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Prof. Yang Xiao, The University of Alabama, USA

Fellow of IEEE, IET, AAIA

https://eng.ua.edu/eng-directory/dr-yang-xiao/

Yang Xiao is a full Professor at the Department of Computer Science, The University of Alabama, Tuscaloosa, AL, USA. Dr. Xiao directed over 20 doctoral dissertations and supervised over 20 M.S. theses/projects. He has published over 300 Science Citation Index (SCI)-indexed journal papers (including over 70 IEEE/ACM TRANSACTIONS) and 300 Engineering Index (EI)-indexed refereed conference papers and book chapters related to these research areas. His research interests include cyber-physical systems, the Internet of Things, security, wireless networks, smart grids, and telemedicine.

Prof. Xiao was a Voting Member of the IEEE 802.11 Working Group from 2001 to 2004, involving the IEEE 802.11 (Wi-Fi) standardization work. He is a Fellow of IEEE, IET, AAIA Fellow, AIIA, and ACIS. Dr. Xiao served as a Guest Editor over 35 times for different international journals, including the IEEE Journal on Selected Areas in Communications (JSAC) in 2022-2023, IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING (TNSE) in 2021, IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING in 2021, IEEE Network in 2007, IEEE WIRELESS COMMUNICATIONS in 2006 and 2021, IEEE Communications Standards Magazine in 2021, and Mobile Networks and Applications (MONET) (ACM/Springer) in 2008. He also serves as the Editor-in-Chief of Cyber-Physical Systems Journal, International Journal of Sensor Networks (IJSNet), and International Journal of Security and Networks (IJSN). Dr. Xiao has been serving as an Editorial Board Member or an Associate Editor for 20 international journals, including the IEEE TNSE since 2022, IEEE TRANSACTIONS ON CYBERNETICS since 2020, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS from 2014 to 2015, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY from 2007 to 2009, and IEEE COMMUNICATIONS SURVEYS AND TUTORIALS from 2007 to 2014. He serves/served as a Member of Technical Program Committee for more than 300 conferences. He received the IEEE TNSE Excellent Editor Award in 2022 and 2023.

(Onsite Talk) Speech Title: Personal Thoughts on Education

Abstract:  Having taught in universities for over twenty years, I would like to share some personal thoughts on education in general, particularly Computer Science (CS) education. In this talk, I will share my comments on several aspects of education: definition, objectives, effectiveness, retention, management, quality, length (short-term vs. long-term ), etc. Furthermore, I will discuss teaching evaluation, teaching vs. research, theory vs. practicality, etc.

Prof. James Tin-Yau KWOK, IEEE Fellow
Hong Kong University of Science and Technology

Prof. Kwok is a Professor in the Department of Computer Science and Engineering, Hong Kong University of Science and Technology. Pr of. Kwok served/is serving as an Associate Editor for the IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing, Artificial Intelligence Journal, International Journal of Data Science and Analytics, and on the Editorial Board of Machine Learning. He is also serving / served as Senior Area Chairs of major machine learning / AI conferences including NeurIPS, ICML, ICLR, IJCAI, and as Area Chairs of conferences including AAAI and ECML. Prof Kwok will be the IJCAI-2025 Program Chair. He is an IEEE Fellow.

(Online Talk) Speech Title: Enhancing Language Models through Improved Pre-Training and Fine-Tuning

Abstract: Language models (LMs) are essential in natural language processing and vision-language modeling. However, several challenges arise in pre-training and fine-tuning of LMs. First, when learning through unsupervised pre-training, information that are semantically irrelevant may negatively affect downstream tasks, leading to negative transfer. Second, cross-modal masked language modeling is often used to learn vision-language associations in vision-language models. However, existing masking strategies may be insufficient in that the masked tokens can sometimes be simply recovered with only the language information, ignoring the visual inputs. Lastly, prompt tuning is effective in fine-tuning LMs on downstream tasks with limited labeled samples, but prompt design is difficult.

