Dr. Madjid Fathi
University of Siegen, Germany
Dr. Madjid Fathi is a Professor and Head of KBS & KM (Knowledge Based System & Knowledge Management) institute at the EECS Department at the University of Siegen, Germany. He obtained his M.Sc. degree in Com-puter Science and Ph.D. degree (Dr.-Ing.) both from the University of Dortmund, Germany, in 1986 and 1991, respectively. Accordingly he obtained Habilitation degree (Post-Doctorate) at the University of Ilmenau, Germa-ny, in 1998. Before he got the Professor at the Department of Electrical Engineering and Computer Science at the University of Siegen he was visiting scholar at Florida State university and from 2003 at LMM (Lab for Mi-cromechanics- Prof. Garmestani) Georgia Institute of Technology. Since 2004, he is with Unviersity of Siegen. He was Visiting Scholar with Professor Zadeh father of Fuzzy Logic at U.C. Berkeley dept. of EECS and joined the BISC (Berkeley Initiative of Soft Computing) from Sep/2012 to Sept/2013. As head of KBS lead a large of different academic team of researchers and educators which has, thus far, resulted in over 60 theses. His re-search interests are focused on Knowledge Based System(KBS), knowledge management and their applications in medicine and engineering, knowledge transfer, organizational learning, and knowledge discovery from text (KDT).
He is the editor of “Integration of Practice-Oriented Knowledge Technology” (2013) and “Integrated Systems, Design and Technology” (2011) published by Springer, as well as three(text book- the last one has been pub-lished in October 2109 with the title: Computer addid Writing by Soringer)and five edited books. He, with his students, has published with more than 270 publications including 30 Journal publications, and obtained four paper awards. He got the European Award Cute-prize 2015. He is a senior member of IEEE as well as member of editorial board of five respective journals. He is the founder of Alzheimer Knowledge Platform www.Alwip.de.
Title: Artificial Intelligent & Knowledge Technology for progressive quality in agricultural economy
ARecent developments in the agricultural economics also in food consumption industry have introduced numerous challenges. These challenges stem from increased production demands, novel marketing strategies, enhanced service expectations, and efficient management practices. Addressing these multifaceted challenges requires a heightened emphasis on improving the quality of various aspects within this dynamic process. Navigating through the vast volumes of production data, environmental insights, extensive existing knowledge, and accumulated experiential wisdom poses a significant challenge for human resources. This necessitates effective strategies to manage these resources. Moreover, the integration of cyber-technological advancements can prove instrumental due to their ability to swiftly gather data, utilize metadata for data fusion, and offer additional functionalities.
Artificial Intelligence (AI) holds promise in tackling complex tasks, but their solutions often demand extended time or remain unattainable due to time-sensitive data availability. Developing AI algorithms becomes paramount in enhancing our ability to comprehend the intricacies inherent in the challenges we seek to address. While production speed and technical logistics enable rapid distribution, they can inadvertently compromise the sensory experience for consumers, leading to a gap in flavor satisfaction. This, in turn, disrupts the agricultural processes, creating a cyclical production issue. Exploring the potential of AI-driven resources such as learning algorithms, decision-making frameworks, and recommendation systems becomes crucial in addressing problems that may be insurmountable using conventional methods. AI's core components encompass knowledge acquisition, meta-knowledge utilization, and metadata integration, forming the cornerstone of its technological capabilities. By leveraging these resources, we aim to uncover innovative solutions that transcend the limitations of traditional approaches.