ICIME Keynote Speakers
Prof. Xiaoli Li, Singapore University of Technology
and Design, Singapore (IEEE Fellow and AAIA Fellow)
Prof Li Xiaoli joined SUTD on 15 August 2025 as Head of the
Information Systems Technology and Design (ISTD) Pillar. In this role, he
provides strategic leadership in academic programme development, research
direction, and industry engagement across the Pillar.
Prof Li brings over 30 years of combined experience in academia and industry.
Before joining SUTD, he was the Department Head of Machine Intellection at
A*STAR Institute for Infocomm Research (I²R), where he led more than 100
scientists to develop cutting-edge AI technologies that delivered high-impact
solutions across diverse sectors. He also served as the Technical Director of
the Sectoral AI Centre of Excellence for Manufacturing (AIMfg)—a national
initiative supported by the Ministry of Trade and Industry (MTI) with a funding
of S$35.8 million.
He has been a trusted advisor and technical panel member for several key
government agencies, including the Infocomm Media Development Authority (IMDA),
Ministry of Education (MOE), Ministry of Health (MOH), and the Smart Nation and
Digital Government Office (SNDGO) under the Prime Minister’s Office. In
academia, he has held adjunct faculty appointments at both the National
University of Singapore (NUS) and Nanyang Technological University (NTU).
Prof Li is internationally recognised in the AI community and has held
leadership roles at top-tier conferences including NeurIPS, ICLR, KDD, ICDM,
WWW, IJCAI, AAAI, ACL, and EMNLP—serving as Conference Chair, Area Chair,
Workshop Chair, and Session Chair.
He has published over 380 research papers in leading AI and data science
conferences and journals. He is currently an Associate Editor of IEEE
Transactions on Artificial Intelligence. His research excellence is widely
acknowledged—he has been named a Clarivate Highly Cited Researcher and is listed
among the world’s top 2% scientists by Stanford University.
In addition to his academic credentials, Prof Li has deep industry experience.
He has led more than 10 collaborative R&D projects with partners across
verticals including aerospace, telecommunications, insurance, and aviation. He
has also served as joint lab director with industry leaders such as DBS,
Singtel, and KPMG. His expertise in AI, machine learning, and data mining has
enabled him to develop innovative solutions addressing complex real-world
challenges.
Prof. Irwin King, The Chinese University of Hong Kong
(ACM Fellow, IEEE Fellow, INNS Fellow and AAIA Fellow)
Professor Irwin King, a distinguished professor at the Department of Computer Science & Engineering, The Chinese University of Hong Kong. His research interests span machine learning, social computing, artificial intelligence, and data mining. Professor King’s extensive research has been recognized through numerous publications and awards in internationally renowned venues. He holds prestigious fellowships in the IEEE, INNS, AAIA, and HKIE, and is an ACM Distinguished Member. In addition to his research work, he has also been an evangelist, promoting E-Learning with AI technology. He serves as the Director of the ELearning Innovation and Technology (ELITE) Centre, the Machine Intelligence and Social Computing (MISC) Lab, and the Trustworthy Machine Intelligent Joint Lab. Professor King obtained his Bachelor of Science degree from California Institute of Technology (Caltech) and his Master’s and Doctorate degrees in Computer Science from the University of Southern California (USC).
Prof. Tomoaki Otsuki, Keio University, Japan (IEICE
fellow, AAIA fellow)
Tomoaki Otsuki (Ohtsuki) received the B.E., M.E., and Ph. D.
