Sujan Perera is a Research Staff Member of the Watson for Patient Safety (WPS) team. WPS is focused on developing cognitive technology to monitor the effects of drugs before and after the approval for the prescription. Sujan is responsible for generating novel ideas to understand the patient safety related information from a large variety of data sources by using machine learning and natural language processing technologies.
Sujan earned his PhD from Kno.e.sis research center, Wright State university. His dissertation advisor was Amit Sheth. During his graduate studies, he focused on extracting implicit information from unstructured text. He has published on several international forums, done multiple internships, and earned a patent for his work on identifying implicit connections between biological entities.
Sujan is broadly interested in machine learning, deep learning, natural language processing, knowledge graphs, and semantic technologies. He has served as a program committee member for conferences such as EKAW, ISWC, IJCAI, WWW. He was awarded with the George Thomas post graduate fellowship for the academic year of 2016.