To tackle these issues, we propose several measures. First, we introduce a new pre-training method that trains each expert with only semantically relevant data through cluster-conditional gates. This allows downstream tasks be allocated to customized models pre-trained on data most similar to the downstream data. Second, on pre-training vision-language models, we use a masking strategy based on the saliencies of language tokens to the image. Lastly, we use meta-learning to learn an efficient prompt pool that can extract diverse knowledge from historical tasks. This allows instance-dependent prompts to be constructed from the pool without tuning the whole LM. Experimental results show that these measures can significantly improve the performance of LMs.

Prof. Huan Li, Southwest University, China

Dr. Huan Li, a professor, PhD supervisor, and vice dean at the Faculty of Special Education in Southwest University, holds a distinguished position under the Hanhong Youth Talent program. Selected as a top young talent in the Chongqing Talent Program and awarded by the Ministry of Education's Fok Ying-Tong Education Foundation, Dr. Li is an expert in teacher education accreditation, children's resources, and educational evaluation in Chongqing, as well as a member of several psychological and inclusive education associations. Graduating from Peking University's School of Medicine and obtaining a PhD in education from Beijing Normal University, Dr. Li has dedicated their career to the research of language and reading disorders in special children, earning numerous awards and leading several national research projects. With over 30 SSCI and CSSCI papers and six monographs.

李欢，博士，教授，博士生导师，西南大学含弘优青岗，教育学部特殊教育学院副院长。首批入选重庆英才计划·青年拔尖人才，获教育部霍英东教育基金会第十七届高校青年教师奖，现为全国高等院校师范类专业认证专家，重庆市儿童资源中心专家，重庆市教育评估监测专家，中国心理卫生学会残疾人心理分会理事，中国残疾人事业发展研究会融合教育专业委员会委员，中国学生营养与健康促进会心理健康分会委员，任《International Journal of Inclusive Education》《International Journal of Disability, Development and Education》《International Journal of Chinese Education》《教育学报》等多个SSCI/SCOPUS/CSSCI期刊审稿专家。本科毕业于北京大学医学部，获医学学士学位；于北京师范大学教育学部特殊教育系硕博连读，获教育学博士学位。长期一直致力于特殊儿童语言障碍、阅读障碍相关研究，曾获高等教育国家级教学成果奖二等奖、顾明远教育发展基金会博士论文集、重庆市教学创新大赛一等奖等10余项教学及科研奖励，主持国家社科基金2项、主持国家民委科研项目、教育部人文社科项目等近20项，以第一作者或通讯作者发表SSCI及CSSCI论文30余篇，出版专著6部，科研成果获《光明日报》《人民日报》等50余家主流媒体全文转载。

(Onsite Talk) Speech Title: Identification and Intervention of Students With Dyslexia Supported by Educational Technology
Abstract: Dyslexia, a neurobiological learning disability in the reading domain that has symptoms in early childhood and persists throughout life, presents distinct challenges within educational systems. This review provides an exhaustive examination of how educational technology can support the needs of students with dyslexia, focusing on the identification and intervention processes. It begins by defining dyslexia, outlining the diagnostic criteria, and describing the typical symptoms and prevalent methods for its identification and intervention. Building on this framework, the review proactively highlights the critical roles played by advanced educational technologies in the precise assessment, diagnosis, and recognition of dyslexia. A critical examination of current technological challenges in practice lays the groundwork for the subsequent analysis. Through a meta-analysis approach, the review assesses the impact of these technologies on these students' progress and evaluates the hurdles faced while integrating technological solutions in educational settings. The latter part of the review is future-oriented, discussing the nascent potential of artificial intelligence (AI) in streamlining the identification and intervention process for dyslexia. The review concludes by advocating for responsible dissemination strategies to ensure these innovations offer inclusive, equitable support across diverse student populations, thereby transforming the learning landscape for individuals with dyslexia.