Erich Senin Huang | Scholars@Duke

Erich Senin Huang
Assistant Professor in Biostatistics and Bioinformatics

Chief Data Officer for Quality, Duke Health
Director of Duke Forge
Director of Duke Crucible
Assistant Dean for Biomedical Informatics

Dr. Huang’s research interests span applied machine learning, research provenance and data infrastructure. Projects include building data provenance tools funded by the NIH’s Big Data to Knowledge program, regulatory science funded by the Burroughs Wellcome Foundation. Applied machine learning applications include “Deep Care Management” a highly interdisciplinary project with Duke Connected Care, Duke’s Accountable Care Organization, that integrates claims and EHR data for predicting unplanned admissions and risk stratifying patients for case management; CALYPSO, a collaboration with the Department of Surgery for utilizing machine learning to predict surgical complications. My team is also building the data platform for the Department of Surgery's "1000 Patients Project" an intensive biospecimen and biomarker study based around patients undergoing the controlled injury of surgery.

As Director of Duke Forge, Dr. Huang is working to build a data science culture and infrastructure across Duke University that focuses on actionable health data science. The Forge emphasizes scientific rigor, awareness that technology does not supersede clinicians’ responsibilities and human relationship with their patients, and the role of data science in society.

Current Appointments & Affiliations

Assistant Professor in Biostatistics and Bioinformatics, Biostatistics & Bioinformatics, Basic Science Departments 2014
Assistant Dean, Biomedical Informatics, Biostatistics & Bioinformatics, Basic Science Departments 2016
Co-Director, Duke Forge, Biostatistics & Bioinformatics, Basic Science Departments 2017
Assistant Professor in Surgery, Surgery, Clinical Science Departments 2014
Core Faculty in Innovation & Entrepreneurship, Duke Innovation & Entrepreneurship, Initiatives 2018

Contact Information

2424 Erwin Road, 9022 Hock Plaza, Durham, NC 27705
Duke Box 2721, Durham, NC 27710
erich.huang@duke.edu (919) 668-2814
ORCID profile

Background
Education, Training, & Certifications
- M.D., Duke University 2003
- Ph.D., Duke University 2002
Duke Appointment History
- Adjunct Assistant Professor in the Department of Surgery, Surgical Oncology, Surgery 2012 - 2013
- Assistant Professor of Surgery, Surgical Oncology, Surgery 2011 - 2012
- Assistant Professor of Surgery, Surgery, Clinical Science Departments 2008 - 2010
Leadership & Clinical Positions at Duke
- Chief Data Officer for Quality, Duke Health
  Director of Duke Forge, Duke University School of Medicine
  Director of Duke Crucible, Duke University School of Medicine
Recognition
In the News
- SEP 28, 2018
  
  +DataScience Wants to Put the Power of Machine Learning in Everyone’s Hands
- NOV 9, 2017 Duke Research Blog
  
  Opportunities at the Intersection of Data Technology and Healthcare
- MAR 8, 2016 Duke Translational Medicine Institute / DukeCTSA
  
