum sensing is a crucial ingredient of various types of applications, such as frequency spectrum sensing for cognitive radio and angular spectrum sensing for direction of arrival estimation. A popular tool that has recently been introduced for spectrum sensing is compressive sampling. Adopting this technique, it is possible to sample the measured signal below the Nyquist rate without compromising the reconstruction error, under the condition that the measured signal is sparse in some domain (frequency, angular, etc.). Current compressive spectrum sensing techniques mainly focus on reconstructing the signal itself. However, for many applications, this is overkill and estimating the power on every frequency or angle is sufficient. In this talk, we therefore present a new framework for reconstructing the power spectrum from compressive measurements, labeled as compressive power spectrum sensing. This allows for improved compression rates, and if designed properly, it even works without any sparsity constraints on the spectrum, i.e., it can also be used to reconstruct non-sparse spectra. We will first introduce the concept of compressive power spectrum sensing, and then more specifically focus on reconstructing frequency and angular power spectra from compressive measurements using for instance multi-coset sampling and non-uniform antenna arrays.
Biography:
Prof. Geert Leus received the electrical engineering degree and the PhD degree in applied sciences from the Katholieke Universiteit Leuven, Belgium, in June 1996 and May 2000, respectively. Currently, Geert Leus is an "Antoni van Leeuwenhoek" Full Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science of the Delft University of Technology, The Netherlands. His research interests are in the area of signal processing for communications. Geert Leus received a 2002 IEEE Signal Processing Society Young Author Best Paper Award and a 2005 IEEE Signal Processing Society Best Paper Award. He is a Fellow of the IEEE. Geert Leus was the Chair of the IEEE Signal Processing for Communications and Networking Technical Committee, and an Associate Editor for the IEEE Transactions on Signal Processing, the IEEE Transactions on Wireless Communications, and the IEEE Signal Processing Letters. Currently, he is a member of the IEEE Sensor Array and Multichannel Technical Committee and serves as the Editor in Chief of the EURASIP Journal on Advances in Signal Processing.
April 06, 2013
By: Dr. Amro M. Elshurafa, King Abdullah University of Science and Technology,
Date: Saturday, 6th April 2013,
Time: 12:00pm – 1:00pm,
Location: Building 9, Level 3, Room 3128,
Abstract:
Have you ever wondered why most insects fly while most mammals walk? Did it ever occur to you that most of the fat in the chicken is in the skin, while most of the fat in the buffalo is within the meat? Answering these questions can actually help us in designing better and smarter cellular phones! In this talk, I will answer the questions above along with many others akin to them, and then link the answers to the design of future wireless communication circuits based on MEMS technology.
Biography:
Dr. Amro M. Elshurafa received his PhD in electrical engineering in 2008 from Dalhousie University, Halifax, Nova Scotia, Canada, and immediately joined KAUST afterwards where he still remains. His research interests include design, modeling, fabrication, and testing of MEMS devices and circuits. Dr. Elshurafa is the (co)author of 35 papers and patents.
March 23, 2013
By: Prof. Taousmeriem Laleg, King Abdullah University of Science and Technology,
Date: Saturday, 23rd March 2013,
Time: 12:00pm – 1:00pm,
Location: Building 9, Level 3, Room 3128,
Abstract:
We are interested in this talk in the analysis of physical systems using a measured signal where the objective is to extract relevant information characterizing the system. We will focus on two approaches:
- The first approach consists in a new signal analysis method that we developed. It is based on a semi-classical analysis of the Schrödinger operator and it helps the extraction of information from the analysis of the morphology of the signal. We will show its application to the analysis of the arterial blood pressure waveform for clinical diagnosis purpose and introduce its generalization to image processing.
- The second approach uses mathematical modeling relating the measured signal with the information that we would like to extract. This can be viewed as an inverse problem, usually ill posed, that we propose to solve using a recursive approach based on observers. We will present two applications. The first example consists in the estimation of the neural activity and some relevant physiological variables using functional magnetic resonance imaging data (BOLD signal). The second example is about the estimation of the source for wave propagation.
