International Conference on Multivariate Probability and Statistical Methods
(ICMPMSM-26)

7th November 2026 || Pune - India || Hybrid Mode

Proudly Organized by INRI

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Conference Session Tracks

The International Conference on Multivariate Probability and Statistical Methods (ICMPMSM), scheduled to be held on 7th November 2026 in Pune, India, features a diverse range of session tracks covering key research areas, emerging trends and interdisciplinary innovations within the field of Probability Theory,Statistics.

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 Multivariate Probability Theory
    This track focuses on recent developments in multivariate probability theory, emphasizing theoretical frameworks and innovative approaches. Contributions that explore the implications of multivariate distributions in various applications are particularly encouraged. Aligned SDGs: SDG 4 – Quality Education  |  SDG 9 – Industry, Innovation and Infrastructure
  • Track 02 – Statistical Methods for High-Dimensional Data
    This session will explore statistical methodologies tailored for high-dimensional datasets, including challenges and solutions in estimation and inference. Topics such as variable selection, regularization techniques, and model evaluation will be discussed. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 11 – Sustainable Cities and Communities
  • Track 03 – Machine Learning Techniques in Statistical Analysis
    This track aims to bridge the gap between machine learning and traditional statistical methods, highlighting how these fields can complement each other. Papers that demonstrate the application of machine learning algorithms in statistical contexts are welcome. Aligned SDGs: SDG 4 – Quality Education  |  SDG 9 – Industry, Innovation and Infrastructure
  • Track 04 – Regression Analysis in Multivariate Contexts
    This session will delve into advanced regression techniques applicable to multivariate data, including generalized linear models and multivariate adaptive regression splines. Contributions that address model diagnostics and validation in complex scenarios are encouraged. Aligned SDGs: SDG 3 – Good Health and Well-being  |  SDG 11 – Sustainable Cities and Communities
  • Track 05 – Clustering and Classification Techniques in Data Science
    This track will cover innovative clustering and classification methods that enhance data interpretation and decision-making. Emphasis will be placed on algorithmic advancements and their practical applications in various domains. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 11 – Sustainable Cities and Communities
  • Track 06 – Dimension Reduction Techniques in Statistical Modeling
    This session will focus on dimension reduction methods, such as Principal Component Analysis and Factor Analysis, that facilitate the simplification of complex datasets. Papers that demonstrate the effectiveness of these techniques in real-world applications are encouraged. Aligned SDGs: SDG 4 – Quality Education  |  SDG 9 – Industry, Innovation and Infrastructure
  • Track 07 – Simulation Techniques in Probability and Statistics
    This track will explore the role of simulation in probability and statistical methods, including Monte Carlo simulations and bootstrapping. Contributions that showcase novel simulation techniques and their applications in empirical research are welcome. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 11 – Sustainable Cities and Communities
  • Track 08 – Big Data Analytics: Challenges and Solutions
    This session will address the challenges posed by big data in statistical analysis and present innovative solutions. Topics may include data management, processing techniques, and the integration of statistical methods with big data technologies. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 11 – Sustainable Cities and Communities
  • Track 09 – Computational Statistics: Methods and Applications
    This track will highlight computational approaches in statistics, focusing on algorithm development and implementation. Papers that discuss the application of computational methods in solving complex statistical problems are particularly encouraged. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 11 – Sustainable Cities and Communities
  • Track 10 – Predictive Analytics in Multivariate Frameworks
    This session will explore the intersection of predictive analytics and multivariate statistical methods, emphasizing model development and validation. Contributions that demonstrate the application of predictive models in various fields are welcome. Aligned SDGs: SDG 4 – Quality Education  |  SDG 11 – Sustainable Cities and Communities
  • Track 11 – Applications of Applied Statistics in Research
    This track will showcase the application of statistical methods in diverse research fields, highlighting case studies and empirical findings. Contributions that illustrate the impact of applied statistics on decision-making and policy formulation are encouraged. Aligned SDGs: SDG 4 – Quality Education  |  SDG 9 – Industry, Innovation and Infrastructure
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 3 SDG 3
    Good Health and Well-being
  • SDG 4 SDG 4
    Quality Education
  • SDG 9 SDG 9
    Industry, Innovation and Infrastructure
  • SDG 11 SDG 11
    Sustainable Cities and Communities

Need Assistance?

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

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