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SDS 2026 : Statistics and Data Science

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Link: https://sds2026.sis-statistica.it/
 
When Mar 30, 2026 - Apr 1, 2026
Where Caserta, Italy
Submission Deadline Jan 18, 2026
Notification Due Feb 23, 2026
Final Version Due Mar 2, 2026
Categories    statistics   data science
 

Call For Papers

Academics, researchers, PhD candidates, and professionals working in statistics, data science, and their methodological and applied domains are invited to submit contributions to the SIS – Statistics and Data Science Section Meeting: SDS 2026, that will be organized at the University of
Campania “Luigi Vanvitelli” in Caserta, on March 30–31 – April 1, 2026 The interaction between Statistics and Data Science is increasingly central across numerous fields—from machine learning and predictive modelling to the analysis of complex and high-dimensional data; from advanced data visualization techniques to natural language and text analytics. In social sciences, economics, finance, medicine, genomics, natural sciences, and
physics, the synergy between statistics and data science enables the development of more effective tools to describe, interpret, and forecast complex phenomena.
Alongside these opportunities, new challenges arise, such as ensuring transparency, fairness, and interpretability of models. True innovation lies precisely in the ability to combine theoretical rigour with computational power to address data-driven challenges responsibly and creatively across diverse fields. The conference aims to promote interactions and interdisciplinary collaborations by encouraging innovative approaches aligned with the listed topics.



Submission guidelines
Authors wishing to present a contribution are invited to submit a short paper of 4 to 6 pages, including abstract, figures, and references.

The abstract must not exceed 200 words and should not contain references or formulas.
The short paper should describe the methodological or applied problem addressed, the data used, the adopted methodology, and the main results and conclusions, ending with the most relevant bibliographic references.

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