Speaker

KEYNOTE SPEAKERS

Biography

Assoc. Prof. Dr. Abdul Hadi Abd Rahman is a recognised expert in Artificial Intelligence (AI) and Robotics in Malaysia, with contributions spanning international, national, industry, and academic domains. Internationally, he was invited to present the Report on the Development of the Artificial Intelligence Industry in Malaysia at the First Forum on China-ASEAN AI Cooperation 2023, reaffirming his role as a regional thought leader. He is an Adjunct Professor at Ontario Tech University, Canada (2021–2027) and collaborates with Tokai University, Japan on autonomous robotics. In 2023, he was part of the Malaysia AI Delegation to the United Kingdom, under the British High Commission, to assess national progress under the Malaysia AI Roadmap 2021–2025. Nationally, Dr. Abdul Hadi leads the WaRiSAN MELAYU Project, a RM8 million initiative under Budget 2025 to build Malaysia’s sovereign Bahasa Melayu Large Language Model (LLM) and supporting infrastructure. The project comprises over 25 sub-projects, covering corpus development, domain-specific datasets, and applied use cases, positioning UKM as the national hub for continuous LLM-BM development. He is an active member of national platforms including the ASM Task Force on Robotics, where he contributed to the National Robotics Roadmap 2021–2030, the National Blockchain and AI Committee (NBAIC), and the Robotic Talent Development Academy (RoTDA). He is also part of the Young Scientist Network-Academy of Sciences Malaysia (YSN-ASM). In industry, Dr. Abdul Hadi serves as AI consultant to FGV R&D, advancing smart agriculture, and holds a strategic MoA with Move Robotics to commercialize service robots. Since 2012, he has contributed to the UTM-Proton Active Safety (UPAS) Lab and the Vehicle System Engineering Lab (MJIIT, UTM), where he developed AI-based perception modules for autonomous vehicles using LiDAR, radar, and vision fusion. Academically, he leads the ARVIS Lab at UKM and is the inventor of AiRIS, an AI-powered autonomous service robot, and OQSense, a multi-depth vision system. As Deputy Dean (Research and Innovation) at FTSM, UKM, he drives AI research, talent development, and innovation translation across Malaysia and ASEAN.

Title: WaRiSAN MELAYU: Building a Collaborative AI Bahasa Melayu Ecosystem

WaRiSAN MELAYU (Wahana Rintis Semantik Ayat Nasional) is Malaysia’s flagship initiative to build a comprehensive AI Bahasa Melayu ecosystem grounded in data sharing, linguistic resources, and collaborative innovation. As language becomes a strategic digital asset, WaRiSAN MELAYU brings together academia, government, industry, and cultural institutions to develop high-quality corpora, shared infrastructure, and governance frameworks that strengthen language sovereignty. This keynote will highlight how collaborative data ecosystems accelerate the development of Malay language models and enable cross-sector innovation in education, governance, cultural preservation, and digital services. It will address challenges in standardization, interoperability, and policy alignment while outlining Malaysia’s roadmap towards a sustainable, trusted, and inclusive AI Bahasa Melayu ecosystem. Through WaRiSAN MELAYU, Bahasa Melayu is positioned as a digitally empowered language that drives national competitiveness and regional leadership in the AI era.

Biography

Nana Rachmana Syambas. He was graduated from his bachelor degree at Electrical Engineering Department, ITB in 1983. He got his Master by Research degree from Royal Melbourne Institute of Technology, Australia in 1990 and doctoral degree from School of Electrical Engineering and Informatics, ITB in 2011. He has been a lecturer at School of Electrical Engineering and Informatics, ITB since 1984. His research interest includes: Telecommunication Networks, Telematic Services, Content Centric Network (CCN), Software Define Network (SDN), Protocol engineering and Tele-traffic engineering. He has authored or coauthored over 150 published articles.

Title: Future Network & Trend

Named Data Networking (NDN) is a forward-looking architecture for the Internet. Rather than relying on device addresses, NDN routes and caches data by name, enabling users to retrieve content from the closest or most efficient source. This paradigm reduces latency, improves throughput, and cuts packet loss by leveraging in-network caching and name-based forwarding. Data security comes inherently via cryptographic signatures on content, ensuring integrity regardless of path. Using simulations based on the Palapa Ring network, we observe that NDN consistently outperforms traditional IP-based models in delay, reliability, and resource utilization. Given its alignment with the requirements of 5G and 6G—especially ultra-low latency and scalability—NDN offers a promising path for future electrical engineering and information systems research.