CFP and demos, Excellence in Edge Artificial Intelligence, Cambridge UK, June 25th

Deadline extended. There will be no more extensions…

 

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Excellence in Edge Artificial Intelligence In Conjunction with ACM MobiSys 2026

25 June 2026 – William Gates Building, University of Cambridge, UK

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Workshop website: https://excelai2026.short.gy      

 

The convergence of AI and edge computing represents a new era of technological advances, where the immediacy of data processing and the sophistication of AI algorithms lead to new products and services. Industries are rapidly adopting edge AI applications to streamline costs, automate complex processes, enhance decision-making capabilities, and refine operational efficiency. These applications are not just theoretical constructs; they are real-world solutions that are reshaping industries.

This workshop is dedicated to exploring the frontiers of the AI and edge computing synergy, focusing on the development of scalable and robust AI systems. The workshop is organized and supported by the dAIEdge European Network of Excellence on AI at the Edge. In order to make the workshop more interactive and lively, there will be a demo session. In the latter, participants will be able to show live demos, either on-site or with a video, of their latest research results. Participants in any session will be automatically invited to participate in and benefit from dAIEdge’s network of excellence. There will be a best paper award.

 

Topics of interest include (but are not limited to):

•             Edge AI-based applications, use cases, products and services

•             Edge AI tools and methodologies

•             Computer vision: image classification, object detection, semantic segmentation, etc.

•             Edge AI natural language processing, speech recognition and synthesis

•             Energy optimization for edge AI devices

•             Reconfigurable edge AI

•             Optimization and approximation methods and techniques for edge neural networks

•             Multimodal learning for edge AI

•             Federated learning

•             Edge AI accelerators and HW (GPUs, NPUs, TPUs, ASICs, FPGAs, RISC-V, etc.)

•             Edge AI hardware-software co-design methods and tools

•             Neuromorphic HW Architectures

•             Smart connectivity at the edge

•             Edge AI for immersive technologies (XR/VR/AR/MR, metaverse/omniverse/multiverse)

•             Simulation and analysis techniques for edge AI

•             Generative edge AI

•             Transformers at the edge: data, hardware, and software engineering challenges

•             Trustworthy edge AI (security, privacy, reliability, explainability, interpretability, etc.)

•             Edge AI verification, validation and testing

•             Benchmarking edge AI models

•             Edge AI in Space (satellites, Earth observation, etc.)

•             Ethical implications of edge AI

 

Important dates:

Submission deadline: 15 March 2026 22 March 2026

Acceptance notification: 23 April 2026

Camera ready: 30 April 2026

Workshop date: 25 June 2026

 

Submissions:

Papers will be reviewed by the workshop's technical program committee according to criteria regarding a submission's quality, relevance to the workshop's topics, and, foremost, its potential to spark discussions about directions, insights, and solutions on the topics mentioned above. Research papers, case studies, position papers and work-in-progress are all welcome.

 Papers should be formatted for 8.5×11-inch paper. The length of the paper must be no more than 6 pages in the ACM double-column format (10-pt font), excluding references and appendices. Authors are suggested to use the ACM Master article template,  with the \documentclass[sigconf,10pt]{acmart} option.  Papers should be uploaded as PDF and not anonymized (review is single blind). At least one of the authors must register at the conference and attend the workshop to present the paper if it is accepted. Accepted papers will be published in the ACM Digital Library. There will be a best paper award with diploma and 300€ (the latter will only be awarded if the authors of the best paper are not part of the dAIEdge Consortium). The selection of the best paper will be made by the PC and the decision will be irrevocable.

Click here to access the submission site

 

Call for demos:

Demos will be either on-site, remote via Teams or similar, or through a pre-recorded video (with voiceover). Demo proposers do not need to submit a paper to the workshop. The demo should be, in any case, related to the topics of the workshop, and should not last more than 20 minutes.

If the number of demos submitted is too high the program committee will make a selection, prioritizing on-site demos.

To propose a demo, please fill out the form in the workshop website.

