Workshop at BDA 2024

The following two workshops are selected by the workshop chairs.

Workshop 1

Title: GenAI-Driven Big Data Innovations in the Edge-Cloud Continuum

Objective & Scope

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.

Description

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.

Topics of Interest

• Generative AI Techniques and Algorithms
• Advances in Generative Adversarial Networks (GANs)
• Variational Autoencoders (VAEs) for Big Data
• Data Synthesis and Augmentation using GenAI
• Design and Implementation of Edge AI Solutions
• Optimizing AI Workloads on Edge Devices
• Scalable AI/ML Model Deployment in the Cloud
• Serverless Computing for Big Data and AI
• Use of AI in Seamless Integration of Edge and Cloud Resources
• AI/ML Model Training and Deployment on distributed computing continuum
• Secure Data Handling in Edge-Cloud Systems
• Privacy-Preserving Machine Learning Techniques
• Stream Processing and Real-time Data Insights
• Low-latency AI Applications in Edge-Cloud Settings
• Successful Implementations of GenAI in Industry
• Tools for Building and Deploying GenAI Models
• Strategies for Building Fault-Tolerant AI Systems
• Techniques for Orchestrating AI Tasks across Edge and Cloud
• Orchestration Tools and Platforms (e.g., Kubernetes, Docker)
• Scheduling Algorithms for Optimized AI Processing
• Containerization and Microservices for AI
• Tools for Monitoring AI Applications and Implementing Effective Logging Mechanisms
• Data Orchestration and Workflow Management
• Managing AI Data Pipelines across Edge and Cloud
• Implementing Security Orchestration, Automation, and Response (SOAR) for AI Systems

Target Audience

• Researchers and Academics: Scholars and students specializing in AI, machine learning, data science, and edge-cloud computing.
• Students and Enthusiasts: Graduate and postgraduate students, as well as tech enthusiasts eager to learn about the latest trends and network with professionals in the field.
• Industry Professionals: Engineers, data scientists, and IT professionals working in the fields of AI, GenAI, cloud computing, edge computing, big data analytics, and IoT.

Workshop Organizers

Program Committee Members (tentative)

Workshop Format

Duration: Half-day

Tentative Timeline

Submission Guidelines

Authors are required to submit fully formatted, original papers (in PDF format) via [link will be provided soon]. 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.

Workshop 2

Title: Secure, Reliable, and Ethical Generative AI Implementation

Objective & Scope

This workshop invites innovative ideas to present around the implementation of a secure, reliable, and ethical GenAI solution for any organization and/or business requirements, across any domain. We welcome original research ideas that focus on various considerations and implementation aspects of a GenAI implementation.

Description

Generative Artificial Intelligence (GenAI) technology, with its ability to learn ubiquitously from all available sources, poses unique challenges in terms of ethics, privacy, reliability, and potential misuse. These challenges make it mandatory for Gen AI systems to have well-defined boundaries, principles, and controls in the form of various guardrails. With the increasing adoption of GenAI solutions across industries, it is imperative to put in place various checks and bounds for secure and reliable GenAI implementation. This industry workshop focuses on those aspects of GenAI implementation.

Topics of Interest

• Security, Data Privacy and Legal considerations in GenAI adoption
• Considerations for a Reliable GenAI implementation
• Effectiveness of GenAI Guardrails
• Transparency and Explainability of GenAI output
• Prevention of Bias and Discriminatory data in training corpus
• Prevention of Hallucination in GenAI outcome
• Measurement of Accuracy of GenAI content
• Considerations on Regulatory requirements, Intellectual Property Rights

Target Audience

Researchers and Academics working in AI and GenAI, Students and Enthusiasts interested in GenAI technology, and Industry Professionals working in GenAI implementation.

Workshop Organizers

Program Committee Members (tentative)

• Name: Dr. Mainak Adhikari | University: IISER Thiruvananthapuram | Country: India
• Name: Dr. Dhananjoy Dey | University: IIIT Lucknow | Country: India
• Name: Ajay Vaidya | Organization: Tata Consultancy Services | Country: India

Workshop Format

Duration: Half-day
Structure:

• 6 presentations, 20-30 min each
• Technical Panel Discussion: 1 Hour

Tentative Timeline

Submission Guidelines

Authors are required to submit fully formatted, original papers (in PDF format) via [link will be provided soon]. 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.