Abstract:

This talk will focus on pioneering future directions and innovation in smart wearable embedded solutions and Internet of Things (IoT) with applications in connected health and biomedical signal processing. Prof. Amira will discuss and explore different solutions for the development of software tools and hardware accelerators for wearable connected health solutions using Internet of Things (IoT) technologies, smart SoC platforms, heterogeneous data acquisition, visualization and analysis using advanced signal processing, pattern recognition and classification algorithms.
Connected health is the convergence of medical devices, security devices, and communication technologies. It enables patients to be monitored and treated remotely from their home or primary care facility rather than attend outpatient clinics or be admitted to hospital. This new health management model creates an environment where patients are treated in the best location, by the best person, using the most relevant and efficient methods. In this talk Prof. Amira will give a thorough overview of the existing embedded solutions for connecting health applications looking at different challenges and opportunities.
Prof. Amira will present his current research activities in the area of connected health which focuses on the design and implementation of real-time systems for remote monitoring and imaging using reconfigurable intelligent computing. Prof. Amira will address different software and hardware issues related to the implementation of pattern recognition, fusion and compressive sensing algorithms used in connected health applications such as falls detection, ECG/EEG monitoring, gait analysis and medical imaging. The talk will review the latest reconfigurable hardware and IoT technologies for real-time embedded systems, and will conclude with comprehensive case studies demonstrating the deployment of low power reconfigurable architectures for algorithms acceleration and performance evaluation methods for reconfigurable intelligent computing systems.

Biography:
Prof. Abbes Amira received his Ph.D. in Computer Engineering in 2001 from Queen’s University Belfast, United Kingdom. Since then, he has taken many academic and consultancy positions in the United Kingdom, Europe, Asia and the Middleast.  He is currently the acting associate Dean for research and graduate studies in the College of Engineering at Qatar University.
During his career to date, Prof. Amira has been successful in securing substantial funding from government agencies and industry; he has supervised more than 20 PhD students and  has over 280 publications in top journals and conferences in the area of embedded computing, image and signal processing.
He has been invited to give keynote talks, short courses and tutorials at many universities and international conferences and has been chair and program committee for a number of IEEE conferences including; tutorial and invited talk at the prestigious ICIP 2009 and ICCV – ECVW, General Co-Chair of ECVW 2011, Program Chair of ECVW2010, Program Co-Chair of ICM12, DELTA 2008, IMVIP 2005 and General Co-Chair of ICM 2014.
He is also a member of the IEEE Technical Committee for Biomedical Circuits and systems.
He obtained many international awards, including the 2008 VARIAN prize offered by the Swiss Society of Radiobiology and Medical Physics.
Prof. Amira has been a PhD external examiner and member of advisory boards for many Universities worldwide and has participated as guest editor and member of the editorial board in many international journals. He has also been a regular referee for many national and international funding bodies, including (EPSRC-UK and QNRF-Qatar). 
He has taken visiting professor positions at the University of Tun Hussein Onn, Malaysia and the University of Nancy, Henri Poincare, France.
Prof. Amira is a Fellow of IET, Fellow of the Higher Education Academy, Senior member of the IEEE, and Senior member of ACM.

• His research interests include: Embedded systems, high performance computing, Big Data and IoT, Connected Health, Image and Vision Systems, Biometric and Security.