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Invited Speakers

 

Prof. Torsten Schön

AImotion Institute Technische Hochschule Ingolstadt Ingolstadt, Germany

Biography: Prof. Dr. Torsten Schön is a research professor for Computer Vision for Intelligent Mobility Systems at the Technische Hochschule Ingolstadt (THI). His research group is concerned with deep learning methods for analyzing and generating image data. Data from different imaging sensors in two- and three-dimensional space are processed. The aim of the research group is to develop super-human perception for automated vehicles, aircraft, rail vehicles and other means of transport, and to analyze image data from infrastructure sensors for traffic monitoring. Before joining THI, he was working in the research and development department of the AUDI AG for 6 years.
In addition to the efforts in the mobility sector, the research group is committed to the use of computer vision for improved environmental protection and more sustainability.

Assoc. Prof. Maizatul Akmar Ismail

University of Malaya (UM), Malaysia

Biography: Dr. Maizatul Akmar Ismail is an Associate Professor at the Department of Information Systems, Faculty of Computer Science and Information Technology, University of Malaya (UM), Malaysia. Her academic qualifications were obtained from Universiti Malaya (UM) for her Bachelor's and Ph.D. degree, and the University of Putra Malaysia for her master's. At present, she has more than twenty years of teaching experience since she started her career as a lecturer at the Universiti Malaya. Maizatul was involved in various research, leading to the publication of several academic papers in the areas of Information Systems specifically on Educational Technology, Recommender Systems, and Data Mining. She has been actively publishing more than 70 conference papers at renowned local and international conferences. A number of her works were also published in reputable international journals. Maizatul has participated in many competitions and exhibitions to promote her research works. She has been appointed as Competition Judges for several innovation competitions.  She hopes to extend her research beyond Information Systems in her quest to elevate the quality of teaching and learning.

Speech Title: Recommendation Systems in Education Domain: Opportunities and Challenges with Generative AI

Abstract: Recommender systems within the context of education encounter a number of distinct obstacles in contrast to other fields. The aforementioned issues offer significant obstacles to the development of recommendation systems that are both efficient and ethically acceptable for educational objectives, particularly with the advancement in the field of generative AI. Several significant issues arise in this context. Among others are the preservation of data privacy and security, diversity of user profiles, ethical considerations, content quality and diversity, cold start issues, motivation, and engagement. In order to effectively tackle these issues in educational recommender systems, it is imperative to use a meticulous strategy that takes into account the distinct requirements and preferences of the education sector while upholding ethical values and complying with legal restrictions.