2026 IEEE International Conference on Acoustics, Speech, and Signal Processing
4-8 May 2026, Barcelona, Spain
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Educational Activities

Background

The IEEE Signal Processing Society (SPS) is strongly dedicated to advancing signal processing education at all levels through high-quality, accessible, and inclusive educational initiatives. SPS supports lifelong learning by providing resources and programs that serve learners ranging from secondary education students to seasoned professionals, fostering both foundational understanding and advanced expertise in the field.

The SPS Educational Activities program offers a diverse portfolio of learning opportunities designed for students, non-experts, educators, and professionals. These activities include tutorials, outreach programs, and SPS-supported workshops that promote knowledge dissemination, skill development, and community engagement. By addressing audiences with varied backgrounds and career stages, the program aims to strengthen the global signal processing ecosystem and encourage the effective transfer of knowledge across academia, industry, and society.

Program Highlights Include:

Join us at ICASSP 2026 for an engaging and inclusive educational experience that spans all levels of learning. Whether you are discovering signal processing for the first time, deepening your expertise, or sharing knowledge through an SPS-supported workshop, the Educational Activities program offers opportunities to learn, teach, and inspire within the global signal processing community.

Session Detail

Tutorials

Monday,  4 May 2026

Program Page Link: https://2026.ieeeicassp.org/tutorials

Tutorials provide structured, in-depth learning experiences on core and emerging topics in signal processing. Designed for graduate students and professionals alike, the sessions combine foundational concepts with practical insights, enabling participants to broaden their knowledge, update their skills, and engage with leading experts in the field.

AI Panel

Date TBD

This roundtable discussion will explore how recent advances in machine learning and artificial intelligence are shaping the education of the next generation of signal processing practitioners and researchers.

ETON Talks

This program consists of two lectures that offer an overview of significant advancements and emerging topics in signal processing. The Expert-to-Non-Expert Talk (ETON) series is designed for both students and industry professionals to bridge knowledge gaps. These lectures are delivered by the original inventors or leading experts in the field, providing valuable insights and fostering a deeper understanding of cutting-edge developments.

ETON 1: Location-aware sensing: Can Google maps help our cars see better? – Thursday, 7 May 2026, 12:45 – 13:45

Abstract: Autonomous vehicles rely on sensors such as LiDAR and radar to perceive their surroundings; however, these sensing systems are often developed independently of navigation applications such as Google Maps. This talk first demonstrates how location awareness, enabled by static street-topology maps, can be leveraged to adapt LiDAR and radar sensing. A live demonstration of a location-aware LiDAR system is included.

The second part of the talk examines the impact of position and orientation uncertainties on location-aware sensing solutions. To address this challenge, tools from stochastic optimization are employed, showing that location-aware sensing remains viable under practical levels of uncertainty. Finally, the talk outlines steps toward the commercialization of location-aware sensing and highlights promising directions for future research.

Nitin_Jonathan_Myers

Biography: Nitin Jonathan Myers received the B.Tech. and M.Tech. degrees in electrical engineering from IIT Madras in 2016 and the Ph.D. degree in electrical and computer engineering from The University of Texas at Austin in 2020. He is currently a tenured Assistant Professor at the Delft Center for Systems and Control, TU Delft. Previously, he was a Senior Engineer with Samsung Semiconductor’s 5G Modem R&D team. His research focuses on optimization and multi-dimensional signal processing for communications and sensing. He has received multiple academic and research awards, including IEEE paper and demo recognitions, fellowships, and teaching excellence honors at TU Delft.

ETON 2: Deep-Free Physics-Informed Foundation Modeling in Wireless Communications – Wednesday, 6 May 2026, 12:45 – 13:45

Abstract: This talk revisits classical generative modeling approaches, with an emphasis on mixture models developed prior to the rise of deep generative learning, and highlights their continued relevance for the physical layer of wireless communications. Owing to their capacity for analytical inference, mixture models form a natural connection between machine learning and classical signal processing, where covariance information is central to many physical-layer tasks.

By incorporating the underlying physics of wireless channels, these models enable lightweight, interpretable, and easily trainable solutions with strong generalization properties. The framework naturally extends to multimodal settings through multi-view mixture models, providing a unified and efficient approach for handling diverse data types. Overall, the talk bridges classical methods with modern generative modeling and demonstrates that effective generative modeling need not rely solely on deep learning.

Prof. Wolfgang Utschick, Fachgebiet: Methoden der Signalverarbeitung; Foto: Eckert und Heddergott Verwendung frei fuer die Berichterstattung ueber die TU Muenchen unter Nennung des Copyrights

Biography: Wolfgang Utschick, IEEE Fellow, is a Full Professor of Signal Processing at the Technical University of Munich. His research mission is to integrate artificial intelligence into the physical layer of wireless communication systems. He is actively involved in major German 6G initiatives, including the 6G Life Research Hub and the 6G Bavarian Future Lab, and leads multiple national and international 6G research projects in close collaboration with industry. Since the late 1990s, his work has focused on machine learning for communications, with key contributions to generative modeling for wireless systems.

Educational Short Courses

Monday, 4 and Tuesday, 5 May 2026

Program Page Link: https://2026.ieeeicassp.org/educational-short-courses/

These courses aimed at providing a deeper and multi-sided understanding of a topic including hands-on experience, providing the material of the course as well as a professional development certificate. Registration to the main conference is not required to attend short courses.

Preparing to Host an IEEE Signal Processing Society Workshop Session

Friday, 8 May 2026, 9:00 – 10:30

Join us for an engaging learning session designed to provide everything you need to know about proposing, planning, and organizing an SPS Workshop. This session will cover the essentials, including how to prepare and submit a proposal, key organizational requirements, and best practices for success.

The event will feature a discussion with experienced workshop organizers who will share their insights and tips, followed by a Q&A session with SPS Leadership.

Attendees will also gain valuable advice from staff and leadership to help navigate the planning journey. Whether you’re a first-time organizer or looking to refine your approach, this session offers practical guidance to bring your ideas to life. Don’t miss this opportunity to connect with experts and enhance your planning expertise!

K-12 Activities

Thursday, 7 May 2026, 9:00 – 11:00

This short course provides a comprehensive overview of signal processing as a foundational discipline at the intersection of mathematics and engineering, underpinning many of today’s core technologies. Motivated by the rapid growth of intelligent, connected systems, the course introduces the fundamental principles governing the acquisition, analysis, transformation, and interpretation of signals, including audio, images, sensor data, and wireless communication signals.

The course highlights signal processing as the “hidden engine” behind modern innovations, such as speech and image recognition in Artificial Intelligence (AI) systems, high-speed wireless communications (e.g., 5G), and noise reduction and enhancement in multimedia applications. Through intuitive explanations and illustrative examples, participants will gain insights into how signal processing techniques enable reliable, efficient, and high-performance technological solutions. This course is addressed to high-school students seeking a clear conceptual foundation in signal processing and its role in enabling today’s connected data-driven world.