معرفی
Hani Hagras is a Professor in the School of Computer Science and Electronic Engineering at the University of Essex, UK, where he leads pioneering research in type-2 fuzzy logic systems and explainable artificial intelligence (XAI). His work bridges theoretical advances with real-world applications in smart infrastructure, healthcare, telecommunications, and ambient intelligence.
His research interests include explainable AI, type-2 fuzzy logic, computational intelligence, machine learning, human-computer interaction, and intelligent systems. He investigates how fuzzy systems can enhance the transparency, robustness, and adaptability of AI models, particularly in uncertain and dynamic environments. His recent work explores applications in genomics, predictive maintenance, and smart grid optimization.
The publication trends show a strong focus on integrating fuzzy logic with deep learning and optimization techniques to create interpretable models. His work frequently appears in top-tier journals such as IEEE Transactions on Fuzzy Systems, IEEE Transactions on Artificial Intelligence, and Neurocomputing. He emphasizes real-world applicability, often collaborating with industry partners like BT.
- ORCID: 0000-0002-2818-5292
He has advised numerous PhD and Master’s students, including Mehrin Kiani, Ashish Bhatia, and Hugo Leon-Garza, many of whose research projects focus on workforce optimization, healthcare AI, and intelligent systems. His research has been supported by major grants, particularly in smart environments and telecommunications.
Hani Hagras is actively involved in leading research labs and teams at the University of Essex, including work on augmented reality for field service support, georeferenced data visualization, and ambient-assisted living systems. His team develops fuzzy logic frameworks for real-time decision-making in complex environments.
حوزههای پژوهشی
