On-location / Digital Conference

International Conference on Statistical Computing and Data Analytics (ICSCDA-26)

26th - 27th Dec 2026,Milan, Italy

In Association With:


Important Dates


Early Bird Registration

26th Nov 2026

Paper Submission Deadline

1st December 2026

Registration Deadline

11th December 2026

Conference Date

26th - 27th Dec 2026

Conference Updates:

"Stay updated with Science Cite Conference news."

  • Early-Bird Registration Reminder:
    Early-bird registration for the Science Cite Conference in Milan ends soon! Register Now!
  • Certificate of Presentation – Recognizing Your Contribution:
    Receive a Certificate of Presentation to recognize your participation in Milan conference.
  • Peer Review Process:
    The peer review process will begin soon for Milan conference.
  • Networking with Global Experts:
    Join global experts at our conference in Milan.
  • 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 1 — No Poverty
SDG 3 — Good Health and Well-being
SDG 4 — Quality Education
SDG 8 — Decent Work and Economic Growth
SDG 9 — Industry, Innovation and Infrastructure
SDG 11 — Sustainable Cities and Communities
SDG 16 — Peace, Justice and Strong Institutions
SDG 17 — Partnerships for the Goals
Session Tracks
Track 01
Advancements in Statistical Computing

This track focuses on the latest developments in statistical computing techniques and tools. Participants will explore innovative algorithms and software that enhance computational efficiency in statistical analysis.

Track 02
Machine Learning Applications in Statistics

This session will delve into the integration of machine learning methodologies within statistical frameworks. Researchers will present case studies demonstrating the impact of machine learning on statistical inference and prediction.

Track 03
Predictive Analytics in Big Data

This track addresses the challenges and methodologies associated with predictive analytics in large datasets. Presentations will highlight techniques for extracting meaningful insights from big data using statistical models.

Track 04
Data Mining Techniques and Applications

This session will cover various data mining techniques and their applications across different domains. Participants will discuss methodologies for uncovering patterns and relationships in complex datasets.

Track 05
Statistical Software Development

This track focuses on the design and implementation of statistical software tools. Contributions will include discussions on usability, efficiency, and the role of software in advancing statistical research.

Track 06
Algorithm Design for Statistical Modeling

This session will explore novel algorithmic approaches to statistical modeling. Researchers will present their work on algorithms that improve model accuracy and computational performance.

Track 07
Artificial Intelligence in Statistical Analysis

This track examines the intersection of artificial intelligence and statistical analysis. Presentations will highlight how AI techniques can enhance traditional statistical methods and improve decision-making.

Track 08
Applied Statistics in Real-World Scenarios

This session focuses on the application of statistical methods to solve real-world problems. Participants will share case studies that demonstrate the practical utility of statistical techniques in various fields.

Track 09
Statistical Modeling Techniques

This track will cover various statistical modeling techniques and their applications. Researchers will discuss both traditional and contemporary models used for data analysis and interpretation.

Track 10
Data Visualization and Interpretation

This session emphasizes the importance of data visualization in statistical analysis. Participants will explore techniques for effectively communicating statistical findings through visual means.

Track 11
Ethics and Best Practices in Data Analytics

This track addresses ethical considerations and best practices in statistical computing and data analytics. Discussions will focus on responsible data use, transparency, and reproducibility in research.

Indexed / Supported By

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Academic Institutions Whose Scholars Have Contributed

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