On-location / Digital Conference

International Conference on Computational Statistics and Numerical Methods (ICCSNM-27)

22nd - 23rd Mar 2027,Naples, Italy

In Association With:


Important Dates


Early Bird Registration

20th Feb 2027

Paper Submission Deadline

25th February 2027

Registration Deadline

7th March 2027

Conference Date

22nd - 23rd Mar 2027

Conference Updates:

"Stay updated with Science Cite Conference news."

  • Early-Bird Registration Reminder:
    Early-bird registration for the Science Cite Conference in Naples ends soon! Register Now!
  • Certificate of Presentation – Recognizing Your Contribution:
    Receive a Certificate of Presentation to recognize your participation in Naples conference.
  • Peer Review Process:
    The peer review process will begin soon for Naples conference.
  • Networking with Global Experts:
    Join global experts at our conference in Naples.
  • Opportunity for Scopus-Indexed Journal Publication:
    Your research could be published in a Scopus-Indexed Journal. Submit Your Abstract
  • SDG-Inspired Conference Focus:
    Present your work aligned with Sustainable Development Goals.

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 4 — Quality Education
SDG 9 — Industry, Innovation and Infrastructure
SDG 11 — Sustainable Cities and Communities
SDG 12 — Responsible Consumption and Production
Session Tracks
Track 01
Advancements in Computational Statistics

This track focuses on the latest methodologies and techniques in computational statistics. Participants will explore innovative algorithms and their applications in various statistical problems.

Track 02
Machine Learning Techniques in Data Science

This session will delve into the integration of machine learning methods within the realm of data science. Emphasis will be placed on practical applications and theoretical foundations.

Track 03
Numerical Methods for Optimization Problems

This track addresses the development and application of numerical methods for solving optimization challenges. Discussions will include both theoretical insights and computational implementations.

Track 04
Statistical Computing and Software Development

Participants will examine the role of statistical computing in modern research, focusing on software tools and programming techniques. This track encourages the sharing of best practices and innovative solutions.

Track 05
Big Data Analytics and Statistical Techniques

This session will explore the intersection of big data and statistical methodologies. Topics will include data management, analysis techniques, and the implications for decision-making.

Track 06
Regression and Classification Models

This track will cover advanced regression and classification techniques used in statistical modeling. Participants will discuss model selection, validation, and real-world applications.

Track 07
Simulation Methods in Statistical Analysis

This session focuses on the use of simulation techniques for statistical inference and model evaluation. Participants will share insights on Monte Carlo methods and their applications.

Track 08
Forecasting Methods and Applications

This track will explore various forecasting techniques and their applications across different domains. Emphasis will be placed on accuracy, reliability, and practical implementation.

Track 09
Quantitative Methods in Applied Mathematics

Participants will investigate the role of quantitative methods in solving real-world problems through applied mathematics. This track encourages interdisciplinary approaches and collaborations.

Track 10
Artificial Intelligence in Statistical Modeling

This session will examine the integration of artificial intelligence techniques in statistical modeling frameworks. Discussions will focus on enhancing model performance and interpretability.

Track 11
Computational Models in Research Applications

This track will highlight the development and application of computational models in various research fields. Participants will discuss case studies and the impact of these models on scientific discovery.

Indexed / Supported By

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Academic Institutions Whose Scholars Have Contributed

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