Loading...
Header Logo
Keywords
Last Name
Institution

Connection

Search Results to Hua Fang PhD

This is a "connection" page, showing the details of why an item matched the keywords from your search.

                     
                     

One or more keywords matched the following properties of Fang, Hua

PropertyValue
overview

Biography

Dr. Fang is Associate Professor in Division of Biostatistics and Health Services Research, Department of Quantitative Health Science since 2014. 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 (2012-2014) 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 (2013-2018): 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. 

She is also the PI of a NSF/CNS research project (2017-2019): Explore new statistical modeling approaches to characterize the 60GHz WBAN in mHealth applications.

Dr. Fang has been a statistical consultant in health, medicine, economics, and bio-engineering areas over a decade. She also participated in large-scale multi-disciplinary projects at both state and federal levels. She has sustained continous funding as PI/Co-I/Statistician from over 20 extramural grants from  NSF, NIH, VA or PCORI in the past ten years.  

Dr. Fang's research interests include computational statistics, behavioral trajectory pattern recogntion, 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.

Computational Statistics and Data Science (CSDS) lab --- PI: Julia Hua Fang

 

See more selected Publications on E-scholarship


One or more keywords matched the following items that are connected to Fang, Hua

Item TypeName
Academic Article Using propensity score modeling to minimize the influence of confounding risks related to prenatal tobacco exposure.
Concept Data Interpretation, Statistical
Academic Article Pattern Recognition of Longitudinal Trial Data with Nonignorable Missingness: An Empirical Case Study.
Academic Article A survey of big data research.
Academic Article Multiple Imputation based Clustering Validation (MIV) for Big Longitudinal Trial Data with Missing Values in eHealth.
Academic Article A New MI-Based Visualization Aided Validation Index for Mining Big Longitudinal Web Trial Data.
Academic Article ESammon: A Computationaly Enhanced Sammon Mapping based on Data Density.
Academic Article A New Mining Method to Detect Real Time Substance Use Events from Wearable Biosensor Data Stream.
Academic Article An Enhanced Visualization Method to Aid Behavioral Trajectory Pattern Recognition Infrastructure for Big Longitudinal Data.
Academic Article MIFuzzy Clustering for Incomplete Longitudinal Data in Smart Health.
Academic Article Multiple- vs Non- or Single-Imputation based Fuzzy Clustering for Incomplete Longitudinal Behavioral Intervention Data.
Academic Article eFCM: An Enhanced Fuzzy C-Means Algorithm for Longitudinal Intervention Data.
Academic Article Topic modeling for systematic review of visual analytics in incomplete longitudinal behavioral trial data.
Academic Article Harmonizing Wearable Biosensor Data Streams to Test Polysubstance Detection.

Search Criteria
  • Data
  • Science