Principle Investigator: Thanh Thieu, Ph.D.

Dr. Thieu received his Ph.D. in Computer Science from the University of Missouri-Columbia. Prior to Moffitt, he was an Assistant Professor in Computer Science Department at the Oklahoma State University, and further was a postdoc at the U.S. National Institutes of Health. He has been pursuing research in natural language processing, machine learning, and artificial intelligence with application in healthcare and education. Dr. Thieu has taught and mentored students and juniors at University of Missouri, NIH Clinical Center, ACT Inc., Oklahoma State University, and Moffitt Cancer Center. Having worked in academia, government, and industry, Dr. Thieu has developed capability to mentor and collaborate across educational backgrounds, ethnicities, genders, and origins.

Applied Research Scientist: Zitu Md Muntasir, Ph.D.

Born and raised in Dhaka, Bangladesh, Muntasir pursued a B.Sc. in Computer Science at the Chittagong University of Engineering and Technology. During his undergrad years, he sparked an interest in Biomedical Science. This passion led him to become a graduate student in Bioinformatics at Indiana University, where he dedicated two years to the Center for Computational Biology and Bioinformatics. He later joined The Ohio State University and obtained his Ph.D. in Biomedical Informatics. His Ph.D. thesis focused on identifying adverse drug events from clinical narratives of electronic medical records using natural language processing and machine learning. Muntasir started working with Dr. Rollison and Dr. Thieu’s team at Moffitt Cancer Center in 2023 as an Applied Research Scientist. He became part of many projects where he used computer tools, like natural language processing and machine learning, on health data with the aim to find ways to beat cancer. In his free time, Muntasir loves traveling, cooking, and spending time with his family.

Applied Research Scientist: Shohreh Haddadan, Ph.D.

Shohreh earned her master's degree in computational linguistics from Sharif University of Technology before relocating to Luxembourg in 2017 to pursue her Ph.D. studies. She successfully obtained her doctoral degree in Computer Science from the University of Luxembourg in 2022.

Her master’s project focused on abstractive summarization in Persian language utilizing graph-based AMRs (Abstract Meaning Representation graphs).

For her doctoral research she delved into argument mining, utilizing Natural Language Processing methods to extract argument structures from text and employing them to classify fallacious arguments. She defended her doctoral thesis titled “Argument mining in political debates and applications” in April 2022.

Transitioning seamlessly into the role of a data scientist, she participated in research endeavors as part of an industrial project as a collaboration with Zortify S.A. research lab and the Interdisciplinary Centre for Security, Reliability, and Trust, focusing on the adaptation of Large Language Models in domain-specific and low-resource settings.

In addition to her academic achievements, she has gained 5 years of software programming experience in C++ and C# working in an AI-based company in Tehran from 2012-2017.

Shohreh's research interests span a wide spectrum, with a particular emphasis on argument mining and abstractive summarization.

Ph.D. Student: Thanh Duong

Thanh is a Ph.D. student in Computer Science at Oklahoma State University and will transfer to the University of South Florida under advisor of Dr. Licato and Dr. Thieu. His research focuses on NLP algorithm, lexical complexity, and language generation. He is interested in applying NLP algorithm to process free text clinical notes in electronic health records and free text scientific reports in medical literature. Thanh aims to develop a data augmentation generation method for expanding dataset size of clinical notes that improve training process of language model.

Ph.D. Student: Tuan-Dung Le

Tuan Dung is a PhD student in Computer Science at the University of South Florida. He received his master’s degree in Information Systems from the Hanoi University of Science and Technology in Vietnam and worked as AI engineer at FPT.AI for 2 years. Before joining Moffitt Cancer Center as research trainee, he worked under supervision of Dr. Thieu for a year. He has built a host-pathogen interactions database from scientific literature to help the biomedical research community in the field of infectious diseases. He also developed a Natural Language Processing system that can effectively extract patient's history information from clinical unstructured text to benefit the medical billing process.

Undergraduate Student: Long Hung Tran

Hung is currently an undergraduate student at the University of South Florida and is working at Moffitt as a research trainee under the supervision of Dr. Thieu. Hung has started learning and working in the field of Machine Learning and Deep Learning, specifically Natural Language Processing, since high school. Being the youngest member in the team, Hung continues to gain experience and expand his knowledge in Natural Language Processing under the supervision of Dr. Thieu. He is committed to making an impact in the Natural Language Processing and is eager to contribute to the development of cutting-edge AI technologies.

Undergraduate Student: Huu Dang Pham

Dang Pham is currently a sophomore pursuing a Computer Science major at University of South Florida. Alongside his studies, Dang actively contributes to his lab's research as a web developer. He takes charge of creating and maintaining the lab's website, integrating various AI applications and transforming lab findings into user-friendly websites. Dang leverages his expertise in managing lab services through AWS (Amazon Web Services), ensuring efficient operations. Despite his relatively young position within the lab, Dang continues to expand his knowledge in cutting-edge AI technologies and is dedicated to making a significant impact in the field. His enthusiasm drives him to contribute to the development of advanced AI applications and push the boundaries of innovation.