Biography:
Dr. Laleg is assistant professor in applied mathematics at KAUST. She is also affiliated to the Electrical Engineering program. Dr. Laleg’s research interests encompass work across the fields of applied mathematics, control systems, and signal analysis. She works on modeling, estimation and analysis of some complex systems. She is especially interested in developing a new method for signal and image processing based on a semi-classical approach with an application to the analysis of the arterial blood pressure, data compression and the analysis of the performance of turbomachines. Dr. Laleg is also interested in solving some inverse problems using observers-based approaches with a focus on the estimation of the neuronal activation and some physiological variables from fMRI data and also on inverse problems for some partial differential equations.
March 16, 2013
By: Prof. Christian Claudel, King Abdullah University of Science and Technology,
Date: Saturday, 16th March 2013,
Time: 12:00pm – 1:00pm,
Location: Building 9, Level 3, Room 3128,
Abstract:
This talk describes a new architecture for distributed flood and traffic monitoring in cities using combined Eulerian and Lagrangian sensing. Unlike current traffic sensor networks, the architecture maintains user privacy by using a distributed computing approach. In this system, probe vehicles broadcast speed data to local nodes, which estimate vehicles location. Fixed sensors also measure traffic parameters, and all traffic data is forwarded to local coordinator nodes. Using the classical LWR traffic flow model, we show that the traffic reconstruction problem results in a set of MILPs, which can be efficiently solved by all nodes using distributed computing, the coordinator node supervising all computations. With this approach, user privacy is maintained, in the sense that no vehicle track data is forwarded beyond the radio range of the node cluster.
We present an implementation of this system using a custom designed flood and traffic sensor, and discuss some preliminary results."
Biography:
Dr Christian Claudel is an assistant professor of Electrical Engineering and Mechanical engineering at KAUST. He received the PhD degree in EECS from UC Berkeley in 2010, and the Ms degree in Plasma Physics from Ecole Normale Superieure de Lyon in 2004. He received the Leon Chua Award from UC Berkeley in 2010 for his work on Mobile Millennium. His research interests include control and estimation of distributed parameter systems, wireless sensor networks and environmental sensing systems
March 09, 2013
By: Dr. Ahmed Chemori, University of Montpellier 2 (UM2), France,
Date: Saturday, 9th March 2013,
Time: 12:00pm – 1:00pm,
Location: Building 9, Level 3, Room 3128,
Abstract:
This talk deals with two main challenging issues in humanoid robotics, namely pattern generation and control design. The presentation includes three main parts; the first one is an introduction to humanoid robotics, where their basic principles are recalled. The second part deals with the problem of pattern generation in humanoid robotics. It starts with the problem formulation of pattern generation, followed by some proposed solutions (such as B-spline based and human data based pattern generators) and their validations.
The third part of the presentation will be focused on control design of humanoid walking robots. First the problem formulation of control design is introduced, and then the proposed solutions are presented. The first solution deals with control of two-leg (with only lower limbs) biped walking robots. The proposed control architecture includes a ZMP-based pattern generator, an inverse dynamics controller, and a ZMP stabilizer to ensure dynamic walking stability. The proposed solution is validated through numerical simulations on the walking robot SHERPA.
The second solution, concerns whole-body control, and is based on human walking motion capture. This technique is a very interesting concept in design of human-like walking; where mainly joint positions are commonly used to create the human motion database. However, this method needs a huge amount of data. Therefore, a reduction of the data set is necessary to keep only the most valuable information; furthermore this can help for a better understanding of human walking and a smarter implementation of human-like walking on humanoid robots. In our study, we propose to take into account the above mentioned fact concerning data reduction. Consequently, only the feet and center of mass positions are needed to describe the important features of human walking. Then the redundancy of the humanoid robot is considered to track these two objectives using the task formalism. The proposed solution is validated by numerical simulations as well as real-time experiments on the humanoid robot HOAP3.
Biography:
Dr. Ahmed Chemori received his MSc and PhD degrees respectively in 2001 and 2005, both in automatic control from the Grenoble Institute of Technology. He has been a Post-doctoral fellow with the Automatic control laboratory of Grenoble, France in 2006. He is currently a tenured research scientist in Automatic control and Robotics at the Montpellier Laboratory of Informatics, Robotics, and Micro-electronics (LIRMM in French) which is a cross-faculty research entity of the University of Montpellier 2 (UM2) and the National Center for Scientific Research (CNRS). His research interests include nonlinear control, adaptive control, predictive control and their applications in humanoid robotics, underactuated mechanical systems, parallel robots, and underwater vehicles.