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(Julia) Hua Fang, PhD

Julia Hua Fang

Associate Professor
Principal Investigator, CSDS Lab


Department of Computer and Information Science, UMD
Department of Quantitative Health Sciences, UMMS

Dr. Fang’s areas of expertise include machine learning/statistical learning and visual analytics in longitudinal studies (both randomized clinical trials, RCTs, and observational studies), missing data analyses and behavioral trajectory pattern recognition. She has in-depth knowledge of classical statistics, research design, as well as advanced statistical modeling and analyses. Her current research interests include machine or statistical learning of wearable biosensor data, broadly in E-/M-health and Internet of Things. She has also applied her research in data science, substance use, infectious diseases, immunology, nutritional epidemiology, behavioral medicine and business intelligence. As PI or Co-I, she has sustained continuous funding from federal agencies such as NSF, NIH, PCORI or VA over a decade.  Her projects, papers and consulting also contribute to a fair number of extramural collaborative grant awards. While being active in ASA, she has served on several renowned IEEE editorial boards such as IEEE IoT, IEEE Transactions on Big Data, and technical program committees of top ACM/IEEE conferences on data mining and connected health, e.g., ACM KDD, IEEE ICDM or IEEE/ACM CHASE. Dr Fang teaches CIS490/602 Machine Learning, CIS264 Software Quality Assurance and Testing, CIS454 Computer Graphics, CIS602 Pattern Analysis.