Yang Fann, Ph.D.

Dr. Fann joined NINDS in 2002 as the Director of the Intramural IT and Bioinformatics Program overseeing the information technology support services and infrastructures as well as developing biomedical informatics research services including many database tools and clinical applications to assist investigators with their research. In addition to his role at NINDS, he served as a principal investigator on the Informatics Core of Center for Neuroscience and Regenerative Medicine working on building the informatics infrastructure for the National Traumatic Brian Injury (TBI) Study, a collaborative research program of the DoD and NIH from 2009 to2023. 

Among his notable achievements is the creation of the Purchasing On-line Tracking System (POTS). This innovative system streamlined scientific procurement administration and garnered recognition within the NIH community. Dr. Fann’s groundbreaking work earned him the first-ever HHS Innovates Award presented by the Secretary of Health and Human Services in 2010.  Collaboration is at the heart of Dr. Fann’s work. He co-led an international team with Dr. Matthew McAuliffe at the Center for Information Technology (CIT). Together, they developed the Biomedical Research Informatics Computing System (BRICS)—a reusable and sustainable integrated biomedical informatics platform. BRICS supports and catalyzes biomedical research and data sharing. Notably, this system has received numerous industrial and government awards.

In addition to his NINDS responsibilities, Dr. Fann actively participates in various NIH advisory and steering committees. These include the NIH IT Budget Advisory Committee (ITBAC), the Clinical Center IT Advisory Committee, the NIH IT Management Committee, the NIH High Performance Computing Working Group, the NIH STRIDES Enterprise Cloud Advisory Committee, and the NIH Biomedical Informatics Coordination (BMIC) Working Group. He also co-chairs the Biomedical Translational Research Information System (BTRIS) Steering Committee.

Recently Dr. Fann has recently assumed the role of Director of Clinical Informatics for the National Institutes of Health’s Intramural Research Program (IRP). In this capacity, he is responsible for addressing a wide range of clinical informatics challenges related to the clinical research program within the NIH IRP. His strategic vision includes assessing and developing new approaches to clinical informatics within the IRP. His focus is on providing informatics solutions that streamline collaboration, simplify compliance, and enable data sharing. To achieve this, he aims to implement a data ecosystem with interoperability across relevant IRP-wide systems, including e-IRB, CRIS, and IC clinical information systems.

Beyond his administrative responsibilities, Dr. Fann has made significant contributions to the scientific community. He has served on several journals’ editorial boards and recently acted as a scientific judge for the COVID-19 Open Research Dataset Challenge (CORD-19)—an AI challenge involving collaboration between AI2, CZI, MSR, Georgetown, NIH, and The White House.

His dedication and expertise have earned him numerous accolades, including NINDS and NIH Director’s Awards. Dr. Fann’s current research interests span computational biology, bioinformatics, and clinical research informatics. He also explores the application of information technology, including machine learning and artificial intelligence, to advance translational biomedical research.

Selected Recent publications:

1. Shih-Sheng Chang, Ching-Ting Lin, Wei-Chun Wang, Kai-Cheng Hsu, Ya-Lun Wu, Chia-Hao Liu, Yang C. Fann*; “Optimizing Ensemble U-Net Architectures for Robust Coronary Vessel Segmentation in Angiographic Images”; Scientific Reports, 14, 6640 (2024). https://doi.org/10.1038/s41598-024-57198-5
2. Ching-Heng Lin, Yi-An Chen, Jiann-Shing Jeng, Yu Sun, Cheng-Yu Wei, Po-Yen Yeh, Wei-Lun Chang, Yang C. Fann,*, Kai-Cheng Hsu*, Jiunn-Tay Lee, and Taiwan Stroke Registry Investigators; “Predicting Ischemic Stroke Patients’ Prognosis Changes using Machine Learning in a Nationwide Stroke Registry”; Med Biol Eng Comput (2024). https://doi.org/10.1007/s11517-024-03073-4
3. Chen KG, Johnson KR, Park K, Maric D, Yang F, Liu WF, Fann YC, Mallon BS, Robey PG; “Resistance to Naïve and Formative Pluripotency Conversion in RSeT Human Embryonic Stem Cells”; bioRxiv, 2024 Feb 17:2024.02.16.580778. doi: 10.1101/2024.02.16.580778, PMID: 38410444
4. Marco Egle, Wei-Chun Wang, Yang C Fann*, Michelle C Johansen, Jiunn-Tay Lee, Chung-Hsin Yehe, Chih- Hao Jason Lin, Jiann-Shing Jeng, Yu Sun, Li-Ming Lien , Jiunn-Tay Lee, Taiwan Stroke Registry Investigators, Rebecca F Gottesman*; “Sex Differences in the Role of Multimorbidity on Post-Stroke Disability: The Taiwan Stroke Registry”; Neurology, 2024;102:e209140. doi:10.1212/WNL.0000000000209140
5. Yen-Jung Chiu, Chao-Chun Chuang, Yu-Tai Wang, Lin-Chi Yeh, Romel Edwardo Rudon, Kuan-Wei Lin, Wei-Jong Yang, Yang C Fann, Pau-Choo Chung; “FLAg: An automated client-independent federated learning system on HPC for digital pathology slice training”; IEEE Artificial Intelligence, 2023, 314-315
6. Hendrick Gao-Min Lim, Yang C Fann, Yuan-Chii Gladys Lee; “COWID: An Efficient Cloud-Based Genomics Workflow for Scalable Identification of SARS-CoV-2”, Briefings in Bioinformatics, 2023, 1-12, https://doi.org/10.1093/bib/bbad280
7. Yuan-Chii Lee, Fang-Ning Chou, Szu-Yu Tung, Hsiu-Chu Chou, Tsui-Ling Ko, Yang C. Fann, Shu-Hui Juan *; “Tumoricidal activity of simvastatin in synergy with RhoA inactivation in antimigration of clear cell renal cell carcinoma cells”, Int J Mol Sci. 2023 Jun 4;24(11):9738. doi: 10.3390/ijms24119738. PMID: 37298689; PMCID: PMC10253741.
8. Ching-Heng Lin, Kai-Cheng Hsu, Chih-Kuang Liang, Tsong-Hai Lee, Ching-Sen Shih. and Yang C. Fann*; ” Accurately Identifying Cerebroarterial Stenosis from Angiography Reports Using Natural Language Processing Approaches”; Artificial Intelligence in Diagnostics 2022, 12, p1882. https://doi.org/10.3390/diagnostics12081882
9. Hendrick Gao-Min Lim, Shih-Hsin Hsiao, Yang C. Fann and Yuan-Chii Gladys Lee; “Robust Mutation Profiling of SARS-CoV-2 Variants from Multiple Raw Illumina Sequencing Data with Cloud Workflow”; Genes 2022, 13(4), 686; https://doi.org/10.3390/genes13040686
10. Hui-Ju Chang; Mei-Yu Lai; Chen-Hsin Chen; Yang C. Fann, Ueng-Cheng Yang “High BRCA1 gene expression increases the risk of early distant metastasis in ER+ breast cancers”, Scientific Reports, 12, 77 (2022). https://doi.org/10.1038/s41598-021-03471-w
11. Yang, L.-Y.; Tsai, M.-Y.; Juan, S.-H.; Chang, S.-F.; Yu, C.-T.R.; Lin, J.-C.; Johnson, K.R.; Lim, H.G.-M.; Fann, Y.C.; Lee, Y.-C.G. “Exerting the Appropriate Application of Methylprednisolone in Acute Spinal Cord Injury Based on Time Course Transcriptomics Analysis”; Int. J. Mol. Sci. 2021, 22, 13024. https://doi.org/10.3390/ijms222313024
12. Ching-Heng Lin, Kai-Cheng Hsu, Chih-Kuang Liang, Tsong-Hai Lee, Chia-Wei Liou, Jiann-Der Lee, Tsung-I Peng, Ching-Sen Shih, Yang C. Fann*, “A disease-specific language representation model for cerebrovascular disease research”, Comp Methods and Prog in Biomed, 211, 2021, p.106446, https://doi.org/10.1016/j.cmpb.2021.106446.
13. Kory R. Johnson, Barbara S. Mallon, Yang C. Fann, and Kevin G. Chen; “Multivariate Meta-Analysis Reveals Global Transcriptomic Signatures Underlying Distinct Human Naive-like Pluripotent States”, PLOS One, 16(5): e0251461, 2021. https://doi.org/10.1371/journal.pone.0251461.
14. Hsu KC, Lin CH, Johnson KR, Fann YC*, Hsu CY, Tsai CH, Chen PL, Chang WL, Yeh PY, Wei CY, Taiwan Stroke Registry Investigators; “Comparison of outcome prediction models post-stroke for a population-based registry with clinical variables collected at admission vs. discharge”. Vessel Plus 2021;5:2. http://dx.doi.org/10.20517/2574-1209.2020.45.
15. Ching-Heng Lin, Kai-Cheng Hsu, Kory R. Johnson, Yang C. Fann*, Chon-Haw Tsai, Yu Sun, Li-Ming Lien, Wei-Lun Chang, Po-Lin Chen, Cheng-Li Lin, Chung Y. Hsu, Taiwan Stroke Registry Investigators; “Evaluation of machine learning methods to stroke outcome prediction using a nationwide disease registry”, Computer Methods and Programs in Biomedicine, 2020 Jul;190:105381, https://doi.org/10.1016/j.cmpb.2020.105381