Prof. Kenichi Okada 

Institute of Science Tokyo, Tokyo, Japan (formerly Tokyo Institute of Technology) 

Abstract

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Biography

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Assoc. Prof. Astria Nur Irfansyah

Institut Teknologi Sepuluh Nopember, Indonesia

Abstract

Modern microelectronics depend on analog and mixed-signal circuits that bridge the physical world with the digital domain of computation. However, as transistor size continues to scale down for greater computing power through processors with more cores and functionality, memory with much higher density, and systems with much more complexity, the same advantage of this CMOS scaling does not directly apply to analog and mixed-signal circuits. This is due to reduced signal quality, worse device mismatch, and increased device leakage current with smaller CMOS technology nodes. Digitally-assisted analog and mixed-signal circuits have emerged to exploit the advantages of digital circuits in modern CMOS processes for analog circuit functionality. A connected paradigm is the neuromorphic circuit technique which draws on biological neural network structure and efficiency for use in intelligent systems. Biological systems are inherently analog in nature, therefore analog electronic circuits have been widely considered for neuromorphic circuit implementations. The energy efficiency potential of neuromorphic circuits is much needed given the very high power consumption of modern AI systems. Relevant research along these directions, carried out at ITS Surabaya, Indonesia, is discussed as part of a broader collective effort to build semiconductor and IC design talent and capacity in the country.

Biography

Astria Nur Irfansyah is an associate professor at the Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS) Surabaya. At ITS, he also serves as Deputy Director for International Partnership at ITS Global Engagement since 2020. Dr. Irfansyah previously served as Vice Secretary of the IEEE Indonesia Section in 2019, and currently Vice Chair of ICDEC (Indonesia Chip Design Collaborative Center). He received his Ph.D in Electrical Engineering from the University of New South Wales, Australia, in 2016, focusing on mixed-signal circuit design. He is currently active in promoting integrated circuit design to students and supervising student thesis on microelectronics and embedded systems.

Assoc. Prof. Anis Salwa Mohd Khairuddin

Universiti Malaya  

Speech Title: From Intelligence to Impact: Shaping the Future of Emerging Technologies

Abstract

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Biography

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Dr. Ngurah Indra ER

Universitas Udayana

Abstract

“From Sensing to Safety: Integrating V2X Communication, Hybrid AI, and Autonomous IoT Networks for Resilient and Sustainable Urban Mobility”

Urban mobility networks across Southeast Asia are expanding at an unprecedented pace, where the coexistence of motorcycles, passenger vehicles, trucks, and pedestrians within shared road spaces creates a fundamentally heterogeneous and high-variance traffic paradigm — a condition commonly referred to as Mixed Traffic. Simultaneously, the maturation of Cellular Vehicle-to-Everything (C-V2X) communication standards, deep learning architectures, and autonomous Internet of Things (IoT) sensing networks is opening a transformative window for next-generation Intelligent Transportation Systems (ITS). However, the fact that most existing ITS frameworks have been designed and validated exclusively under homogeneous traffic conditions crucially limits their applicability in the mixed traffic environments that characterize the majority of roads across the developing world — a gap that demands field-grounded, context-specific research.

In this keynote, we present an integrated three-pillar framework developed to address this gap directly. The first pillar examines C-V2X Sidelink communication architecture, focusing on resource allocation performance and cooperative safety messaging under mixed traffic density. The second proposes a Hybrid Kalman Filter–Long Short-Term Memory (KF-LSTM) model for real-time collision detection at signalized intersections under tropical weather conditions, alongside a YOLOv8-based environmental perception system for autonomous electric vehicles. The third demonstrates how autonomous IoT sensing networks, combined with Vehicle-to-Infrastructure (V2I) data harvesting, enable city-scale environmental monitoring — from drive-by air quality mapping to autonomous flood detection — without prohibitive infrastructure investment.

These three pillars converge in the construction of an Indonesian Mixed Traffic Digital Twin, calibrated from live field survey data, which we argue is crucially advantageous as both a research validation environment and a policy decision-support tool for Vulnerable Road User (VRU) protection. Contrary to complex, homogeneous-traffic-optimized solutions that impose significant standardization and deployment burdens, we demonstrate that a simple and efficient integrated framework — built from the ground up for Southeast Asian road conditions — is sufficient to achieve meaningful gains in urban safety, sustainability, and resilience.

Biography

Ngurah Indra ER is an Assistant Professor at the Electrical & Computer Engineering Department, Udayana University, Bali, Indonesia, in the Telecommunications and Multimedia Networks Group. He completed his PhD at the Institute Mines-Telecom (IMT) Atlantique (formerly Telecom Bretagne), Rennes Campus, France, in the Network Systems, Cyber Security and Digital Law Department, while also affiliated to the IRISA Laboratory. He completed his M.Sc in Communications Engineering from the University of Birmingham, the UK, in 1999 and his B.Eng in Telecommunication Engineering from Sepuluh November Institute of Technology (ITS) Surabaya, Indonesia, a year earlier. His current research interests include Internet of Vehicles (IoV), Vehicular Networks, Internet of Things (IoT), and Smart City Data Collection.