FL-RCE 2026

Workshop on Federated Learning for Resource Constraint Environments

Co-located with IEEE/ACM CCGrid 2026

About the Workshop

Artificial Intelligence (AI) is rapidly emerging as an enabler of sustainable growth, resilience, and digital inclusion, particularly in non-urban environments where access to infrastructure, expertise, and connectivity is limited. By decentralising intelligence and embedding it into affordable, adaptive, and resource-efficient systems, AI offers a pathway to bridge the persistent urban-rural digital divide.

Building on the vision of RuralAI, intelligent, low-cost, and distributed solutions have the potential to unlock unprecedented opportunities for both social and industry communities in rural contexts. Examples include precision farming techniques that enhance yields while conserving resources, environmental monitoring systems that deliver real-time insights for managing natural ecosystems, healthcare applications that extend diagnostic capabilities to underserved populations, and disaster preparedness tools that strengthen resilience through early warning.

Despite this promise, such deployments face unique constraints that differ significantly from those in urban or data-centre settings. Limited and intermittent connectivity, scarce computing resources, and strict energy budgets demand novel approaches for sharing and processing data, training and deploying models, and ensuring robustness under resource constraints.

Relevance to CCGrid

These challenges align directly with the research focus of CCGrid, which emphasises scalable, distributed, and resource-aware computing. By leveraging advances in grid, cloud, and edge computing, the proposed workshop seeks to bring together researchers and practitioners to explore lightweight, energy-aware AI methods; serverless and federated learning architectures; and collaborative edge-cloud frameworks tailored for rural and resource-constrained environments.

Topics of Interest

This workshop provides a platform for researchers and practitioners to discuss and share the current and emerging state-of-the-art, challenges, and solutions on topics including (but not limited to):

Algorithms & Architectures

  • Lightweight and Energy-Aware Algorithms for Low-Power IoT Devices
  • Personalisation and Model Adaptation for Heterogeneous Rural IoT Networks
  • Serverless Frameworks for IoT Deployments in RuralAI
  • Edge-Cloud Collaboration Models for Rural IoT Applications

Security & Resilience

  • Security and Privacy Preserving Techniques in Distributed Rural AI Systems
  • Resilient AI Architectures for Intermittent Connectivity in Remote IoT Networks

Sustainability & Ethics

  • Sustainable AI for Rural Development: Balancing Efficiency, Scalability, and Environmental Impact
  • Policy, Governance, and Ethical Frameworks for Federated Learning in Rural Communities

Applications

  • Drone-Based Sensing and Federated Intelligence for Rural Applications
  • Agricultural Robotics and Automation Powered by Federated Learning
  • Healthcare at the Edge: Telemedicine and Monitoring in Rural Communities
  • Multi-Modal Data Fusion in RuralAI Applications

Platforms & Deployment

  • Low-Cost and Open-Source Federated Platforms for Rural Innovation
  • Scaling RuralAI: From Pilot Deployments to Global Rural Connectivity and Impact

Call for Papers

We invite submissions of original research papers, work-in-progress papers, and position papers addressing the challenges and opportunities in federated learning and distributed AI for resource-constrained environments.

Submission Guidelines

Important Dates

Paper Submission Deadline: February 15, 2026
Notification of Acceptance: March 8, 2026
Camera-Ready Papers Due: March 15, 2026
Workshop Date: TBA (during CCGrid 2026)

All deadlines are 23:59 AoE (Anywhere on Earth)

Workshop Organizers

Shaleeza Sohail

University of Newcastle, Australia

Email: shaleeza.sohail@newcastle.edu.au

Shaleeza Sohail received her Master's and PhD degrees in Computer Science and Engineering from the University of New South Wales, Australia. She is currently a Lecturer and Program Convenor at the University of Newcastle, where she leads and coordinates postgraduate programs in Information Technology. Her research interests span federated learning, blockchain, and the Internet of Things (IoT). She has actively participated in and co-led several national and international research projects and has published over 50 papers in leading international conferences and journals.

Farzana Zahid

University of Waikato, New Zealand

Email: farzana.zahid@waikato.ac.nz

Farzana Zahid received her Ph.D. degree in cybersecurity from the Auckland University of Technology, Auckland, New Zealand. She is currently a Lecturer with the Department of Computer Science, University of Waikato, Hamilton, New Zealand. Her research interests include active security, IoT, ICS, Cloud Computing, and Machine Learning. Her research is dedicated to enhancing the self-protection of resource-constrained devices. She has published her work in top-tier peer-reviewed journals and conferences and brings experience in co-leading national and international research projects.

Program Committee

Xiao Chen
University of Newcastle, Australia
Boyang Li
University of Newcastle, Australia
Sky Miao
University of Newcastle, Australia
Victoria Huang
National Institute of Water and Atmospheric Research, New Zealand
Matthew Kuo
Auckland University of Technology, New Zealand
Mamoona Asghar
University of Galway, United Kingdom
Akbar Hussain
Eastern Institute of Technology, New Zealand
Daniyal Munir
RPTU University Kaiserslautern, Germany
Munir Ahmed
Barani Institute of Technology, Pakistan
Aasia Khanum
Forman Christian College, Pakistan
Teuku Geumpana
University of Newcastle, Australia
Barry Dowdeswell
Otago Polytechnic, New Zealand
Collin Pillbrow
University of Waikato, New Zealand
Sapna Jaidka
University of Waikato, New Zealand

Workshop Structure

The workshop will include:

Contact Us

Have questions about the workshop? Get in touch with the organizers:

Direct Contact

Shaleeza Sohail
University of Newcastle, Australia
shaleeza.sohail@newcastle.edu.au
Farzana Zahid
University of Waikato, New Zealand
farzana.zahid@waikato.ac.nz