degrees in Electrical Engineering from Keio University, Yokohama, Japan in 1990,
1992, and 1994, respectively. From 1994 to 1995 he was a Post Doctoral Fellow
and a Visiting Researcher in Electrical Engineering at Keio University. From
1993 to 1995 he was a Special Researcher of Fellowships of the Japan Society for
the Promotion of Science for Japanese Junior Scientists. From 1995 to 2005 he
was with Science University of Tokyo. In 2005 he joined Keio University. He is
now a Professor at Keio University. From 1998 to 1999 he was with the department
of electrical engineering and computer sciences, University of California,
Berkeley. He is engaged in research on wireless communications, optical
communications, signal processing, and information theory. Dr. Ohtsuki is a
recipient of the 1997 Inoue Research Award for Young Scientist, the 1997 Hiroshi
Ando Memorial Young Engineering Award, Ericsson Young Scientist Award 2000, 2002
Funai Information and Science Award for Young Scientist, IEEE the 1st
Asia-Pacific Young Researcher Award 2001, the 5th International Communication
Foundation (ICF) Research Award, 2011 IEEE SPCE Outstanding Service Award, the
27th TELECOM System Technology Award, ETRI Journal’s 2012 Best Reviewer Award,
9th International Conference on Communications and Networking in China 2014
(CHINACOM ’14) Best Paper Award, 2020 Yagami Award, The 26th Asia-Pacific
Conference on Communications (APCC2021) Best Paper Award, and International
Conference on Internet of Things, Communication and Intelligent Technology
(IoTCIT) 2024 Best Paper Award. He has published more than 276 journal papers
and 518 international conference papers.
He served as a Chair of IEEE Communications Society, Signal Processing for
Communications and Electronics Technical Committee. He served as a technical
editor of the IEEE Wireless Communications Magazine and an editor of Elsevier
Physical Communications. He is now serving as an Area Editor of the IEEE
Transactions on Vehicular Technology and an editor of the IEEE Communications
Surveys and Tutorials. He is also serving as the IEEE Communications Society,
Asia Pacific Board Director. He has served as general-co chair, symposium
co-chair, and TPC co-chair of many conferences, including IEEE GLOBECOM 2008,
SPC, IEEE ICC 2011, CTS, IEEE GLOBECOM 2012, SPC, IEEE ICC 2020, SPC, IEEE
APWCS, IEEE SPAWC, and IEEE VTC. He gave tutorials and keynote speeches at many
international conferences including IEEE VTC, IEEE PIMRC, IEEE WCNC, and so on.
He was Vice President and President of the Communications Society of the IEICE,
also he was a distinguished lecturer of the IEEE. He is a fellow of the IEICE, a
Fellow of Asia-Pacific Artificial Intelligence Association (AAIA), a senior
member of the IEEE, and a member of the Engineering Academy of Japan.
ICIME Invited Speakers
Associate Professor Anirut Satiman, Silpakorn University, Bangkok, Thailand
Anirut Satiman is Associate Professor of Educational
Technology, Department of Educational Technology, Faculty of Education,
Silpakorn University, Bangkok, Thailand.
He received a bachelor of education B.Ed. in Educational Technology from the
Faculty of Education, Naresuan University, Thailand, in 1996, and a master of
education M.Ed. in Educational Technology from the Faculty of Education,
Srinakharinwirot University, Bangkok, Thailand, in 1999. He received a doctorate
degree of education (Ed.D.) in Educational Technology from Srinakharinwirot
University, Bangkok, Thailand, in 2007. He received a certificate (e-learning)
from IACE Busan National University, South Korea (2009) and received a Visiting
Scholarship on Instructional Technology, e-Learning, and ICT for Education at
the School of Education, San Jose State University, California, USA. (2006)
From 2002 to 2024, he worked at Silpakorn University. His administrative
experience: Program Chair, Ph.D. Program in Educational Technology, Faculty of
Education, Silpakorn University (2021–present). Vice President, Thailand
Association of Educational Communications and Technology (ThaiAECT),
https://thaiaect.org (2019–present). Committee of Thailand Cyber University
Project (TCU) and Thai MOOCs Ministry of Higher Education Science Research and
Innovation (2005–present). Committee Professional and Organizational Development
Network of Thailand Higher Education (Thailand POD): http://www.thailandpod.org
(20018–present).
His research interests center on computers for education, ICT for education,
online education, MOOCs, e-learning, technology of education, and knowledge
management (KM).