  CTSA Profile: Erich Huang - Putting Big Data Ideas Into Action
Awards & Honors
- IBM Faculty Award. IBM. 2019
- IBM Faculty Award. IBM. 2018
- Innovations in Regulatory Science. Burroughs Wellcome Fund. June 2015
- Translational Science Award. Sidney Kimmel Cancer Research Foundation. 2009
Expertise
Global Scholarship
- Research
  - Taiwan (Country)
Research
Selected Grants
- Medical Scientist Training Program awarded by National Institutes of Health 1997 - 2022
- Postdoctoral Training in Genomic Medicine Research awarded by National Institutes of Health 2017 - 2022
- Bridging the Gap to Enhance Clinical Research Program (BIGGER) awarded by National Institutes of Health 2016 - 2021
- Infrastructure for Research Provenance & Reproducibility to Support Auditable Regulatory Scientic Workflows awarded by Burroughs Wellcome Fund 2015 - 2021
- Bioinformatics and Computational Biology Training Program awarded by National Institutes of Health 2005 - 2020
- Flexible & Executable Provenance in Data-Intensive Biomedical Research: A Flexible Research Data Service awarded by National Institutes of Health 2015 - 2020
- SC2i 2014 - 2020
- Prototype Development of CANARIUS - a Flexible, Dynamic, Scaleable, and Low-cost Platform for Surveiling Population Health 2019 - 2020
- A Dialog about AI Safety and Transparency in Health Care 2018 - 2020
- Machine Learning Platform for Surgical Risk Prediction and Modification 2017 - 2018
- Duke/NIDDK Functional Genomics Center awarded by National Institutes of Health 2000 - 2003
External Relationships
- MedBlue Data
- Stratus Medicine
- kelaHealth
Publications & Artistic Works
Selected Publications
- Academic Articles
  - Cobb, Adrienne N., Andrew J. Benjamin, Erich S. Huang, and Paul C. Kuo. “Big data: More than big data sets.” Surgery 164, no. 4 (October 2018): 640–42. https://doi.org/10.1016/j.surg.2018.06.022.
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  - Poore, Gregory D., Emily R. Ko, Ashlee Valente, Ricardo Henao, Kelsey Sumner, Christopher Hong, Thomas W. Burke, et al. “A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies.” Front Microbiol 9 (2018): 2957. https://doi.org/10.3389/fmicb.2018.02957.
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  - Cheng, Skye H., Chen-Fang Horng, Tzu-Ting Huang, Erich S. Huang, Mei-Hua Tsou, Li-Sun Shi, Ben-Long Yu, Chii-Ming Chen, and Andrew T. Huang. “An Eighteen-Gene Classifier Predicts Locoregional Recurrence in Post-Mastectomy Breast Cancer Patients.” Ebiomedicine 5 (March 2016): 74–81. https://doi.org/10.1016/j.ebiom.2016.02.022.
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  - Guinney, Justin, Charles Ferté, Jonathan Dry, Robert McEwen, Gilles Manceau, K. J. Kao, Kai-Ming Chang, et al. “Modeling RAS phenotype in colorectal cancer uncovers novel molecular traits of RAS dependency and improves prediction of response to targeted agents in patients.” Clin Cancer Res 20, no. 1 (January 1, 2014): 265–72. https://doi.org/10.1158/1078-0432.CCR-13-1943.
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  - Ferté, Charles, Andrew D. Trister, Erich Huang, Brian M. Bot, Justin Guinney, Frederic Commo, Solveig Sieberts, et al. “Impact of bioinformatic procedures in the development and translation of high-throughput molecular classifiers in oncology.” Clin Cancer Res 19, no. 16 (August 15, 2013): 4315–25. https://doi.org/10.1158/1078-0432.CCR-12-3937.
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  - Gutman, David A., Lee A. D. Cooper, Scott N. Hwang, Chad A. Holder, Jingjing Gao, Tarun D. Aurora, William D. Dunn, et al. “MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set.” Radiology 267, no. 2 (May 2013): 560–69. https://doi.org/10.1148/radiol.13120118.
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  - Margolin, Adam A., Erhan Bilal, Erich Huang, Thea C. Norman, Lars Ottestad, Brigham H. Mecham, Ben Sauerwine, et al. “Systematic analysis of challenge-driven improvements in molecular prognostic models for breast cancer.” Sci Transl Med 5, no. 181 (April 17, 2013): 181re1. https://doi.org/10.1126/scitranslmed.3006112.
