Travis Goodwin

Travis Goodwin, PhD

Computational Health Research Branch
Postdoctoral Research Fellow

Contact Information
Building 38A - Lister Hill Center, 10N1003M

Expertise and Research Interests:

Travis R. Goodwin, PhD, joined the Communications Engineering Branch at the Lister Hill National Center for Biomedical Communications (LHNCBC) as a Postdoctoral Research Fellow in June 2018. Dr. Goodwin completed his PhD in Computer Science at the University of Texas at Dallas (UTD) in May 2018. His PhD research focused on Bayesian and (deep) neural methods for medical question answering, clinical decision support, and medical information retrieval. He is currently working on applying deep learning techniques for predictive modeling and laboratory test ordering under the mentorship of Dr. Dina Demner-Fushman.

Professional Activities:

Dr. Goodwin joined the Student Editorial Board (SEB) of the Journal of the American Medical Informatics Association (JAMIA) in 2018, and is a member of the American Medical Informatics Association (AMIA), the Association for Computational Linguistics (ACL), and the Association for Computing Machinery’s (ACM) Special Interest Group on Information Retrieval (SIGIR).

Honors and Awards:

Dr. Goodwin was selected into the NIH Independent Research Scholar Program in 2019. Dr. Goodwin’s work on early prediction of hospital acquired pneumonia won a Fellows Award for Research Excellence (FARE) award in the 2020 competition. His doctoral dissertation entitled “Medical Question Answering and Patient Cohort Retrieval” won first prize in the 2019 AMIA Doctoral Dissertation Awards.


Moldwin A, Demner-Fushman D, Goodwin TR. Empirical Findings on the Role of Structured Data, Unstructured Data, and their Combination for Automatic Clinical Phenotyping. AMIA Summit 2021.

Goodwin T, Demner-Fushman D. A customizable deep learning model for nosocomial risk prediction from critical care notes with indirect supervision. Journal of the American Medical Informatics Association, 2020: 27 (4), 567-576.

Goodwin T, Demner-Fushman D. Deep Learning from Incomplete Data: Detecting Imminent Risk of Hospital-acquired Pneumonia in ICU Patients. Proceedings of the AMIA 2019 Annual Symposium, Washington, DC, USA, November 17-20, 2019.

Goodwin T, Demner-Fushman D, Fung K, Do P. Overview of the TAC 2019 Track on Drug-Drug Interaction Extraction from Drug Label. Proceedings of the Text Analysis Conference (TAC) 20 19, Gathersburg, MD, USA, November 12-13, 2019.