Associate Professor Vincent CS Lee, Monash University, Australia
Vincent CS Lee (PhD, FIEAust, SMIEEE) is an Associate
Professor (top level), Department of Data Science and Artificial Intelligence,
Faculty of IT, Monash University (Go8), Australia. His research spans across AI
in Digital Health, Signal and Information Processing, Financial Innovation
Technology, Edge Computing, Multimodal Deep Active Learning and Reasoning,
Educational Data Mining. Lee published together 200+ Q1 papers in IEEE
Transactions on Knowledge and Data Engineering, IEEE Transactions on Signal
Processing, IEEE Selected Areas in Communications, European Journal of
Operational Research, Expert Systems with Applications, Neurocomputing, IEEE IoT
Journal, Journal of Educational Computing Research; and in CORE A/A* Peer-review
International Conferences proceedings (AAAI, IJCAI, ICDM, ICML, ICWS, ICDE,
PAKDD, CIKM, WWW, IEEE IC Signal Processing, IC-EDM). Lee also served as invited
keynote speakers for IEEE and ACM Flagship conferences and General Chair,
Co-chair Technical Programs and Co-chair & Keynote speaker for IC on Education
Network & Information Technology, ICNEIT2024, Dalian, Program Co-chair APIT2025
HK, Technical Program Chair for IC AIDF2025 12-15 June 25 in Chengdu. Since
2020, he is serving Associate Editor for Journal of Intelligent Manufacturing
(Springer, SCI Mago Journal Rank Best Quartile Q1); Editorial Board, Science
Progress (a Q1 Journal) in “Computer and Information Science”.
https://scholar.google.com/citations?user=nP5UPKsAAAAJ
Associate Professor Mustafa Misir, Duke Kunshan University, China
Mustafa Mısır is an Associate Professor of Data and Computational Science at Duke Kunshan University in China. He completed his Ph.D. in Computer Science at KU Leuven (Belgium) in 2012. After graduation, he worked as a postdoctoral researcher at INRIA Saclay - Universite Paris Sud XI (France), Singapore Management University (SMU) and University of Freiburg (Germany) respectively. He was also a visiting researcher at University of Zurich (Switzerland) and Universitat Politecnica de Catalunya (UPC) / BarcelonaTech (Spain). Afterwards, he moved to Nanjing University of Aeronautics and Astronautics (China) as a faculty member at the College of Computer Science and Technology. Prior to joining Duke Kunshan University, he was a faculty member in Computer Engineering at Istinye University (Turkey). His main research interests include Automated Algorithm Design (Machine Learning + Algorithm Design) / Automated Algorithm Design, Data Science, and Operations Research. He is the recipient of several prestigious academic awards and has published over 60 papers in various international conferences/journals.
Professor Peng Guo, Shihezi University, China
Professor Peng Guo (Ph.D.) is a professor in the Department of
Geography, College of Science at Shihezi University, China. He serves as a
council member of the Xinjiang Chapter of the National Aviation Plant Protection
Technology Innovation Alliance, a member of the China Cotton Industry Alliance,
and a member of the China Association for the Promotion of Agricultural
International Cooperation. His primary research focuses on agricultural remote
sensing, encompassing crop classification, yield estimation, and innovative
applications of remote sensing technology. Professor Guo has participated in
multiple scientific research projects related to digital agriculture and smart
agriculture, significantly advancing the practical implementation of remote
sensing technology in agricultural practices across northwestern China. He has
published over 30 papers in journals such asTransactions of the Chinese Society
of Agricultural Engineering,Remote Sensing Technology and
Application,Agriculture, andArid Zone Research. Utilizing Sentinel-2A remote
sensing imagery and UAV multispectral imagery, he has analyzed phenological
information of typical crops in northwestern China, identified optimal
timeframes for feature extraction in remote sensing time-series data, and
proposed an object-oriented multi-feature learning method for fine crop
classification. This approach leverages latent color structural information
within imagery to achieve high-precision crop classification.
https://lxy.shzu.edu.cn/_s55/2024/1009/c13389a210545/page.psp