Keynote Speakers

Prof. Mérouane Debbah

Prof. Mérouane Debbah

Professor, Khalifa University of Science and Technology, Abu Dhabi
Founding Director, KU 6G Research Center

Talk Title

Large Perceptive Models for the future of Intelligent Connectivity

Abstract

The next evolution of the Internet of Things (IoT) is not about connecting more devices — it's about making them understand us. In this talk, I introduce the emerging concept of Large Perceptive Models (LPMs): AI-driven systems that integrate large language models (LLMs) into the very fabric of IoT. LPMs act as both interpreters of multimodal IoT data and optimizers of user intent, translating raw sensor signals into meaningful narratives and converting natural language instructions into real-time control and optimization strategies This shift redefines the role of AI in IoT, from passive data processors to proactive collaborators. The result: a more human-centric, resilient, and explainable IoT, where users no longer configure devices, but simply converse with them.

Biography

Mérouane Debbah is Professor at Khalifa University of Science and Technology in Abu Dhabi and founding Director of the KU 6G Research Center. He is a frequent keynote speaker at international events in the field of telecommunication and AI. His research has been lying at the interface of fundamental mathematics, algorithms, statistics, information and communication sciences with a special focus on random matrix theory and learning algorithms. In the Communication field, he has been at the heart of the development of small cells (4G), Massive MIMO (5G) and Large Intelligent Surfaces (6G) technologies. In the AI field, he is known for his work on Large Language Models, distributed AI systems for networks and semantic communications. He received multiple prestigious distinctions, prizes and best paper awards (more than 50 IEEE best paper awards) for his contributions to both fields and according to research.com is ranked as the best scientist in France in the field of Electronics and Electrical Engineering. He is an IEEE Fellow, a WWRF Fellow, a Eurasip Fellow, an AAIA Fellow, an Institut Louis Bachelier Fellow, an AIIA Fellow and a Membre émérite SEE. He is actually chair of the IEEE Large Generative AI Models in Telecom (GenAINet) Emerging Technology Initiative and a member of the Marconi Prize Selection Advisory Committee.

Prof. Dacheng Tao

Prof. Dacheng Tao

Distinguished University Professor, Nanyang Technological University, Singapore

Biography

Dr Dacheng Tao is currently a Distinguished University Professor in the College of Computing & Data Science at Nanyang Technological University. He mainly applies statistics and mathematics to artificial intelligence and data science, and his research is detailed in one monograph and over 200 publications in prestigious journals and proceedings at leading conferences, with best paper awards, best student paper awards, and test-of-time awards. His publications have been cited over 112K times and he has an h-index 160+ in Google Scholar. He received the 2015 and 2020 Australian Eureka Prize, the 2018 IEEE ICDM Research Contributions Award, and the 2021 IEEE Computer Society McCluskey Technical Achievement Award. He is a Fellow of the Australian Academy of Science, AAAS, ACM and IEEE.

Prof. Baoquan Chen

Prof. Baoquan Chen

Distinguished Boya Professor, Peking University, China
Associate Dean of the School of Artificial Intelligence, Peking University

Biography

Baoquan Chen is a Professor of Peking University, where he is the Associate Dean of the School of Artificial Intelligence. His research interests generally lie in computer graphics, computer vision, and visualization. He has received Best Paper Award in several prestigious conferences, such as ACM SIGGRAPH Asia (2022), ACM SIGGRAPH (2022 Honorary Mention), and IEEE Visualization (2005). He received Ten-year Test-of-Time Award in ACM SIGGRAPH 2025. Chen has served as chairs of prestigious conferences such as SIGGRAPH Asia 2014, IEEE Visualization 2005, and 3D Vision 2017. He currently serves as the ACM SIGGRAPH Executive Committee Director. Chen is an IEEE Fellow, and was inducted to IEEE Visualization Academy and ACM SIGGRAPH Academy in 2021 and 2024, respectively.

Prof. Vesa Välimäki

Prof. Vesa Välimäki

Professor and Vice Dean, Aalto University, Finland

Talk Title

Audio Signal Processing with the Giant FFT

Abstract

Today, the Fast Fourier Transform (FFT) enables rapid processing of surprisingly long signals, a feat made possible by advancements in memory capacity and computing speed. This presentation explores how a large, one-shot FFT, coupled with spectral processing and inverse FFT, can transform audio and speech signals in various, and even unexpected, ways. One particularly valuable technique is FFT-based sample-rate conversion, which achieves an arbitrary, constant rate change using a single FFT and inverse FFT. Along with its blinding speed, this approach offers the advantages of simplified processing and the elimination of spectral imaging, a common issue with time-domain filtering techniques. Other current applications extend to creative effects for music, gaming, and film sound production, including audio time-scale modification, babble noise synthesis, and transforming music recordings into texture-like sound effects while maintaining a realistic timbre. Many of these techniques are straightforward to implement and serve as excellent examples in signal processing courses, enhancing the understanding of properties of the complex spectrum.

Biography

Vesa Välimäki is a Professor of audio signal processing at Aalto University, Espoo, Finland. He is also the Vice Dean for research and the Head of the doctoral program at the Aalto University School of Electrical Engineering. His research group belongs to the Aalto Acoustics Lab, a multidisciplinary center of high competence with excellent facilities for sound-related research. Prof. Välimäki is a Fellow of the IEEE (Institute of Electrical and Electronics Engineers), a Fellow of the AES (Audio Engineering Society), and a Fellow of the AAIA (Asia-Pacific Artificial Intelligence Association). He was a Board Member of Heureka, the Finnish Science Centre in 2017-2025. In 2008, he was the General Chair of the 11th International Conference on Digital Audio Effects DAFx-08, and in 2017, he was the General Chair of the 14th Sound and Music Computing Conference SMC-17. In 2015-2020, he was a Senior Area Editor of the IEEE/ACM Transactions on Audio, Speech and Language Processing. From 2020 to 2025, Prof. Valimäki was the Editor-in-Chief of the Journal of the Audio Engineering Society, and currently, he is the Deputy Editor-in-Chief.

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