2024 6th International Conference on Frontier Technologies of Information and Computer (ICFTIC 2024)

Keynote Speakers



Keynote Speakers of ICFTIC 2024

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Prof. Mohamad Sawan

Academician of the Canadian Academy of Engineering

Academician of the Royal Society of Canada

Academician of the Canadian Academy of Engineering

IEEE Fellow

Founder of the Advanced Neurochip Center of Westlake University

Westlake University, China

Mohamad Sawan, Fellow of the Canadian Academy of Engineering, Fellow of the Engineering Institute of Canada, Fellow of the Royal Society of Sciences of Canada, Fellow of the IEEE, is an internationally renowned scientist in the field of smart medical devices. He has made significant contributions in implantable and wearable medical devices based on smart microsystems. Professor Sawan got a Ph.D. in Electrical Engineering from University of Sherbrooke in 1990, was a postdoc fellow in Biomedical Engineering in McGill University in 1991, and was assistant professor, associate professor and full professor from 1991 to 2018 in Polytechnique, the Engineering School of University of Montreal. He joined the School of Engineering of Westlake University as a Chair Professor in 2018, he is the Founder and Principle Investigator the Center of Excellence in Biomedical Research on Advances-in-Chips Neurotechnologies (CenBRAIN Neurotech) in Westlake University.




Prof. Deshuang Huang

IEEE Fellow

Foreign Academician of Russian Academy of Engineering

Eastern Institute of Technology, Ningbo, China

黄德双,工学博士,教授,博士生导师,宁波东方理工大学(暂名)教授。国家科技创新2030-新一代人工智能重大项目首席科学家(主持人),国家科技创新2030-脑科学与类脑研究重大项目管理专家,国家自然科学基金委第十四届专家评审组成员。纽约科学院Active Member,IEEE Fellow,IAPR Fellow,AAIA Fellow,ACM SIGBIO中国奖励委员会委员,2014年度第11届IEEE生物信息学与计算生物学中的计算智能学术会议程序委员会主席(美国),2015年度国际神经网络联合会议(IJCNN2015)大会主席(爱尔兰),国际智能计算学术会议Founding Chair(已成功连续举办19年,EI和CCF C类会议),中国生物信息学会(筹)生物医学数据挖掘与计算专业委员会主任,中国计算机学会生物信息学专业委员会副主任。


迄今Google Scholar引用24220余次,H因子81。IEEE/ACM Transactions on Computational Biology and Bioinformatics,IEEE Transactions on Cognitive and Developmental Systems等国际杂志编委。已发表SCI收录论文260余篇,其中Genome Biology、PLOS Computational Biology、Bioinformatics和Brief in Bioinformatics等生物信息学领域影响因子大于5.0的论文50余篇,IEEE系列刊物69篇,SCI他引7100多次,发表在Neural Computation,Digital Signal Processing和Methods上的3篇论文分别被选为当期的封面。发表ESI论文4篇,入选2014-2022年度爱思唯尔(Elsevier)Scopus数据库中国高被引学者榜单(计算机科学卷)。出版专著3本,主编论文集86本,曾获1997年度第八届全国优秀科技图书二等奖(排名唯一),2010年度安徽省自然科学一等奖(排名第一),2016年度教育部自然科学一等奖(排名第一),2018年度吴文俊人工智能科技进步一等奖(排名第一)。授权发明和实用新型专利38项; 美国发明专利授权1项、日本发明专利授权2项、软件著作权7项。作为客座编辑,在14种国际SCI杂志已编辑出版31期刊物。


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Prof. Xiaoli Li

IEEE Fellow

Principal Scientist at the Institute for Infocomm Research

Nanyang Technological University, Singapore

Xiaoli is currently a department head (Machine Intellection department, consisting of 100+ AI and data scientists, which is the largest AI and data science group in Singapore) and a principal scientist at the Institute for Infocomm Research, A*STAR, Singapore. He also holds adjunct professor position at Nanyang Technological University (He was holding adjunct position at National University of Singapore for 6 years). He is an IEEE Fellow and Fellow of Asia-Pacific Artificial Intelligence Association (AAIA). Xiaoli is also serving as KPMG-I2R joint lab co-director. He has been a member of Information Technology Standards Committee (ITSC) from ESG Singapore and Infocomm Media Development Authority (IMDA) since 2020. Moreover, he serves as a health innovation expert panel member for the Ministry of Health (MOH), expert panel member for Ministry of Education (MOE), as well as an AI advisor for the Smart Nation and Digital Government Office (SNDGO), Prime Minister s Office, highlighting his extensive involvement in key Government and industry initiatives.

Title: AI-Driven Time Series Analytics: Revolutionizing Industry through Predictive Insights
Abstract: The rapid growth of sensor deployments in industries such as manufacturing, aerospace, transportation, and education has created immense opportunities to leverage AI for time-series data analytics. This keynote explores cutting-edge AI solutions that are driving real-world applications, from predictive maintenance and equipment diagnostics to real-time decision-making.
In manufacturing and aerospace, AI-driven analytics optimize operations by enabling predictive maintenance, minimizing downtime, and improving the accuracy and efficiency of machine remaining useful life predictions. We will address key challenges such as high accuracy requirements, model compression for edge computing, and domain adaptation across diverse industrial environments.
Additionally, AI is reshaping transportation through real-time analytics, including smart traffic management that enhances safety and efficiency.
Online learning platforms generate vast amounts of data, opening opportunities for enhancing and personalizing the learning experience. We will explore how AI can be used for knowledge tracing, predicting student performance, and identifying at-risk students, enabling timely interventions and tailored learning pathways.
Join us as we explore how AI is revolutionizing both industry and education, fueling innovation, and driving global competitiveness in today’s data-driven world.