Professor Fernando is actively engaged in pioneering research across a spectrum of advanced fields within artificial intelligence and computational optimization. His primary focus encompasses machine learning (ML) and deep learning (DL), where he is dedicated to advancing intelligent systems by leveraging innovative techniques such as swarm intelligence, evolutionary computing, and neural networks. Prof. Fernando’s expertise extends into the intricate domain of natural language processing (NLP), aiming to enhance language understanding and generation. Furthermore, he makes substantial contributions to multi-objective combinatorial optimization, developing algorithms to tackle complex decision-making challenges. In the context of industry, Prof. Fernando’s research is geared towards practical applications, offering solutions to real-world problems. For potential postgraduate students, joining his research group provides a dynamic and intellectually stimulating environment to explore the forefront of AI, fostering both theoretical understanding and hands-on expertise. Together, the aim is to push the boundaries of AI research and cultivate solutions with tangible impacts on industry and societal advancements. His specific areas of interest are:
- Machine Learning (ML)
- Deep Learning (DL)
- Intelligent Systems
- Swarm Intelligence
- Evolutionary Computing
- Natural Language Processing (NLP)
- Multi-objective Combinatorial Optimization