Keynote Speakers

 

Prof. Xiaoli Li

IEEE Fellow, AAIA Fellow

Institute for Infocomm Research (I2R), A*STAR, Singapore

Dr. Li Xiaoli is the Department Head and Principal Scientist of the Machine Intellection (MI) department at the Institute for Infocomm Research (I2R), A*STAR, Singapore. He also holds adjunct full professor position at School of Computer Science and Engineering, Nanyang Technological University. He has been a member of ITSC (Information Technology Standards Committee) from ESG Singapore since 2020 and has served as joint lab directors with a few major industry partners.
His research interests include AI, data mining, machine learning, and bioinformatics. He has been serving as the Chair of many leading AI/data mining/machine learning related conferences & workshops (including KDD, ICDM, SDM, PKDD/ECML, ACML, PAKDD, WWW, IJCAI, AAAI, ACL, and CIKM). He currently serves as editor-in-chief of Annual Review of Artificial Intelligence, and associate editor of Machine Learning with Applications (Elsevier).
He led his team to win various top AI and data analytics international benchmark competitions and works closely with government agencies and industry partners across different verticals, e.g., bank and insurance, healthcare, aerospace, telecom, audit firm, transportation etc, to create social and economic impact.
Dr Li has published more than 270 peer-reviewed papers in top AI, Data Mining, Machine Learning and Bioinformatics conferences and journals with more than 13,000 citations (more than 2,000 annual citations in recent years; H-index 53) and won eight best paper awards.

 

Prof. Lei Meng

Shandong University, China

Lei Meng is Professor with the School of Software, Shandong University. He received the B.Eng.’s degree in 2010 from Shandong University, China, and obtained the PhD’s degree in 2015 from Nanyang Technological University. From 2015 to 2020, he worked successively at Nanyang Technological University and National University of Singapore as Research Fellow and Senior Research Fellow. His research interests include multimedia computing, deep learning, and its applications in healthcare and digital twin for social governance. He has published a book with Springer and fifty conference and journal papers at top and renowned venues, such as MM, AAAI, TKDE and TNNLS. He serves as the Associate Editor of Applied Soft Computing, and the (senior) program committee member of top-tier conferences, such as MM, AAAI, IJCAI, and SIGIR.

 

Dr. Chiang Liang Kok

Newcastle Australia Institute of Higher Education, Singapore

In 2010, Chiang Liang graduated with First Class Honours in Bachelor of Electrical & Electronic Engineering from Nanyang Technological University (NTU). His exceptional performance earned him the highly coveted Singapore EDB Integrated Circuit Design PhD Scholarship to pursue his PhD at NTU. In 2014, Chiang Liang was awarded his PhD Degree in Electrical & Electronic Engineering in which he delved deeply into power management units, AI, sensors and energy harvesting systems. He also served as an NTU undergraduate tutor and teaching assistant for NTU-TUM Master courses. In 2014, Chiang Liang joined the Ministry of Défense, Mindef DSO National Lab as a senior member of technical staff. Here, he spearheaded several state-of-the-art projects, earning acclaim with the prestigious Design Innovation Award (Individual) at the Electronics division level. Chiang Liang was invited to be the Adjunct Professor (Faculty Member) at Singapore University of Social Sciences (SUSS), where he teaches electronics courses with passion. In 2021, Chiang Liang was bestowed with the prestigious Gold Medal Award for Teaching Excellence (University level) at SUSS.

In 2020, Chiang Liang joins the Newcastle Australia Institute of Higher Education as a lecturer and program coordinator for the Bachelor of Electrical and Electronic Engineering (BEEE). His influence extends far beyond the classroom, as evidenced by his exclusive invitation to the Channel News Asia (CNA) Money Mind programme in May 2021, where he shared his expertise on blockchain technology and sustainable energy solutions. In Nov 2021, he receives the Best Paper award at the 3rd ICESA. Chiang Liang also serves as chairman for the STEM Industrial Advisory Board Committee and a committee member for the PEI Exam Board Council. His expertise is sought after on the international stage, with invitations as keynote/plenary speaker and local organising chair for GMASC 2023, MSM 2024, CCCN 2024, ASET 2024, ACEE 2024 and PCDS 2024. Furthermore, he is in the technical program committee for ICET 2024, ITET 2024, ICICDT 2024, TENCON 2024 and RASSE 2024. He is also the chairperson and moderator for WES 2023, session chair for AGBRP 2024, TENCON 2024 and ISCAS 2024. He also serves as the publicity chair for MCSoC 2024 and RASSE 2024. Recently, he also serves as the special session chair and co-trainer for workshop titled “Modern Technologies for Sustainability and Asset Management” in McSOC 2024. In July 2024, he is appointed to the Topical Advisory Panel for MDPI Electronics, Circuit and Signal Processing Section. He also serves as guest editor and reviewer for esteemed Q1/Q2 ranking journals such as MDPI Sensors/Electronics/Applied Sciences, IEEE Access, Circuits, Systems, and Signal Processing and IEEE Transactions on Industrial Electronics. Till date, he has been awarded research funding of more than S$240K in both PI and co-PI capacity. With over 50 publications in Q1/Q2 ranking journals, top conferences, and several book chapters, Chiang Liang's scholarly impact continues to reverberate across the global engineering landscape.

 

A. Lakshminarayanan (Lux)

Institute for Infocomm Research, A*STAR, Singapore

A. Lakshminarayanan (Lux) is a principal research engineer at I2R, working at the intersection of AI, Networking and Cybersecurity. In his 25+ year career as a practitioner and entrepreneur, he has delivered multiple projects scanning a wide swath of industry verticals. He is currently a part-time doctoral research student at Singapore Management University researching AI Engineering in the context of emerging AI regulations.

Title: Emerging AI Regulations – Implications for AI/ML in Networks

Abstract: AGI is just round the corner. AI/ML is getting adopted into every aspect of digital infrastructure. At the same time awareness about AI safety has also increased. AI/ML learn from data - data that might not be representative or sufficient, data that might be noisy and biased. Powerful black-box AI models are prone to hallucination and over-confidence. AI in networking is particularly hard because networks are highly dynamic and bespoke.

Globally, we have seen increasing regulatory activity, both horizontal e.g. EU’s AI act and sector specific e.g. GSMA’s responsible AI maturity roadmap. In this talk, I will give a bird’s eye view of AI regulatory activities from around the world and how it is will impact AI in networking. I will also cover 3GPP’s 5G-Advanced specifications on incorporating AI/ML and how this can be accomplished in the context of AI regulations.