 

Organizers:

German Research Center for Artificial Intelligence (DFKI), Germany Sorbonne University, France The University of Edinburgh, United Kingdom University of Glasgow, United Kingdom Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), France Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e. V., Germany Institut National de Recherche en Informatique et en Automatique (INRIA), France Eidgenoessische Technische Hochschule Zuerich (ETHZ), Switzerland STMicroelectronics SRL, Italy Thales SIX GTS France SAS, France Blekinge Tekniska Hogskola (BTH), Sweden Centre d'Excellence en Technologies de l'Information et de la Communication (CETIC), Belgium Deutsche Zentrum für Luft- und Raumfahrt e. V. (DLR), Germany Safran Electronics & Defense, France FundingBox Accelerator Sp. z o.o., Poland Idryma Technologias Kai Erevnas (FORTH), Greece Hipert Slr, Italy Interuniversitair Micro-Electronica Centrum (IMEC), Belgium Sofia University St Kliment Ohridski, Bulgaria Fundación Instituto Internacional de Investigación en Inteligencia Artificial y Ciencias de la Computación, Spain Katholieke Universiteit Leuven (KUL), Belgium SINTEF AS, Norway Synopsys International Ltd, Ireland Ubotica Technologies Ltd, Ireland University of Castilla-La Mancha (UCLM), Spain Università degli Studi di Modena e Reggio Emilia (UNIMORE), Italy University of Salamanca (USAL), Spain Varjo Technologies Oy, Finland VERSES Global BV, Netherlands Vicomtech, Spain Aegis Rider AG, Switzerland Centre suisse d'électronique et de microtechnique (CSEM), Switzerland Haute école spécialisée de Suisse occidentale (HE-SO), Switzerland

 

ACM MMSports’26 @ ACM Multimedia 2026 – Call for Papers

9th International Workshop on Multimedia Content Analysis in Sports (MMSports'26) @ACM Multimedia, Nov 10 – Nov 14, 2025, Rio de Janeiro, Brazil

We'd like to invite you to submit your paper for the 9th International Workshop on Multimedia Content Analysis in Sports to be held Rio de Janeiro, Brazil together with ACM Multimedia 2026. The ambition of this workshop is to bring together researchers and practitioners from many different disciplines to share ideas and methods on current single and multimodal content analysis research in sports. We welcome single and multimodal-based research contributions as well as best-practice contributions focusing on the following (and similar, but not limited to) topics:
 – annotation and indexing in sports
 
 
– tracking people/ athlete and objects in sports
 – activity recognition, classification, and evaluation in sports
 – 3D scene and motion reconstruction in sports
 – event detection and indexing in sports
 – performance assessment in sports
 – injury analysis a
nd prevention in sports
 – data driven analysis in sports
 – graphical augmentation and visualization in sports
 – automated training assistance in sports
 – camera pose and motion tracking in sports
 – brave new ideas / extraordinary multimodal solutions in sp
orts
 – personal virtual (home) trainers/coaches in sports
 – datasets in sports
 – graphical effects in sports
 – alternative sensing in sports (beyond the visible spectrum)
 – multimodal perception in sports
 – exploiting physical knowledge in learning systems
 for sports
 – sports knowledge discovery
 – narrative generation and narrative analysis in sports
 – mobile sports application
 – multimedia in sports beyond video, including 3D data and sensor data
 
Submissions can be of varying length from 6 to 8 pages, plu
s up to two pages for the references. There is no distinction between long and short papers, but the authors may themselves decide on the appropriate length of their paper. All papers will undergo the same review process with the same review period.
 
Pleas
e refer to the workshop website for further information: http://mmsports.multimedia-computing.de/mmsports2026/index.html  

 IMPORTANT DATES
 Submission Due:                          16 July 2026
 
 
Acceptance Notification:               06 August 2026
 Camera Ready Submission:         20 August 2026
 
 
Workshop Date:                            TBA; either Nov 10th or Nov 14th, 2026

ACM MMSports’26 Chairs: Thomas Moeslund, Rainer Lienhart and Hideo Saito


Call for Participants: MEGC2026: Micro-Expression Grand Challenge on Visual Question Answering at FG2026

We are pleased to invite you to participate in the Micro-Expression Grand Challenge (MEGC) 2026 on Visual Question Answering, held in conjunction with IEEE FG 2026 (Face and Gesture).