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  - Ferte, Charles, Justin Guinney, Jonathan Derry, erich H. huang, Benjamin Besse, and Jean-Charles Soria. “Abstract 1199: NSCLC KRAS G12C and G12V mutations drive different pathways and display specific drug sensitivity patterns.” Clinical Research, April 15, 2013. https://doi.org/10.1158/1538-7445.am2013-1199.
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  - Guinney, Justin, Charles Ferte, Erich Huang, Jonathan Derry, and Stephen Friend. “Abstract 2409: A model of RAS pathway in colorectal cancer elucidates molecular traits and drug sensitivity: an integrated analysis of gene expression from human tumors, mouse xenografts and the Cancer Cell Line Encyclopedia (CCLE).” Clinical Research, April 15, 2013. https://doi.org/10.1158/1538-7445.am2013-2409.
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  - Trister, A. D., and E. S. Huang. “A network-heuristic approach to improve the impact of genomic data on drug discovery.” Clin Pharmacol Ther 93, no. 4 (April 2013): 295–97. https://doi.org/10.1038/clpt.2012.246.
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  - LaBreche, Heather G., Joseph R. Nevins, and Erich Huang. “Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors.” Bmc Med Genomics 4 (July 22, 2011): 61. https://doi.org/10.1186/1755-8794-4-61.
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  - Huang, E. S., and A. T. Huang. “Genomics in the Diagnosis and Management of Breast Cancer,” December 1, 2010, 446–56. https://doi.org/10.1016/B978-0-12-374934-5.00035-0.
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  - Huang, E. S., and A. T. Huang. “Breast Cancer and Genomic Medicine,” December 1, 2009, 869–78. https://doi.org/10.1016/B978-0-12-369420-1.00072-X.
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  - Cheng, Skye H., Cheng-Fang Horng, Mike West, Erich Huang, Jennifer Pittman, Mei-Hua Tsou, Holly Dressman, et al. “Genomic prediction of locoregional recurrence after mastectomy in breast cancer.” J Clin Oncol 24, no. 28 (October 1, 2006): 4594–4602. https://doi.org/10.1200/JCO.2005.02.5676.
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  - Pittman, Jennifer, Erich Huang, Joseph Nevins, Quanli Wang, and Mike West. “Bayesian analysis of binary prediction tree models for retrospectively sampled outcomes.” Biostatistics 5, no. 4 (October 2004): 587–601. https://doi.org/10.1093/biostatistics/kxh011.
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  - Huang, Erich S., Joseph R. Nevins, Mike West, and Paul C. Kuo. “An overview of genomic data analysis.” Surgery 136, no. 3 (September 2004): 497–99. https://doi.org/10.1016/j.surg.2004.05.037.
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  - Pittman, Jennifer, Erich Huang, Holly Dressman, Cheng-Fang Horng, Skye H. Cheng, Mei-Hua Tsou, Chii-Ming Chen, et al. “Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes.” Proc Natl Acad Sci U S A 101, no. 22 (June 1, 2004): 8431–36. https://doi.org/10.1073/pnas.0401736101.
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  - Nevins, Joseph R., Erich S. Huang, Holly Dressman, Jennifer Pittman, Andrew T. Huang, and Mike West. “Towards integrated clinico-genomic models for personalized medicine: combining gene expression signatures and clinical factors in breast cancer outcomes prediction.” Hum Mol Genet 12 Spec No 2 (October 15, 2003): R153–57. https://doi.org/10.1093/hmg/ddg287.
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  - Huang, Erich S., Esther P. Black, Holly Dressman, Mike West, and Joseph R. Nevins. “Gene expression phenotypes of oncogenic signaling pathways.” Cell Cycle 2, no. 5 (September 2003): 415–17.
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  - Huang, E., S. Ishida, J. Pittmann, H. Dressman, A. Bild, M. Kloos, M. D’Amico, R. G. Pestell, M. West, and J. R. Nevins. “Erratum: Gene expression phenotypic models that predict the activity of oncogenic pathways (Nature Genetics (2003) 34 (226-230)).” Nature Genetics 34, no. 4 (August 1, 2003). https://doi.org/10.1038/ng0803-465.
