The objective of the workshop "GenAI-Driven Big Data Innovations in the Edge-Cloud Continuum" is to provide a comprehensive platform for researchers, practitioners, and industry experts to exchange knowledge and insights on the integration of Generative AI with big data within the edge-cloud continuum. The workshop aims to highlight cutting-edge techniques, innovative solutions, and practical applications that enhance AI workload optimization, secure data handling, and real-time data processing across the computing continuum. By facilitating discussions on advanced algorithms, orchestration tools, and deployment strategies, the workshop seeks to drive advancements in the field and foster collaboration among attendees to address the challenges and opportunities in leveraging GenAI for big data across edge and cloud environments.
The workshop on "GenAI-Driven Big Data Innovations in the Edge-Cloud Continuum" focuses on the latest advancements in the integration of Generative AI (GenAI) with big data, emphasizing the practical and theoretical aspects of deploying AI solutions across the edge-cloud continuum. This workshop will explore various techniques and algorithms, including advances in Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), as well as their applications in data synthesis and augmentation. Attendees will gain insights into the design and implementation of edge AI solutions, the optimization of AI workloads on edge devices, and scalable AI/ML model deployment in the cloud. Additionally, the workshop will address key challenges such as secure data handling, privacy-preserving machine learning, real-time data processing, and fault-tolerant AI systems, especially in the edge-cloud continuum. By bringing together experts and practitioners, this workshop aims to facilitate discussions on the effective orchestration of AI tasks, the use of containerization and microservices, and the implementation of security measures to ensure robust and efficient AI applications in edge-cloud environments.
Name: Chinmaya Dehury
Email: dehury(at)ut.ee
Address: University of Tartu, Estonia
Webpage: https://kodu.ut.ee/~dehury/
Duration: Half-day
Structure:
Authors are required to submit fully formatted, original papers (in PDF format) via gAI-BDEC2 easychair. All workshop papers are limited to no more than 6 pages, including references, in the IEEE format aligned with the BDA 2024 main conference guidelines. Each submission must be written in English, accompanied by a 75 to 200 words abstract that clearly outlines the scope and contributions of the paper. Papers exceeding 6 pages will not be accepted. At least one author of each accepted paper is required to register for the workshop.
Authors are required to submit fully formatted, original papers (in PDF format) via Easy Chair through >>this link<< .
We are pleased to inform you that we intend to invite you to submit an extended version of your paper for publication in a Special Issue of a Springer journal. We are in the process of SI approaval and we will provide further details as soon as the process is complete.
Those who deliver a presentation at the event will be awarded a certificate acknowledging their contribution. Additionally, all attendees will receive a certificate of participation.
We look forward to your active participation and hope these recognitions serve as a testament to your engagement and dedication.