Dr. Hira Zaheer's research is centered on the development and application of Soft Computing techniques to solve complex, nonlinear, and multi-objective problems in various domains. Her doctoral research at IIT Roorkee focused on enhancing the efficiency of Differential Evolution (DE) and other evolutionary algorithms by introducing adaptive mutation strategies and hybrid optimization approaches. She has extensively worked on improving the convergence speed and robustness of metaheuristic algorithms, particularly in high-dimensional optimization tasks.

Her research integrates Artificial Intelligence (AI) and Machine Learning (ML) with mathematical modeling to provide intelligent solutions to real-world problems. She is particularly interested in applying fuzzy logic, neural networks, evolutionary computation, and hybrid soft computing systems to areas such as decision support systems, predictive modeling, classification, and control systems.
Dr. Zaheer has published her work in peer-reviewed journals and presented at reputed international and national conferences. Her research contributions aim to bridge the gap between theoretical development and practical implementation of soft computing methodologies. She also actively collaborates with researchers and mentors students in implementing ML and AI-based projects, including predictive analytics, engineering system optimization, and data-driven decision-making models.

She remains engaged in interdisciplinary research that connects mathematics with computer science, engineering, and data science, and is currently expanding her focus toward explainable AI and interpretable machine learning models to enhance the transparency of intelligent systems. Her long-term goal is to contribute to socially impactful, computationally efficient, and ethically sound AI solutions.