『Our Digital Life Podcast: A series by IEEE-SPS』のカバーアート

Our Digital Life Podcast: A series by IEEE-SPS

Our Digital Life Podcast: A series by IEEE-SPS

著者: IEEE-SPS
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As the world's largest professional organization, IEEE plays a significant role in enhancing the quality of our lives. Specifically, the IEEE signal processing society or SPS focuses on research and development of audio and speech processing, biomedical analysis, and wireless communication technologies, all of which are key enablers to today's modern society. In this series, we explore more about the works of signal processing and engage with various global speakers.

© 2026 Our Digital Life Podcast: A series by IEEE-SPS
物理学 科学
エピソード
  • Signal‑Processing Frontiers: Humanistic AI Solutions for Digital Forensics, Health, Well‑Being, and Fighting Disinformation
    2026/07/02

    In this episode of the IEEE Signal Processing Society podcast, Dr. Rogério Augusto Bordini, a Post-doctoral Researcher and Science Journalist at the Artificial Intelligence Lab., Recod.ai, University of Campinas (Unicamp), interviews Dr. Anderson Rocha, Full Professor at the University of Campinas (Unicamp) specializing in Artificial Intelligence, Digital Forensics, and Reasoning for Complex Data. Their conversation explores how modern signal-processing techniques have been explored in various social sectors.

    Dr. Anderson Rocha

    Professor Anderson Rocha, Former Director of Unicamp's Institute of Computing and two-time Chair of the IEEE Information Forensics and Security Technical Committee, was named an IEEE Fellow in 2023, an IEEE SPS Distinguished Lecturer in 2025, and an IEEE Biometrics Council Distinguished Lecturer also in 2025. Closing a remarkable year, he was awarded the prestigious Zeferino Vaz Prize—Unicamp's highest recognition. Recognized as one of the world's top scientists by Stanford, PLOS ONE, and Research.com, he holds fellowships from Microsoft and Google and co-founded the Recod.ai AI Lab at Unicamp over 16 years ago.

    In this episode, Dr. Rocha discusses applications of signal processing spanning digital forensics, wearable sensors, deepfake detection, and misinformation mitigation, while highlighting core algorithms, real-world healthcare applications, and emerging AI-driven forensic tools, and also provides insights into his research group's key differentiator—a humanistic, expert-in-the-loop approach to solution design.

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    51 分
  • Stopping Counterfeiting with QR Codes and AI
    2026/03/13

    In this episode of the IEEE Signal Processing Society Podcast, Hemang Chawla, Solutions Lead at Scantrust, speaks with Justin Picard, Co-founder and CTO of Scantrust. Their conversation explores how modern signal processing, printing physics, and machine learning are being combined to combat the global problem of product counterfeiting through secure QR codes and copy detection technology.

    Dr. Justin Picard

    Dr. Justin Picard is the Co-founder and Chief Technology Officer of Scantrust, a company specializing in product authentication and traceability solutions. Originally from Canada and now based in Switzerland, Dr. Picard completed his Ph.D. in artificial intelligence before moving into digital watermarking and image security. After working in research and development roles across North America and Europe, Dr. Picard co-founded Scantrust to develop smartphone-based authentication systems that empower consumers and brands to verify product authenticity in real time.

    In this episode, Dr. Picard discusses the trillion-dollar global impact of counterfeiting, which now affects not only luxury goods but also everyday products such as food, industrial components, health supplements, and consumer goods—an issue intensified by e-commerce and global supply chains. He explains that traditional anti-counterfeiting methods, including holograms, UV inks, and forensic testing, struggle to scale in today’s digital marketplace because they rely on specialized equipment or human inspection.

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    34 分
  • Functional Brain Imaging: Signals, Imaging, and Graphs
    2026/03/11

    Functional Brain Imaging: Signals, Imaging, and Graphs

    In this episode of the IEEE Signal Processing Society Podcast, Professor Borbála Hunyadi from the Mental Health and Neuroscience Research Institute, Maastricht University, The Netherlands interviews Dr. Dimitri Van De Ville, Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL) and the University of Geneva, Switzerland. Their conversation explores how modern neuroimaging modalities, combined with advanced signal processing and computational methods, are transforming our understanding of brain function in health and disorder.

    Dr. Dimitri Van De Ville

    Dr. Dimitri Van De Ville received his M.S. and Ph.D. degrees from Ghent University, Belgium, in 1998 and 2002, respectively. He was a postdoctoral fellow at EPFL before leading the Signal Processing Unit at the University Hospital of Geneva as part of the CIBM Center for Biomedical Imaging. Since 2024, he has been a Full Professor at EPFL’s Neuro-X Institute with a joint appointment at the University of Geneva. His interdisciplinary research focuses on computational neuroimaging, wavelets, sparsity, and graph signal processing, applied to MRI and M/EEG data.

    In this episode, he discusses current and emerging neuroimaging modalities such as intracranial recordings, fMRI, fNIRS, M/EEG, and functional ultrasound (fUS). He highlights how signal processing plays a vital role in data formation, preprocessing, and analysis, enabling researchers to extract meaningful information about brain activity. The discussion also touches on innovations such as independent component analysis, connectomics, and the growing influence of AI and deep learning in neuroimaging. Dr. Van De Ville concludes by reflecting on the field’s future—emphasizing multimodal integration, brain–body connectivity, and targeted neuromodulation as key directions for advancing both neuroscience research and clinical applications.

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    43 分
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