🔗 Official Challenge Website:
https://megc2026.github.io/challenge.html

MEGC 2026 focuses on advancing micro-expression analysis using Vision-Language Models (VLMs) and Multimodal Large Language Models (MLLMs). This year’s challenge introduces two reasoning-oriented tasks:

🔥 Task 1: ME-VQA (Micro-Expression Visual Question Answering)
Participants analyze short video clips containing micro-expressions and answer natural language questions

🔥 Task 2: ME-LVQA (Micro-Expression Long-Video Question Answering)
A more challenging task where participants analyze long videos that may contain multiple micro-expressions

📅 Important Dates
Competition Opens: 23 December 2025
Competition Closes: 30 March 2026

Best Regards

News for Learning Over Time (LOT 2.0) Spring School, registration is open and speaker confirmation!

The second edition of the Spring School on Learning Over Time (LOT 2.0) will be held in Barcelona from April 27 to 30, 2026. Save the date! 

The school focuses on machines that continuously and sustainably learn over time, with a particular emphasis on rethinking the role of data in this process and on lean learning solutions, inspired by Collectionless AI (https://collectionless.ai/).

We have speaker confirmation: we are pleased to inform you that Prof. Joost van de Weijer, Prof. Egidio Falotico, and Prof. David Kappel will be holding a session! will be holding a session!

More info on the webpage https://lot2-spring-school.cttc.es/index.php/lecturers-staff

More speakers will be announced soon, stay tuned!

Secure your place, registration is open (deadline 5th of April)
Register here now: https://lot2-spring-school.cttc.es/index.php/registration

Topics

  • Collectionless AI 
  • Continual/Lifelong Learning
  • Reinforcement Learning
  • Time Series
  • Representation Learning and Universal Representation
  • Collaborative Learning
  • Distributed / Decentralized Learning
  • Brain-inspired Computing
  • Online Learning
  • Active Learning
  • Curriculum Learning
  • Domain Adaptation
  • Transfer Learning
  • In-Context Learning
  • On-device Learning 

When: 
April 27-30, 2026

Where: 
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Parc Mediterrani de la Tecnologia
Castelldefels, Barcelona (Spain)

See you there!

LOT2.0 Organizers
Paolo Dini, Marco Miozzo, Vincenzo Lomonaco, Stefano Melacci

Special Issue on Autonomous and Evolutive Optimization in Networked AI

IEEE Journal of Selected Topics in Signal Processing (JSTSP) Special Issue on “Autonomous and Evolutive Optimization in Networked AI“.

Special Issue Overview:
This Special Issue addresses autonomous and evolutive optimization in networked AI, a transformative paradigm that integrates traditional adaptive signal processing with modern deep learning approaches. It explores online, self-evolving mechanisms that enable distributed models to improve through dynamic data acquisition, reward generation, and pseudo-labeling. Emphasis is placed on unifying supervised and reinforcement learning within multi-agent, time-varying environments. The issue highlights scalable, self-optimizing AI architectures applicable to communications, IoT, and intelligent signal processing. Its goal is to advance foundational methodologies and promote impactful real-world applications in next-generation AI systems.

Topics of Interest Include:
• Foundations and principles of signal processing in networking systems of AI
• Mathematical underpinnings of networked AI optimization
• End-cloud collaborative large language models with evolutive optimization
• Coordinated sensing and control processing in autonomous multi-agent AI systems
• Multimodal and adaptive signal processing with networked AI
• Networked AI for cognitive communications and networks
• Online model-drift detection and compensation mechanisms
• Networked AI enhanced signal processing in non-stationary environments
• Practices of autonomous and evolutive learning for networked AI systems

Key Dates:
• Submission Deadline: June 15, 2026
• First Review Due: August 14, 2026
• Final Decision: November 20, 2026
• Publication: January 2027

Links:
IEEE JSTSP Special Issue Call: https://signalprocessingsociety.org/events/ieee-jstsp-special-issue-autonomous-and-evolutive-optimization-networked-ai
Guidelines: https://signalprocessingsociety.org/publications-resources/ieee-journal-selected-topics-signal-processing
Submission: https://mc.manuscriptcentral.com/sps-ieee

Guest Editors:
Liang Song, Fudan University, China, songl@fudan.edu.cn (Lead GE)
Jiangchuan Liu, Simon Fraser University, Canada, jcliu@sfu.ca
Amit Dvir, Ariel University, Israel, amitdv@g.ariel.ac.il
Athanassios Skodras, University of Patras, Greece, skodras@upatras.gr
Victor C.M. Leung, University of British Columbia, Canada, vleung@ece.ubc.ca
Qi Bi, China Telecom Research Institute, China, qibi@chinatelecom.cn

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