CALL FOR PAPERS

Special Session on

Statistical Quality Control and Data Science: Integrating Classical Methods with Modern Analytics

Under the International Conference on Mathematical Sciences and Computational Intelligence  (ICMSCI-2026)

February 20–22, 2026

The Department of Mathematics, P.G.D.A.V. College, University of Delhi, in collaboration with Faculty of Mathematical Sciences, University of Delhi, IIT Mandi and NIT Uttarakhand, cordially invites researchers, academicians, scientists, industry experts, and research scholars to submit their original and unpublished research papers for a Special Session on "Statistical Quality Control and Data Science: Integrating Classical Methods with Modern Analytics" under the International Conference on Mathematical Sciences and Computational Intelligence (ICMSCI-2026).

Statistical Quality Control (SQC) has long been the backbone of process improvement and quality assurance in manufacturing and service sectors. With the rapid growth of data science, machine learning, and big data analytics, traditional SQC tools are being enhanced and redefined to handle complex, high-dimensional, and real-time data. This special session aims to bridge classical SQC techniques with modern data science approaches to address contemporary quality and decision-making challenges.

The proposed session aligns with ICMSCI-2026 by emphasizing the application of mathematical and computational frameworks to real-world quality and process improvement challenges. Topics such as multivariate process monitoring, predictive quality analytics, anomaly detection, and real-time statistical control directly involve computational intelligence and advanced mathematical techniques, which are central to the conference themes.

Topics of Interest

• Classical and Advanced Control Charts (Shewhart, CUSUM,).

• Machine Learning Methods for Process Monitoring and Fault Detection

• Statistical Quality Control in Industry 4.0 and Smart Manufacturing.

• Quality Improvement in Service and Healthcare Systems using Data Science .

• Bayesian Methods in Statistical Quality Control

Submission Guidelines

• Manuscript must follow the conference template. All submissions will undergo peer review.

• Maximum length: 9–16 pages including references.

• Accepted papers will be presented and included in the proceedings/special issue (details to follow).

Presentation Mode

Hybrid (Offline + Online). Selected papers will be presented through oral or poster sessions.

Important Dates

• Last date for abstract submission: January 15, 2026  , 👍Extended till: January 31, 2026

• Abstract acceptance notification: January 20, 2026, 👍 Extended till: February 05, 2026

• Last date of Registration: February 10, 2026

• Full-Paper Submission: March 10, 2026

Who Should Submit?

Faculty members, researchers, post-doctoral fellows, PhD scholars, postgraduate students, statisticians, engineers, data scientists, and industry professionals.

Submission Email : Authors must submit their abstracts/papers through the following link:

👉Click Here for Abstract Template

👉 Click Here For Abstract Submission

Kindly visit the registration page to register for the conference.

👉 Click Here to Visit Registration Page