Invited Speakers

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Invited Speaker I

Assoc. Prof. Chenglong Shao，Kyushu Institute of Technology, Japan

Dr. Chenglong Shao is an Associate Professor in the Department of Electronics and Information Communication Engineering at Kyushu Institute of Technology, Japan, a position he has held since 2026. He received his B.S. in Information and Communications Engineering from Xi'an Jiaotong University, China, in 2010, and his Ph.D. in Computer Science and Engineering from Korea University, South Korea, in 2019. He previously served as a Research Professor at Korea University in 2019, a JSPS International Research Fellow at Kyushu University from 2021 to 2023, and a Visiting Scholar at the University of California, Riverside, in 2024. His research interests span wireless networking, IoT-enabled mobile computing, wireless security, and networked embedded systems. He has authored over 30 first-author papers in leading international journals and conferences, including IEEE Transactions on Mobile Computing and IEEE/ACM Transactions on Networking. His work has been recognized with more than 10 international awards, such as the CANDAR 2022 Best Paper Award, the 25th Samsung Humantech Paper Award – Bronze Prize in 2019, and the 1st Place Transactions Award of 2018 Annual IEEE Consumer Electronics Society Chester W. Sall Memorial Awards in 2018. He is an active member of the research community, contributing as a TPC member at over 20 international conferences and as a reviewer for more than 40 academic journals.

Speech Title: Pushing the Limits of LoRa Communications in Ultra-Low SNR Environments

Speech Abstract: Long-range wide area network (LoRaWAN) has emerged as a leading wireless communication technology for the Internet of Things (IoT) because of its long-range and low-power capabilities. However, dead-zone LoRa communication remains a major challenge, where end devices experience ultra-low signal-to-noise ratios (SNRs) at gateways due to environmental factors such as signal blockage, reflection, and severe attenuation in urban and indoor environments. Existing solutions primarily rely on additional hardware, deep learning-based techniques, or repeated signal retransmissions. However, these approaches suffer from increased deployment costs, scalability issues, and energy inefficiencies. In this paper, we propose DeLoRa, a novel physical-layer solution that enables reliable LoRa communication in dead zones without requiring extra hardware, deep learning models, or excessive signal retransmissions. DeLoRa introduces chirp redundancy, which enhances demodulation robustness by improving the signal’s distinguishability from the noise floor. We validate DeLoRa through extensive real-world experiments in different environments. Our results show that DeLoRa significantly enhances LoRaWAN coverage by at least 48\%, making it a practical solution for large-scale IoT deployments.

 

Invited Speaker II

Associate Professor Dr. Mardhani Riasetiawan, Universitas Gadjah Mada, Indonesia

Dr. Mardhani Riasetiawan is a distinguished academic and digital transformation leader in Indonesia. He currently serves as a senior lecturer and digital innovation strategist at Universitas Gadjah Mada (UGM), where he plays a pivotal role in advancing the integration of technology across higher education, research, and public service.
With a doctoral degree in Information Technology, Dr. Mardhani Riasetiawan has built a strong portfolio in areas such as data architecture, artificial intelligence in education, digital governance, and smart campus development. His work is widely recognized for bridging academic research with real-world applications, particularly in supporting the digital transformation agendas of universities and government institutions.
At UGM, Dr. Mardhani Riasetiawan is also actively involved in managing digital initiatives and academic platforms, including Massive Open Online Courses (MOOCs), AI-enhanced learning systems, and campus-wide digital literacy programs. He regularly leads workshops, research collaborations, and national forums that promote the ethical and impactful use of emerging technologies in education.
Beyond academia, Dr. Mardhani Riasetiawan contributes as a consultant and advisor for various public and private organizations, especially in the domains of digital strategy, educational innovation, and smart city development. His commitment to digital empowerment and inclusive innovation continues to inspire institutional growth and societal transformation in the digital era.
Doctor in Computer Science from Universitas Gadjah Mada, Master in Information Technology and Bachelor in Accounting. Professionally as Big Data Scientist and Data Analytic Experts, Information System Auditor and Advisor, and Cloud Computing Expert. Currently Lead The Computer System and N Network Research Lab, DCSE FMIPA UGM and lecturer in computer science.
20+ years experienced in cloud and big data management. Currently works on high performance and intelligent data management for support energy companies, and deals with several standards such as PPDM, OAIS, etc. Professionally as cloud and big data scientist and expert for National energy company in Indonesia, and several international energy companies worldwide.