3rd Workshop on Handling Resource Constraints for/using Big Data and AI

Overview

The development of AI/BigData technology has increased human efficiency, accessibility, and safety. However, these technologies are often constrained by limitations in computing power, energy, data, and security risks, leading to a lack of equitable distribution of technology that is essential for promoting innovation and improving lives.

As such, "advancing technology for humanity as a whole" requires addressing these resource constraints using a multi-disciplinary approach that involves advances in computing, energy, connectivity, data engineering, and environmental sustainability.

The broader objectives of CONSTRAINT-2025 are:

• To investigate challenges and resource constraints that prevent development and access to BigData and AI Applications
• To promote research in developing equitable BigData systems and applications
• To provide opportunities for researchers from the "Developing AI and BigData Technology Under Resource Constraints" community worldwide to collaborate
• To foster the development of a broader multi-disciplinary framework to adopt AI systems in daily life

Call for Papers

CONSTRAINT-2025 welcomes submissions on various topics contributing to developing BigData and AI systems under resource constraints. We particularly encourage studies that address practical applications or improve upon resource constraints for AI/BigData systems including, but not limited to:

• Creating new resources such as data, hardware, and protocols for AI/BigData systems
• Optimizing data science systems, embedded platforms, and test beds
• Data privacy, hardware privacy, and new AI/BigData system designs
• Algorithms for urban computing and BigData analytics under resource constraints
• Energy-efficient computing and inferencing for AI/BigData systems
• Optimized VLSI and architecture design for AI/BigData applications
• Algorithms for increasing database efficiency using Machine Learning
• Scaling and optimizing Large Language Models (LLMs) under resource-constrained settings
• Optimizing ML algorithms for environmental sustainability and Green Machine Learning
• Cheaper surrogate AI and BigData systems, algorithms and applications
• Tools and methods for "green AI systems" hardware-software design and evaluation
• Frameworks to improve equity of AI/BigData systems under data and infrastructure constraints
• AI and BigData algorithms for resource-constrained applications in developing regions
• Empirical studies in healthcare, supply chain, smart cities, manufacturing, energy, finance, retail, and more
• Applications of AI and ML under resource constraints

Important Dates

• May 25, 2025: First Call for Papers
• June 25, 2025: Second Call for Papers
• October 27, 2025: Workshop Paper Due Date
• November 10, 2025: Notification of Acceptance
• November 17, 2025: Camera-ready Papers Due
• December 15-18, 2025 (Online/Pre-Recorded) Workshop Dates

Organizers

• Manikandan Ravikiran, Thoughtworks AI Research Lab/Indian Institute of Technology, Mandi
• Karrtik Iyer, Thoughtworks AI Research Lab
• Ankit Sharma, R&D Center, Hitachi India Pvt Ltd/Indian Institute of Technology, Roorkee
• Arnav Bhavsar, Indian Institute of Technology, Mandi
• Rohit Saluja, Indian Institute of Technology, Mandi
• Satyanarayanan N. Aakur, Auburn University