News

  • 01 May 2024: Constraint 2024 Accepted at IEEE Bigdata 2024 and website online.
  • Overview

    The development of AI/Bigdata technology has increased human efficiency, accessibility, and safety. However, these AI/Bigdata technologies are often constrained by limitations in computing power, energy, data, and security risks in turn leading to a lack of equitable distribution of technology that is essential for promoting innovation and improving the lives of people. 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. As AI and bigdata systems become more prevalent, it is important to develop strategies that enable these systems to operate efficiently [1-3] and sustainably in a wide range of environments and applications [4]. The proposed workshop session aims to provide a common ground to showcase recent advancements in developing Bigdata/AI systems under various constraints, build collaborations across disciplines, share benchmarks, algorithms, and methods for resource-constrained AI systems, and inspire research in domains where AI is used to address those research constraints The broader objective of CONSTRAINT-2024 will be.

    • 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 area of the “Developing AI and Bigdata Technology Under Resource Constraints” community from around the world to collaborate with other researchers.
    • To foster the development of a broader multi-disciplinary framework to adopt AI systems in daily life.
    • Submission

      CONSTRAINT-2024 welcomes submissions on various scopes to contribute in developing bigdata and AI systems under a variety of resource constraints and to address resource constraints. We will particularly encourage studies that address either practical applications or improve upon resource constraints for a variety of AI/Bigdata systems in the field but now limited to
    • Creating new resources such as data, hardware, and protocols for AI/Bigdata systems, Algorithms and Applications
    • Optimizing data science systems, embedded platforms, and test beds for AI/Bigdata systems, Algorithms and Applications
    • Data privacy, hardware privacy, and new AI/Bigdata system and Algorithms design
    • Algorithms for Urban computing and bigdata analytics under resource constraints.
    • Energy-efficient computing and inferencing for AI/bigdata systems, Algorithms and Applications
    • Optimized VLSI and architecture design for AI/bigdata and data science applications
    • Algorithms and systems for increasing database efficiency using Machine Learning
    • Optimizing Machine Learning 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 system design and evaluation
    • Frameworks and methods to improve equity of AI/Bigdata systems especially under constraint of data and infrastructure.
    • AI and Bigdata Algorithms catering to applications in resource constraint third world applications.
    • Empirical study of resource constraints in areas of healthcare, supply chain, enterprise mobility solution, mobile systems, edge computing, education, smart campus, smart city and buildings, manufacturing, energy, demand forecasting, finance, retail, social computation, crowd sensing, wireless communication and networking, smart mobility, cyber security, environmental policy, climate change, and control, internet of personalized things, etc.
    • Applications of AI and ML under resource constraints.

      Please submit your papers through wi-lab



      Important Dates

    • May 25, 2024: First Call for Papers
    • June 25, 2024: Second Call for Papers
    • Oct 14, 2024: Workshop Paper Due Date
    • Nov 10, 2024: Notification of Acceptance
    • Nov 20, 2024: Camera-ready papers due
    • December 15-18, 2024: Workshop Dates




    • Organizers

    • Manikandan Ravikiran, R&D Center, Hitachi India Pvt Ltd/Indian Institute of Technology, Mandi
    • Soumen Biswas, R&D Center, Hitachi India Pvt Ltd
    • Aniruddha Rajendra Rao, R&D Center, Hitachi America Ltd
    • Arnav Bhavsar, Indian Institute of Technology, Mandi
    • Satyanarayanan N. Aakur Auburn University
    • Arunkumar Bagavathi, Oklahoma State University




    • Contact Us

      Manikandan Ravikiran: manikandan@hitachi.co.in
      Soumen Biswas: soumen.biswas@hitachi.co.in