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  - Black, Esther P., Erich Huang, Holly Dressman, Rachel Rempel, Nina Laakso, Sylvia L. Asa, Seiichi Ishida, Mike West, and Joseph R. Nevins. “Distinct gene expression phenotypes of cells lacking Rb and Rb family members.” Cancer Res 63, no. 13 (July 1, 2003): 3716–23.
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  - Huang, Erich, Seiichi Ishida, Jennifer Pittman, Holly Dressman, Andrea Bild, Mark Kloos, Mark D’Amico, Richard G. Pestell, Mike West, and Joseph R. Nevins. “Gene expression phenotypic models that predict the activity of oncogenic pathways.” Nat Genet 34, no. 2 (June 2003): 226–30. https://doi.org/10.1038/ng1167.
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  - Huang, Erich, Skye H. Cheng, Holly Dressman, Jennifer Pittman, Mei Hua Tsou, Cheng Fang Horng, Andrea Bild, et al. “Gene expression predictors of breast cancer outcomes.” Lancet 361, no. 9369 (May 10, 2003): 1590–96. https://doi.org/10.1016/S0140-6736(03)13308-9.
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  - Huang, Erich, Mike West, and Joseph R. Nevins. “Gene expression profiling for prediction of clinical characteristics of breast cancer.” Recent Prog Horm Res 58 (2003): 55–73. https://doi.org/10.1210/rp.58.1.55.
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  - West, M., C. Blanchette, H. Dressman, E. Huang, S. Ishida, R. Spang, H. Zuzan, J. A. Olson, J. R. Marks, and J. R. Nevins. “Predicting the clinical status of human breast cancer by using gene expression profiles.” Proc Natl Acad Sci U S A 98, no. 20 (September 25, 2001): 11462–67. https://doi.org/10.1073/pnas.201162998.
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  - Ishida, S., E. Huang, H. Zuzan, R. Spang, G. Leone, M. West, and J. R. Nevins. “Role for E2F in control of both DNA replication and mitotic functions as revealed from DNA microarray analysis.” Mol Cell Biol 21, no. 14 (July 2001): 4684–99. https://doi.org/10.1128/MCB.21.14.4684-4699.2001.
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  - Leone, G., R. Sears, E. Huang, R. Rempel, F. Nuckolls, C. H. Park, P. Giangrande, et al. “Myc requires distinct E2F activities to induce S phase and apoptosis.” Mol Cell 8, no. 1 (July 2001): 105–13. https://doi.org/10.1016/s1097-2765(01)00275-1.
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- Conference Papers
  - Trister, Andrew Daniel, Brian Bot, Andrea Hawkins-Daarud, Kellie Fontes, Carly Bridge, Anne Baldock, Russ Rockne, Erich Huang, and Kristin Swanson. “Use of a novel patient-specific model of glioma growth kinetics to elucidate underlying biology as measured by gene expression microarray.” In Journal of Clinical Oncology, 30:71–71. American Society of Clinical Oncology (ASCO), 2012. https://doi.org/10.1200/jco.2012.30.30_suppl.71.
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  - Trister, Andrew D., Brian Bot, Kellie Fontes, Carly Bridge, Anne L. Baldock, Jason K. Rockhill, Maciej M. Mrugala, Russ R. Rockne, Erich Huang, and Kristin R. Swanson. “A NOVEL PATIENT-SPECIFIC MODEL OF GLIOMA GROWTH KINETICS ELUCIDATES UNDERLYING BIOLOGY AS MEASURED BY GENE EXPRESSION MICROARRAY.” In Neuro Oncology, 14:99–99. OXFORD UNIV PRESS INC, 2012.
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  - Pittman, J. L., C. L. Tebbit, E. P. Black, H. K. Dressman, E. S. Huang, J. A. Olson, J. R. Marks, et al. “Predictive models that combine multiple forms of genomic and clinical data to achieve personalized prediction of outcomes in breast cancer.” In Breast Cancer Research and Treatment, 88:S21–22. SPRINGER, 2004.
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Teaching & Mentoring
Recent Courses
- COMPSCI 394: Research Independent Study 2019
- MMCI 517: Applied Data Science 2018

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Education, Training, & Certifications

Duke Appointment History

Leadership & Clinical Positions at Duke

In the News

Awards & Honors

Global Scholarship

Research

Selected Grants

External Relationships

Selected Publications

Academic Articles

Conference Papers

Recent Courses