Professor Jack (Xuejun) Li is a Professor of Electrical and Electronic Engineering at Auckland University of Technology, with expertise in wireless systems, digital signal processing, wireless sensor networks, system optimisation, and machine learning. At the CNBM–AUT Hub, he brings this expertise to communications, sensing, and optimisation challenges in smart energy and connected transport. His work supports the reliable data exchange and real-time monitoring required for V2G and electric connected and automated vehicle (ECAV) systems.
Dr. Shu Su is a Lecturer in Mathematical Sciences at Auckland University of Technology, specializing in applied mathematics and data analytics. At the CNBM–AUT Hub, she develops mathematical models, advanced optimization methods, and blockchain-based tools to manage uncertainty in energy markets and ECAV operations. Her research underpins dynamic pricing schemes, coordinated charging strategies, and transparent energy trading platforms, ensuring individual decision-making aligns with broader system objectives.
Dr. Sadeeshvara Silva is a Lecturer in Power Electronics with deep experience in EV charging, power converters, and DC microgrids. At the CNBM–AUT Hub he leads work on efficient EV chargers, V2G-capable power electronics, and hardware-aware charging methods to keep systems safe, reliable, and grid-friendly. He blends hands-on design skills with system-level analysis to create robust, scalable solutions for electric transport and distributed energy, and he works with industry and grid operators to turn research into real products.
Dr. Zoey Zhou is a Lecturer at AUT who focuses on power system control, integrating renewables, and applying AI for smart grids. At the CNBM–AUT Hub she develops reinforcement-learning control methods that coordinate renewable generation, energy storage, and electric connected/automated vehicle (ECAV) charging to support stable, low-emission, V2G-capable power systems. She also works on practical implementation and testing to ensure these solutions are robust, scalable, and compatible with existing grid operations.
Dr. Ramon Zamora is a Senior Lecturer at Auckland University of Technology specializing in microgrids, energy management, and renewable-plus-storage grid integration. At the CNBM–AUT Hub he leads research on ECAV-enabled microgrids and vehicle-to-grid systems, developing architectures that use electric and autonomous vehicles as flexible energy resources to boost resilience, efficiency, and decarbonization for community and industrial networks.
Dr Duaa Al-Hamid is a Lecturer at Auckland University of Technology whose research spans wireless communications, wireless sensing, IoT, software-defined networking, and network digital twins. She applies these technologies to vehicular networks, UAVs, healthcare, environmental monitoring, and disaster management. At the CNBM-AUT Hub, her expertise supports resilient sensing and digital-twin frameworks for real-time environmental and infrastructure monitoring, helping translate connected data into practical decision support for sustainable communities and intelligent transport.
Dr Minglong Zhang is an Assistant Research Professor in Electrical and Computer Engineering at Mississippi State University. His research covers 5G and 6G communications, AI-enabled wireless networking, O-RAN, V2X communications, and communication security. At the CNBM-AUT Hub, his expertise supports intelligent and secure connectivity for connected transport, distributed energy systems, and future mobility, including AI-native network control and resilient vehicle-to-everything communications.
Associate Professor Ivan W. H. Ho is an Associate Professor in Electrical and Electronic Engineering at The Hong Kong Polytechnic University, a Fellow of the IET, and a Chartered Engineer. His research focuses on wireless communications and networking, vehicular networks, intelligent transportation systems, IoT, connected autonomous vehicles, and wireless sensing. At the CNBM–AUT Hub, his expertise supports V2X connectivity, sensing, and digital-twin-enabled transport systems for autonomous EV fleets and smart mobility.
Professor Minho Jo is a Professor in the Department of Computer Science and Software Engineering at Korea University and Director of the IoT Data Science Team within the Brain Korea 21 programme. His current interests include IoT, generative AI and large language models, quantum computing and security, autonomous vehicles, edge computing, and network optimisation. At the CNBM–AUT Hub, his expertise supports AI-driven mobility, secure connected systems, and optimisation for intelligent energy and transport networks.
Dr. William Liu is an Honorary Researcher with expertise in resilient, secure, and sustainable computing, communications, and networking. At the CNBM–AUT Hub, he contributes external research expertise in cybersecurity, IoT, edge computing, and intelligent connected systems, supporting the development of secure digital infrastructure for intelligent green technologies and future mobility applications.
Associate Professor Saeed Rehman is an Associate Professor in Cybersecurity and Networking and Research Section Head for Data and Information Science at Flinders University. His research covers wireless communication, physical-layer and network security, satellite communication, and secure IoT systems. At the CNBM–AUT Hub, his expertise supports resilient communications and cybersecurity for 6G-enabled smart energy networks, connected infrastructure, and trusted V2G data exchange.
Professor Winston K. G. Seah is a Professor of Network Engineering at Te Herenga Waka – Victoria University of Wellington. His research focuses on networking protocols for constrained and highly mobile systems, mobile edge computing, industrial IoT, quantum networks, and AI-enabled network anomaly detection. At the CNBM–AUT Hub, his expertise supports resilient, low-latency communications for 5G/6G-connected energy infrastructure, autonomous mobility, and distributed sensing.
Jishen Sun is a PhD researcher at Auckland University of Technology. His research focuses on graph neural networks, higher-order graph representation learning, recommender systems, and reliable AI. Drawing on previous industry experience in power generation and large-scale industrial control, he connects advanced machine learning with energy infrastructure and operational systems. At the CNBM-AUT Hub, his expertise supports intelligent monitoring, robust decision support, and practical AI applications for complex industrial and energy environments.
Keane (Zijun) Li is a PhD researcher at Auckland University of Technology specialising in computer vision, machine learning, and facial behaviour analysis. His research examines personalised micro-expression dynamics and motion signatures for distinguishing authentic human videos from AI-generated content. Before his PhD, he developed real-time speech translation and intelligent video-processing systems as an AI research engineer. At the CNBM-AUT Hub, he supports AI-driven visual monitoring, human-system interaction, and real-time intelligent systems.
Shwan (Lingxuan) Hou is a PhD researcher in the School of Engineering, Computer and Mathematical Sciences at Auckland University of Technology. His research spans multimodal large language models, computer vision, medical AI, and the integration of visual, textual, and sensor data. At the CNBM-AUT Hub, he contributes multimodal and generative AI expertise for intelligent energy and transport systems, supporting data-driven monitoring, knowledge extraction, explainable decision support, and reliable human-centred applications.
Xuanpeng Meng is a PhD candidate in Geotechnical Engineering at Auckland University of Technology. His research focuses on geopolymer-based stabilisation of expansive soils and the development of sustainable, low-carbon geotechnical solutions. He previously completed a master's degree at the University of New South Wales, where he researched geothermal energy. At the CNBM-AUT Hub, his expertise links low-carbon materials, ground engineering, and renewable energy to support resilient infrastructure and practical pathways for sustainable development.
