Cosmin Adrian Bejan, PhD, is a computer scientist working in a research area that lies at the intersection of biomedical informatics, natural language processing, and machine learning. Currently, he is developing text mining technologies for processing narrative patient reports to identify illness phenotypes and to facilitate clinical and translational studies of large cohorts of critically ill patients. One methodology he recently devised for this purpose is based on statistical hypothesis testing to extract the most relevant clinical information corresponding to the phenotype of interest. For this study, he also developed a state-of-the-art assertion classifier for assigning assertion values to the concepts associated with a specific phenotype.
In his previous research, Dr. Bejan designed and implemented machine learning systems for automatic extraction of structured information from open domain text documents. In particular, his focus was on discovering the events encoded in documents, the entities participating in a specific situation, and the interactions that happen between events. One significant part of his previous work is the development of a new class of fully generative, nonparametric Bayesian models for unsupervised event coreference resolution.
For more information about Dr. Bejan’s research, please visit his website.