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ICCKE 2014 Keynote Speakers

Prof. Madjid Fathi

University of Siegen, Institute of Knowledge Based Systems & Knowledge Management

Siegen, Germany


Title: Knowledge Engineering and Web Based Technology for Neuro-Assistant System

Abstract: The common component in Bio-Medical Technology (Neuro Science) are Knowledge and Knowledge Engineering distributed in: reasoning (i.e. reasoning under uncertainty), discovery (Text Mining & recommender systeme) and decision-making. While reasoning requires some kind of simplification or adaption to deal with exceptions or to increase the usability of decision-making situations. Reasoning under uncertainty is interchangeably associated with the handling of uncertain knowledge for example in Neuro Science. Knowledge Engineering concentrates on conceptual handling with facts and solutions that enable the usage and further development of knowledge based techniques and methods to support human behavior and Assistant System based on decision-making, learning, planning or controlling. The problem solving abilities based on Knowledge Engineering reflect a human expert which separates the domain knowledge and related know-how. In our understanding many people suffer from neurological diseases like stroke, discus prolaps or dementia/Alzheimer, the patients abilities to fulfill tasks of everyday life decrease during the course of disease. Therefore the situation is not only difficult for a patient himself, but also for the family members who care for him and most often don’t have previous experience in this medical field. Also the integration of entire Knowledge Engineering component, Web-based technology, Text Mining and recommender System shows that an efficient management of HR is an important process for successful realization of Neuro Assistant system and increase the investment of substantial progress in Medical-education.


Biography: Prof. Madjid Fathi is a professor and director of Institute Knowledge Based Systems and Knowledge Management (KBS & KM), Department of Electrical Engineering and Computer Science at University of Siegen, Germany. Mr Fathi is the founder and director of Knowledge Management Center (KMC). He obtained his PhD degree from University of Dortmund in Germany, further he received his Habilitation(above Ph.D) degree at University of Ilmenau, Germany. Prof. Fathi’s research interests are focused on Knowledge Management and their Applications in Medicine (neuroscience Technology and learning) and Engineering, Knowledge Engineering and Expert Systems and Computational Intelligence. He is a senior member of IEEE and editorial board of 5 respective journals. He is the founder of Alzheimer Knowledge Platform (www.alwip.de). Mr. Fathi served as a Visiting Scholar(9/2012-9/2013) at EECS Department, U.C. Berkeley, hosted by Prof. Zadeh, the father of Fuzzy Logic. The latest keynote speeches of Prof. Fathi were at IEEE EIT2008, IEEE EIT 2009, KMIS 2009, IEEE-SMC (UK) 2009, KMI 2010, KMI2011, ICCKE2012 KMAP2012, HeathGIS2013, KMI2014, IEEE EIT 2014, ICCESEN2014.

Time: October 29, 2014 -  8 – 9 AM

Link: http://webinar2.um.ac.ir/r4hmzibtg7u


Prof. Mohammad-R. Akbarzadeh-T.

Department of Electrical Engineering, Center of Excellence on Soft Computing and Intelligent Information Processing, FUM


Title: Agencies of Intelligence: From the Macro to the Nano

Abstract: ‘Homo sapiens’ (Latin for ‘Wise Man’) is what we call our species. Wisdom and Intelligence stands at the center of how we define ourselves. But what is intelligence? In this lecture, we review an array of perspectives from the outer behavioral aspects of intelligence to its inner compositional. Our journey will walk us through the concept of omnipotency where an entity has it all, knows it all, and does it all; to the nanopotency where the entity has little, knows little, and does little. From the original manifestation of the human dream to create the omnipotent being that could generalize, learn, and optimize, we now come to its recent realization that perhaps less is more. We will illustrate by sharing a few of our findings on traditionally hard problems such as robotics, urban traffic, computer networks, and judicial/medical decision making to the more evasive and humanly profound problems such as the atherosclerosis and cancer.

Biography: Prof. Mohammad-R. Akbarzadeh-T. (Senior Member, IEEE) received his PhD on Evolutionary Optimization and Fuzzy Control of Complex Systems from the department of electrical and computer engineering at the University of New Mexico in 1998.

He currently holds dual appointment as professor in the departments of electrical engineering and computer engineering at Ferdowsi University of Mashhad. In 2006-2007, he completed a one year visiting scholar position at Berkeley Initiative on Soft Computing (BISC), UC Berkeley. From 1996-2002, he was affiliated with the NASA Center for Autonomous Control Engineering at University of New Mexico (UNM).

Prof. Akbarzadeh is the founding president of the Intelligent Systems Scientific Society of Iran, the founding councilor representing the Iranian Coalition on Soft Computing in IFSA, and a council member of the Iranian Fuzzy Systems Society. He is also a life member of Eta Kappa Nu (The Electrical Engineering Honor Society), Kappa Mu Epsilon (The Mathematics Honor Society), and the Golden Key National Honor Society. He has received several awards including: the IDB Excellent Leadership Award in 2010, The IDB Excellent Performance Award in 2009, the Outstanding Faculty Award in 2008 and 2002, the IDB Merit Scholarship for High Technology in 2006, the Outstanding Faculty Award in Support of Student Scientific Activities in 2004, Outstanding Graduate Student Award in 1998, and Service Award from the Mathematics Honor Society in 1989. His research interests are in the areas of evolutionary algorithms, fuzzy logic and control, soft computing, multi-agent systems, complex systems, robotics, and biomedical engineering systems. He has published over 250 peer-reviewed articles in these and related research fields.

Time: October 30, 2014 -  8 – 9 AM

Link: http://webinar2.um.ac.ir/r52jvqgh89z

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