ICKMS Invited Speakers 

 

 

 

Prof. Anu Gokhale

St. Augustine’s University, USA

Biography:Dr. Anu A. Gokhale is currently a Professor and Chair of the Department of Computer Information Systems at Saint Augustine’s University. She has been selected as a 2023-24 Convergence Fellow by the Association of American Colleges & Universities. Gokhale visited Cairo University in Egypt in August 2022 as Fulbright Specialist in Data Analytics. Formerly, she was a Distinguished Professor and Coordinator of the Computer Systems Technology program at Illinois State University (ISU). Gokhale has completed thirty years as faculty and has received several College and University research, teaching and service awards. Having earned certifications in online delivery, she was recruited to mentor colleagues in online teaching beginning March 2020. Gokhale was named Fulbright Distinguished Chair in STEM+C at the University of Pernambuco, Brazil, 2016-17; was a Faculty Fellow in Israel and Fulbright Specialist in Cybersecurity at Gujarat Technological University, India in summer 2017. As a Visiting Professor in College of Business at Shandong University in Jinan, China in spring 2017, her focus was on e-commerce. Her achievements encompass extensively cited refereed publications; groundbreaking externally funded research supported by a continuous 20-year stream of grants from state and federal agencies including the National Science Foundation; and elevation of the ISU student experience through excellence in teaching, mentorship, and the creation of opportunities for students to get involved in research. Originally from India, she has a master’s in physics‒electronics from the College of William & Mary, and a doctorate from Iowa State University. Dr. Gokhale authored a second edition of her book Introduction to Telecommunications, which has an international edition in Chinese. She continues to be an invited keynote speaker at various conferences. As an active volunteer in IEEE, she has served as R4 Educational Activities Chair, Women in Engineering Coordinator, and MGA representative to the Educational Activities Board. She was honored with the IEEE Third Millennium Medal and 2019 Region 4 Outstanding Professional Award. She consults for business and industry to increase productivity using data analytics and business intelligence while leveraging e-technologies. She has delivered multiple workshops focusing on hybrid teaching & learning, inclusion & diversity, as well as on algorithms and data analytics.

Title of Speech: AI in Information Systems: Algorithm Design and Applications

Abstract: Enterprise information systems combined with latest developments in data mining strategies have created unprecedented opportunities for enhancing competitive advantage. Executives seek to leverage Artificial Intelligence (AI), the biggest driver of technological change, to inform decision-making. Corporate data environments include both structured and unstructured information and there exists tremendous potential to glean key insights for business advantage from the vast data that is available today and new data that is being constantly generated. Algorithms used in analyzing big data vary significantly based on the problem of study and its goals and objectives. The talk will address the issues and processes associated with analyzing big data in business information systems, applicable algorithms to enhance functionality and predictive analytics, and discuss how data-driven decisions support product/service innovation.

Assoc. Prof. Mohamed Zakaria Kurdi

University of Lynchburg in Virginia, USA

Biography: Dr. Kurdi is an Associate Professor of Computer Science at the University of Lynchburg in Virginia, USA. In addition to his Ph.D. in CS, he has an interdisciplinary background in Software Engineering, Cognitive Science, and Linguistics. Before joining the University of Lynchburg, he worked in several institutions in North America and Europe. His research interests are in text and data mining and their applications to areas like intelligent computer-assisted language education, authorship attribution, bioinformatics, and Social Network Analysis (SNA). He authored a two-volume textbook about Natural Language Processing (NLP) that was published in French and English. His recent work on text mining won two best paper awards and a nomination from three different international conferences.

Prof. Ta-Chung Chu

Southern Taiwan University of Science and Technology, Taiwan

Biography: Ta-Chung Chu received his Ph.D. degree from the Department of Industrial Engineering at the University of Texas at Arlington, USA. Dr. Chu is a professor in the Department of Industrial Management and Information, Southern Taiwan University of Science and Technology, Taiwan; he served as Department Chair from August 2010 to July 2016. His research interests are in fuzzy multiple criteria decision-making, fuzzy number ranking and their applications. Dr. Chu has published 53 refereed journal papers and 88 conference papers. He served as a reviewer for various international journals and has reviewed 243 journal papers. He was the Chairman of the Conference of Industrial Management and Information Application Innovation, Taiwan (IMIAI 2013/2014). Dr. Chu was listed in 「Career-Long Impact List」 and「Year Impact List」 of the World’s Top 2% Scientists 2021/2022, and was listed in 「Career-Long Impact List」 in 2023. Currently, he serves as Academic Editor of PLOS ONE (SCIE/IF:3.7/Q2) and Guest Editor of the Special Issue of Axioms (SCIE/IF:2.0/Q2): Advances in Fuzzy MCDM, Hybrid Methods, Fuzzy Number Ranking and Their Applications (https://www.mdpi.com/journal/axioms/special_issues/7F551OEE24).

Title of Speech: Ranking Alternatives by an Extension to Fuzzy VIKOR

Abstract: An extension to fuzzy VIKOR is proposed, where membership functions of fuzzy weighted weightings can be derived. The proposed extension can resolve the limitation of using approximation to represent multiplication of two positive triangular fuzzy numbers in existing methods. The total integral value is used to rank fuzzy numbers and formulas of ranking procedure are presented to help complete the proposed model. Finally, a numerical example is used to demonstrate the feasibility of the proposed extension.