Topics of Interest
Topics of interest include but not limited to the following:
Track - 1: Artificial Intelligence and Applications
- Deep Learning Architectures for Vision and Language
- Generative Models (GANs, VAEs, Diffusion)
- Reinforcement Learning and Intelligent Control
- Natural Language Processing and Large Language Models
- Computer Vision and Image Understanding
- AI for Robotics and Autonomous Systems
- Explainable and Trustworthy AI
- Federated and Edge AI Systems
- Optimization for Machine Learning (Convex and Nonconvex)
- Probabilistic Modeling and Bayesian Inference
- Graph Neural Networks and Representation Learning
- Time-Series Forecasting and Sequential Modeling
- Multi-Objective and Evolutionary Optimization
- AI for Healthcare Imaging and Diagnostics
- Data Augmentation and Synthetic Data Generation
Track-2: Mathematical Modeling, Optimization, and Intelligent Systems
- Mathematical Modeling of Complex and Adaptive Systems
- Optimization Theory and Algorithms for Large-Scale Systems
- Intelligent Control and Decision-Making Systems
- Stochastic Modeling and Uncertainty Quantification
- Simulation-Based Modeling and Digital Twins
- Hybrid Mathematical–Intelligent Frameworks for Engineering and Health Applications
- Dynamical Systems Theory and Nonlinear System Analysis
- Multi-Objective and Evolutionary Optimization Techniques
- Optimal Control and Reinforcement-Inspired Control Systems
- Robust and Resilient System Design and Analysis
- Graph-Theoretic Models and Network Optimization
- Mathematical Foundations of Intelligent Cyber-Physical Systems
- Model-Based Systems Engineering and Validation
- Sensitivity Analysis and Parameter Estimation in Mathematical Models
- Computational Optimization for Energy, Environment, and Infrastructure Systems
- Physics-Informed and Constraint-Aware Mathematical Models
