Muhammad Imran Khan is a Ph.D. student at the Nara Institute of Science and Technology (NAIST), Japan, and a visiting Erasmus scholar at the University of Trento. His research focuses on applying AI models to healthcare data, particularly for antimicrobial resistance (AMR) prediction using electronic health records.
He holds a Master of Engineering in ICT from the Bangladesh University of Engineering and Technology (BUET) and a Master’s degree in Applied Statistics and Data Science from Jahangirnagar University. He also earned a Bachelor’s degree in Computer Science from North South University, Bangladesh.
Before starting his Ph.D., he accumulated 20 years of professional experience working with international donor agencies in monitoring, evaluation, and learning (MEL), with a strong emphasis on data systems, analytics, and GIS.
During his stay at the lab, he is working on the KNApSAcK database, a comprehensive resource of species–metabolite relationships, with the goal of applying the lab’s knowledge graph methodologies to this dataset. He aims to develop an advanced GPT-based system enriched with structured knowledge to support prediction, inference, and natural language question answering over biochemical data.
His research interests lie at the intersection of artificial intelligence, health informatics, and knowledge representation, with a focus on integrating knowledge graphs and large language models.