Mohammad Tariqul Islam

Mohammad Tariqul Islam’s research is focused on employing AI to develop next-generation biomedical applications, including nanotechnologies. Specifically, Tariq specializes in unsupervised machine learning, a field that looks for patterns in unlabeled data. In his doctoral research, he developed a new approach for analyzing chest X-rays that successfully distinguishes Covid-19 patients from healthy patients and differentiates between two distinct types of Covid response. Additionally, he developed unsupervised methods for curating large radiological datasets. As an MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellow, he aims to create innovative algorithms specifically tailored for nano-electronic and bio-hybrid systems. To accomplish this, he will develop algorithms to identify related groups within data, with a particular focus on neighbor relations and topology-preserving approaches. Tariq’s work holds exciting potential to bridge the field of AI with next-generation nanodevices and improve diagnosis, treatment, and understanding of human disease.