International Conference on Computational Algorithms for Data-Intensive Science
(I2CADIS-26)

18th October 2026 || Pondicherry - India || Hybrid Mode

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Conference Session Tracks

The International Conference on Computational Algorithms for Data-Intensive Science (I2CADIS), scheduled to be held on 18th October 2026 in Pondicherry, India, features a diverse range of session tracks covering key research areas, emerging trends and interdisciplinary innovations within the field of Computational Science.

Each track offers researchers, academicians, industry professionals and practitioners a platform to present their work, exchange ideas and explore the advancements shaping the future of the domain. Every track is curated to encourage knowledge sharing, collaboration and meaningful discussion.

All Session Tracks
  • Track 01 – Advancements in Computational Algorithms
    This track focuses on the latest developments in computational algorithms that enhance data processing capabilities in scientific research. Contributions should highlight innovative approaches and methodologies that improve algorithm efficiency and effectiveness. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 4 – Quality Education
  • Track 02 – Mathematical Foundations of Data Science
    This session aims to explore the mathematical principles underpinning data science techniques. Papers should discuss theoretical frameworks and their applications in real-world data-intensive scenarios. Aligned SDGs: SDG 4 – Quality Education  |  SDG 7 – Affordable and Clean Energy
  • Track 03 – High-Performance Computing in Scientific Research
    This track emphasizes the role of high-performance computing in accelerating scientific discoveries. Submissions should address computational challenges and solutions in data-intensive environments. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 11 – Sustainable Cities and Communities
  • Track 04 – Machine Learning and Artificial Intelligence Applications
    This session invites papers that investigate the application of machine learning and artificial intelligence in various scientific domains. Contributions should demonstrate how these technologies can enhance data analysis and decision-making processes. Aligned SDGs: SDG 4 – Quality Education  |  SDG 9 – Industry, Innovation and Infrastructure
  • Track 05 – Optimization Algorithms for Big Data
    This track focuses on optimization techniques tailored for big data analytics. Papers should present novel algorithms that improve performance and scalability in data-intensive applications. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 12 – Responsible Consumption and Production
  • Track 06 – Statistical Modeling and Predictive Analytics
    This session aims to showcase advancements in statistical modeling and its role in predictive analytics. Contributions should highlight innovative statistical techniques that enhance forecasting accuracy in complex datasets. Aligned SDGs: SDG 4 – Quality Education  |  SDG 9 – Industry, Innovation and Infrastructure
  • Track 07 – Numerical Methods for Data-Driven Science
    This track explores the application of numerical methods in solving data-driven scientific problems. Papers should discuss the development and implementation of numerical techniques that facilitate data analysis. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 12 – Responsible Consumption and Production
  • Track 08 – Knowledge Discovery in Data-Intensive Environments
    This session focuses on methodologies and technologies for knowledge discovery in large datasets. Contributions should address challenges and solutions in extracting meaningful insights from complex data. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 4 – Quality Education
  • Track 09 – Quantitative Methods in Computational Science
    This track invites discussions on quantitative methods that enhance computational science research. Papers should explore the integration of quantitative techniques with computational algorithms to solve scientific problems. Aligned SDGs: SDG 4 – Quality Education  |  SDG 7 – Affordable and Clean Energy
  • Track 10 – Simulation Techniques in Data Science
    This session emphasizes the role of simulation techniques in data science applications. Contributions should highlight innovative simulation methodologies that support data analysis and interpretation. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 4 – Quality Education
  • Track 11 – Research Applications of Computational Algorithms
    This track showcases real-world applications of computational algorithms in various research fields. Papers should provide case studies demonstrating the impact of these algorithms on scientific advancements. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 11 – Sustainable Cities and Communities
Alignment with the Sustainable Development Goals
Alongside its academic focus, the conference promotes responsible research, ethical practice and knowledge-driven development. Its session tracks collectively contribute to the following United Nations Sustainable Development Goals.
  • SDG 4 SDG 4
    Quality Education
  • SDG 7 SDG 7
    Affordable and Clean Energy
  • SDG 9 SDG 9
    Industry, Innovation and Infrastructure
  • SDG 11 SDG 11
    Sustainable Cities and Communities
  • SDG 12 SDG 12
    Responsible Consumption and Production

Need Assistance?

If you need any clarification on the session tracks or support with your submission, please feel free to reach out to us:

Email: [email protected]

Phone: +91 9677007228