Biography

Dr. Morteza Pourreza is a researcher specializing in Natural Language Processing (NLP) and machine learning, with a focus on extracting information from unstructured text. He earned his Ph.D. from Montana State University in 2020 under the supervision of Dr. Indika Kahanda. His research interests encompass applying advanced machine learning techniques, including Transformers, Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), and classic algorithms, to tasks such as named entity recognition, relation extraction, and question answering.

Dr. Pourreza has contributed to several notable publications in the field. For instance, he co-authored “An Ensemble Approach for Automatic Structuring of Radiology Reports,” which presents a method combining Bi-directional LSTMs and sentence encoders to achieve high accuracy in structuring medical texts presented at EMNLP 2021. Additionally, he worked on “Deep Semi-supervised Ensemble Method for Classifying Co-mentions of Human Proteins and Phenotypes,” presented at ISMB 2020, focusing on biomedical text analysis .