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    Hua Fang PhD

    TitleAssistant Professor
    InstitutionUniversity of Massachusetts Medical School
    DepartmentQuantitative Health Sciences
    AddressUniversity of Massachusetts Medical School
    55 Lake Avenue North
    Worcester MA 01655
        Overview 
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        Biography

        Dr. Fang is Assistant Professor in Division of Biostatistics and Health Services Research, Department of Quantitative Health Science. Before joining UMass Medical School in 2010, she had served as Research Assistant Professor/ Biostatistician in University of Nebraska-Lincoln for four years. She graduated from Ohio University in 2006 with her Ph.D. core in Statistics.

        She won a paper award at the 2006 Joint Research Conference on Statistics in quality industry and technology. She won Layman Awards for missing data modeling and growth trajectory pattern recognition via UNL research council competition in 2008.

        She is a recipient of the 2012 UMass CTSA Pilot Project award for modeling heterogeneity of treatment effects (HTE) in longitudinal RCT and observational studies, including 3 RCTs and 2 observational studies for comparative effectiveness research.

        She is the PI of NIH/NIDA R01 DISC project (2013-2016): Develop behavioral trajectory pattern recognition methods and tools for large-scale unstructured data from longitudinal RCT behavioral intervention studies for smoking cessation, generally, substance use, such as internet-delivered RCT interventions, and small-scaled culturally-tailored cognitive interventions. Her methods are used to capture behavioral (e.g, engagment/response) changes, identify and validate patterns, inform which  components or measures are working for which patients/users at what time and to what degree, therefore to clarify the efficacy of a trial and the effectiveness of a treatment/exposure. This approach is expanding to various application areas.

        Dr. Fang has been a statistical consultant in health, medicine, economics, and bio-engineering areas for years. She also participated in large-scale multi-disciplinary projects at both state and federal levels. She is PI/Co-I/Statistician on 11 NIH, VA, or PCORI grants.  

        Dr. Fang's research interests include computational statistics, research design, statistical modeling and analyses in clinical and translational research. She is interested in developing novel methods and applying emerging robust techniques to enable or improve the health studies that can have potential impact on the treatment or prevention of human diseases. Her research applications are in data science, substance use, infectious diseases, immunology, nutritional epidemiology, behavioral medicine, and E-/M-health.

        (Dr. Fang’s research website is under construction)

         

        See more selected Publications on E-scholarship



        Bibliographic 
        selected publications
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        1. Fang H, Dukic VM, Pickett KE, Wakschlag LS, Espy KA . Detecting graded exposure effects: A report on an east Boston pregnancy cohort. Nicotine Tob Res.2012 Advance Access doi: 10.1093/ntr/ntr272. 2012.
        2. Fang H, Johnson C, Stopp C, Espy KA. A new look at quantifying tobacco exposure during pregnancy using fuzzy clustering. Neurotoxicol Teratol. 2011 Jan-Feb; 33(1):155-65.
          View in: PubMed
        3. Fang H, Johnson C, Chevalier N, Stopp C, Wiebe S, Wakschlag LS, Espy KA. Using propensity score modeling to minimize the influence of confounding risks related to prenatal tobacco exposure. Nicotine Tob Res. 2010 Dec; 12(12):1211-9.
          View in: PubMed
        4. Fang H, Rizzo ML, Wang H, Espy KA, Wang Z. A new nonlinear classifier with a penalized signed fuzzy measure using effective genetic algorithm. Pattern Recognit. 2010; 43(4):1393-1401.
          View in: PubMed
        5. Fang, H., Kou, G., Wang, H., & Prevost, A (In Press). Special issue on “Innovative Computational Learning: Theory, Methods and Applications”. J. Comput. System Sci. Using probabilistic approach to concurrent clustering and statistical inference.
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