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Call for submission: 2026 INFORMS Conference on Service Science - Weaving the World with Digitalization and AI

  • 1.  Call for submission: 2026 INFORMS Conference on Service Science - Weaving the World with Digitalization and AI

    Posted 3 hours ago

    2026 INFORMS Conference on Service Science in Hangzhou, China

    Weaving the World with Digitalization and AI

    (Conference website http://icss2026.servicescienceglobal.org)


    Invited Track: Data-Driven Intelligence: Integrating Analytics, Artificial Intelligence, and Machine Learning for Smarter Decision-Making

    Track Organizers:

    Dr. Satish Mahadevan Srinivasan, Penn State Great Valley
    Dr. Luna Yang, Penn State Brandywine
    Dr. Yang Wang, La Salle University
    Dr. Abhishek Tripathi, The College of New Jersey

    Overview:
    The exponential growth of data and rapid advancements in artificial intelligence (AI) and machine learning (ML) are reshaping how organizations make strategic and operational decisions. From predictive maintenance and personalized healthcare to algorithmic trading and adaptive supply chains, data-driven intelligence lies at the heart of modern management science. However, harnessing the full potential of these technologies requires seamless integration across the analytics–AI–ML continuum, emphasizing transparency, ethics, and human-centered design.

    This invited track aims to bring together researchers and practitioners to explore advances, applications, and challenges at the intersection of data-driven analytics, AI, and ML. We seek contributions that highlight synergies among these fields to enable robust, accountable, and intelligent decision-making systems.

    Topics of Interest Include (but are not limited to):

    Data-Driven Analytics: Predictive and prescriptive analytics, optimization under uncertainty, real-time analytics, visualization.
    Artificial Intelligence: Explainable AI, ethical AI, intelligent decision support systems, cognitive and hybrid AI systems.
    Machine Learning: Deep learning, reinforcement learning, federated learning, interpretable ML, AutoML, and optimization–ML hybrids.
    Applications: Healthcare, finance, supply chain management, energy systems, smart infrastructure, networking, and more.

    Submission Guidelines:
    We invite extended abstracts (500–800 words) or full papers addressing theoretical, methodological, or applied contributions. Submissions should clearly articulate the problem, methodology, results, and implications for practice or research.

    Important Dates:

    Abstract/Paper Submission Deadline: January 15, 2026
    Notification of Acceptance: February 28, 2026
    Final Presentation Materials Due: March 31, 2026

    Track Structure:
    Accepted submissions will be organized into:

    Invited sessions featuring leading experts.
    Technical and applied research presentations.
    A panel discussion on "Future Directions in Data-Driven Decision Intelligence."

    This track aligns with INFORMS' mission to advance analytics and operational research for improved decision-making in business, government, and society. Join us in shaping the future of intelligent, data-informed decisions!

    Contact:
    For inquiries, please contact Dr. Satish Mahadevan Srinivasan at sus64@psu.edu.

     



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    Shuo (Luna) Yang
    Assistant Professor of Business
    The Pennsylvania State University
    King of Prussia PA
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