Jianying Hu, PhD
Program Director, Center for Computational Health
IBM T. J. Watson Research Center
Jianying Hu is a Distinguished Research Staff Member and Program Director of Center for Computational Health at IBM T. J. Watson Research Center, NY. Prior to joining IBM in 2003 she was with Bell Labs at Murray Hill, New Jersey. Dr. Hu has conducted and led extensive research in machine learning, data mining, statistical pattern recognition, and signal processing, with applications to healthcare analytics and medical informatics, business analytics, document analysis, and multimedia content analysis. Her recent focus has been on leading research efforts to develop advanced machine learning, data mining and visual analytics methodologies for deriving data-driven insights from real world healthcare data to facilitate learning health systems. Dr. Hu has published over 100 technical articles and holds 27 patents. She has served as associate editor for IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, Pattern Recognition, and International Journal for Document Analysis and Recognition, and is currently on the advisory board of the Journal of Healthcare Informatics Research. Dr. Hu is a fellow of IEEE (class of 2015), a fellow of the International Association of Pattern Recognition (class of 2010), and a recipient of the Asian American Engineer of the Year Award (class of 2013).
A Perer, F Wang, J Hu, Mining and exploring care pathways from electronic medical records with visual analytics, Journal of biomedical informatics 56, 2015, 369-378.
P Zhang, F Wang, J Hu, R Sorrentino, Label Propagation Prediction of Drug-Drug Interactions Based on Clinical Side Effects, Scientific reports 5, Nature Publishing Group, 2015.
X Wang, F Wang, J Hu and R Sorrentino, Towards actionable risk stratification: a bilinear approach, Journal of biomedical informatics 53, 2015, 147-155.
M Ozery-Flato, L Ein-Dor, H Neuvirth, N Parush, MS Kohn, J Hu, R Aharonov, A system for identifying and investigating unexpected response to treatment, AMIA Summits on Translational Science Proceedings 2015.
Z Sun, F Wang and Hu, J Hu , LINKAGE: An Approach for Comprehensive Risk Prediction for Care Management, ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2015, 1145-1154.
C Liu, F Wang, J Hu, H Xiong, Temporal phenotyping from longitudinal electronic health records: A graph based framework, ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2015, 705-714.
F Wang, P Zhang, N Cao, J Hu, R Sorrentino, Exploring the associations between drug side-effects and therapeutic indications, Journal of biomedical informatics 51, 2014, 15-23.
Ng K, Sun J, Hu J, Wang F, Personalized Predictive Modeling and Risk Factor Identification using Patient Similarity, American Medical Informatics Association (AMIA) Joint Summit on Translational Sciences, Translational Bioinformatics (TBI), 2014.
J Zhou, F Wang, J Hu, J Ye, From micro to macro: data driven phenotyping by densification of longitudinal electronic medical records, Proceedings of the 20th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2014, 135-144.
F Wang, N Lee, J Hu, J Sun, S Ebadollahi, A Framework for Mining Signatures from Event Sequences and Its Applications in Healthcare Data, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 35(2), 2013, 272-285.
J Sun, F Wang, J Hu, S Edabollahi, Supervised patient similarity measure of heterogeneous patient records. ACM SIGKDD Explorations Newsletter 14 (1), 2012, 16-24
Combining knowledge and data driven insights for identifying risk factors using electronic health records. AMIA 2012, 901-10
J Hu, F Wang, J Sun, R Sorrentino, S Ebadollahi, A healthcare utilization analysis framework for hot spotting and contextual anomaly detection. AMIA 2012