CALL FOR PAPERS
Special Session on
Artificial Intelligence Driven Computational Intelligence: Models, Methods, and Applications
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invites researchers, academicians, scientists, industry experts, and research scholars to submit their original and unpublished research papers for a Special Session on "Artificial Intelligence Driven Computational Intelligence: Models, Methods, and Applications" under the International Conference on Mathematical Sciences and Computational Intelligence (ICMSCI-2026).
This special session focuses on the synergy between Artificial Intelligence and Computational Intelligence, emphasizing advanced models, algorithms, and real-world applications. It aims to bring together researchers and practitioners working on AI-driven computational techniques such as machine learning, deep learning, evolutionary computation, optimization, and hybrid intelligent systems. The session highlights mathematical foundations, algorithmic innovations, and application-oriented solutions addressing complex problems in science, engineering, healthcare, finance, and smart systems. The objective is to foster interdisciplinary discussion on emerging trends, challenges, and future directions in AI-enabled computational intelligence.
The proposed special session strongly aligns with the core themes of ICMSCI-2026 by integrating mathematical sciences with computational intelligence and artificial intelligence. It emphasizes mathematically grounded AI models, intelligent algorithms, and data-driven computational techniques for solving complex real-world problems.
Topics of Interest
Mathematical Foundations of Artificial Intelligence and Computational Intelligence
Machine Learning and Deep Learning Models for Intelligent Systems
Optimization Techniques and Evolutionary Algorithms in AI
Hybrid AI and Computational Intelligence Approaches
Probabilistic Models, Statistical Learning, and Uncertainty Handling
Explainable, Interpretable, and Trustworthy AI Models
Reinforcement Learning and Intelligent Control Systems
AI-Driven Data Analytics and Predictive Modeling
Neural Networks, Graph-Based Models, and Intelligent Computing
Real-World Applications of AI in Science, Engineering, and Healthcare
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.
Special Session Coordinator
Prof. (Dr.) Sudhanshu Maurya
Professor CSE
Manav Rachna International Institute of Research and Studies (Deemed to be University), Faridabad, India
Email ID: dr.smaurya3feb@gmail.com
Phone Number: +91-7717782567
Prof. (Dr.) Abhishek Saxena
Professor CSE
Manav Rachna University, Faridabad, India
Email ID: abhisheksaxena@mru.edu.in
Phone Number: +91-9457580379
We warmly welcome research contributions that blend theoretical insight, methodological rigor, and impactful applications.