Overview

My research activity focuses on developing trustworthy, lightweight, efficient, and generalizable artificial intelligence systems that can operate effectively in complex, dynamic, and resource-constrained environments. My work sits at the intersection of artificial intelligence, machine learning, deep learning, trustworthy AI, and efficient computing, with an emphasis on developing methods that are not only accurate but also robust, adaptable, interpretable, and deployable in real-world settings.

During my research activity in Iran, I investigated the application of machine learning techniques to optimize 5G beam selection for UAV communication, with the aim of improving connectivity, communication efficiency, and network performance in dynamic aerial environments. This provided me with experience in machine learning, 5G wireless communications, UAV networks, optimization, and intelligent communication systems, and strengthened my broader interest in developing efficient and adaptive AI solutions for real-world applications.

During my PhD studies at Universiti Brunei Darussalam earlier research focused on the design and development of lightweight and efficient deep learning frameworks for stress detection, identification, and classification, with an emphasis on developing models that can be effectively deployed beyond controlled laboratory environments. Building on this foundation, my current research interests extend toward the application of different technologies like meta-learning, continual learning, generative AI, algorithmic fairness, Bayesian optimization, reinforcement learning, and robust deep learning in health, agriculture, ecology, and sustainable computing. 

I explore these areas from both theoretical and algorithmic standpoints, with a strong desire to apply them to high-impact domains such as scientific discovery, sustainable agriculture, and sustainable computing. To learn more about our lab's work, see here or take a look at our blog.

Research interests

Computer Vision, Artificial Intelligence, Deep Learning, Digital Health, Smart Agriculture, Sustainable Computing