Professor Dato’ Dr. Mazliham Mohd Su’ud
President / Chief Executive Officer, Universiti Kuala Lumpur
Professor Dato’ Dr. Mazliham was born on 8th September 1967 in Johor, a southern state of Peninsular Malaysia. At the age of 19, he earned a Malaysian government scholarship to further his studies in Europe, earning his place at the Universite de Montpellier II - Sciences et Techniques du Languedoc, Montpellier, France. After 7 years in France, Professor Mazliham returned to Malaysia having completed his Post Master Degree in Electronics.
For his accomplishments thus far, he was awarded a state award by the Sultan of Pahang (“Darjah Sultan Ahmad Shah Pahang”) which carries the title “Dato” in 2013. In May 2015, he was conferred the Chevalier in the l’Ordre National du Merite (The National Order of Merit) award by the President of the French Republic bestowed to Dato’ Mazliham by His Excellency Mr. Christophe Penot, Ambassador of France to Malaysia. This award is one of the two highest awards by the French Government awarded to French citizens as well as foreign nationals for distinguished civil or military achievements.
Professeur BAILLARGEAT Dominique
(Director CNRS of XLIM UMR 7252 CNRS/University of Limoges, France)
Biography: D. BAILLARGEAT (49) is Senior Member IEEE. He is Professor at the University of Limoges (France) and visiting Professor at Nanyang Technological University of Singapore. He is currently the Director of XLIM a joint research institute of CNRS and University of Limoges and the Director of Lab of Excellence SIGMA_LIM. From September 2009 to August 2013 he was the Director of the research laboratory CINTRA in Singapore. D Baillargeat has done a lot of research activities on CAD applied to the packaging and the design of RF and mmW devices. His research work is mainly in the following areas: (1) Modeling and design of RF and mmW components and modules, (2) Use of specific technologies (muliti-layer, additive, nanotechnologies) for the design of RF and mmW components, (nano)packaging (interconnect), 3D integration. Prof Baillargeat has been involved in many projects (past and present) either as XLIM scientific responsible or collaborator through funding from the ANR, European Community, ESA, CNES or with industrial partners (Thales, EADS etc). He has been the advisor of 30 graduated PhD students. D Baillargeat has co-authored more than 70 articles in international journals and books, and 180 communications in international conferences.
Keynote title: The Advanced progresses from additive manufacturing to nanotechnologies for RF to mm- wave multilayer circuits and 3D structures
Abstract: During the presentation, we will describe our latest contributions on the several aspects regarding: (1) the additive manufacturing processes we are developing (stereo lithography) or using (LTCC) with, in particular the specific use of ceramic materials (2) the use of nanotechnologies dedicated to the fabrication of CNTs based mmW interconnects for RF to sub-mmW packaging (3) the multilayer structures we are fabricating dedicated to RF and mmW components and packaging for 3D integration. Test structures operating at 50/60GHz and beyond 100GHz have been fabricated and tested with success. That demonstrates the potential of such technologies.
Dr. Saleh Alshehri
(Director of Research and Applied Sciences Center – Jubail University College)
Dr. Saleh Alshehri is the director of the research and applied sciences center in Jubail University College in Saudi Arabia. of computer science and engineering department at Jubail University College in Saudi Arabia. His specialization is computer engineering. His research areas include computer architecture, medical equipment design, pattern recognition and image processing.
Keynote Title: Breast Cancer Detection Using Ultra-Wideband and Neural Networks Techniques
Breast cancer is one of the main causes of women’s death. Early detection of tumors increases the chances of overcoming this disease. There are several diagnostic methods for detecting tumors, each of which has its own limitations. Recently, Ultra-Wideband (UWB) imaging has gained wide acceptance for several good features such as its specificity and lack of ionizing radiation. The confocal method has been the dominant technique in this area based on homogeneous breast tissues and prior knowledge of tissue permittivity. Hence it is impractical and difficult to be implemented clinically.
This work has focused on the development of a complete non-confocal system for breast tumor detection using Neural Network (NN)-based Ultra-Wideband (UWB) imaging considering both homogeneous and heterogeneous tissues.
At the simulation stage, a feed-forward NN model was developed to identify the existence, size, and location of tumors in a breast model. A modified Principle Feature Analysis (PFA) method was implemented to reduce the feature vector size and extract the most informative features. The extracted features from the received UWB signals were fed into the NN model to train, validate, and test it first and then to detect the presence, size, and location of possible breast tumors.