CALL FOR PAPERS

Special Session on

Mathematical Methods and Algorithmic Foundations of Artificial Intelligence and Data Science

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invites researchers, academicians, scientists, industry experts, and research scholars to submit their original and unpublished research papers for a Special Session on "Mathematical Methods and Algorithmic Foundations of Artificial Intelligence and Data Science" under the International Conference on Mathematical Sciences and Computational Intelligence (ICMSCI-2026).

This special session focuses on the mathematical and algorithmic foundations that underpin artificial intelligence, machine learning, and data science. Emphasis is placed on optimization theory, statistical learning, probabilistic modeling, linear algebra, graph theory, and information-theoretic approaches for intelligent systems. The session encourages contributions that integrate rigorous mathematical analysis with computational methodologies, addressing both theoretical developments and application-driven research. The objective is to bridge mathematical sciences and computer science, enabling the design of robust, interpretable, and scalable AI-driven solutions for real-world problems.

The proposed session aligns strongly with the core themes of ICMSCI-2026 by integrating mathematical sciences with computational intelligence. It emphasizes mathematical modeling, algorithm design, and analytical methods that support advances in AI, machine learning, and data-driven intelligence. The session contributes to the conference objectives by promoting interdisciplinary research, theoretical rigor, and practical innovation in intelligent computing, thereby strengthening the synergy between mathematics and computational intelligence.

Topics of Interest

• Optimization techniques for machine learning algorithms

• Statistical learning theory and generalization analysis

• Mathematical foundations of deep learning models

• Probabilistic and Bayesian methods in data science

• Graph theory and network analysis for intelligent systems

• Symmetry, invariance, and group-theoretic approaches in AI

• Explainable and interpretable AI through mathematical models

• Algorithmic complexity and scalability in AI systems

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