Schlumberger Centennial Chaired Professor, Dept of Electrical and Computer Engineering
University of Texas at Austin
Lab website: IDEAL@UT
Joydeep Ghosh is currently the Schlumberger Centennial Chair Professor of Electrical and Computer Engineering at the University of Texas, Austin. He joined the UT-Austin faculty in 1988 after being educated at, (B. Tech ’83) and The University of Southern California (Ph.D’88). He is the founder-director of IDEAL (Intelligent Data Exploration and Analysis Lab) and a Fellow of the IEEE. His research interests lie primarily in data mining and web mining, predictive modeling / predictive analytics, machine learning approaches such as adaptive multi-learner systems, and their applications to a wide variety of complex real-world problems such as healthcare. He has published more than 400 refereed papers and 50 book chapters, and co-edited over 20 books. He has received 14 Best Paper Awards over the years, including the 2005 Best Research Paper Award across UT and the 1992 Darlington Award. He also received the 2015 Technical Achievement Award from IEEE CS for development of multi-learner systems.
Dr. Ghosh has been a plenary/keynote speaker on several occasions such as ICDM’13,(Health Informatics workshops at) KDD14, ICML13 and ICHI13; MICAI’12, KDIR’10 and ISIT’08, and has widely lectured on intelligent analysis of large-scale data. He served as the Conference Co-Chair or Program Co-Chair for several top data mining oriented conferences, including SDM’13, SDM’12, KDD 2011, CIDM’07, ICPR’08 (Pattern Recognition Track) and SDM’06. He was the Conf. Co-Chair for Artificial Neural Networks in Engineering (ANNIE)’93 to ’96 and ’99 to ’03. He has also co-organized workshops on health informatics, high dimensional clustering, Web Analytics, Web Mining and Parallel/ Distributed Knowledge Discovery. Dr. Ghosh has served as a co-founder, consultant or advisor to several successful startups in addition to consulting for large corporations. Currently he is on the advisory board of Cognitive Scale (Healthcare thrust) and Accordion Health.
Chena Y, Joydeep Ghoshb, Cosmin Adrian Bejana, Carl A. et al. Building bridges across electronic health record systems through inferred phenotypic topics. J Biomed Inform. 2015 Apr 1. pii: S1532-0464(15)00054-4. doi: 10.1016/j.jbi.2015.03.011
Ho JC, Lee CH, Ghosh, J. Septic Shock Prediction for Patients with Missing Data. ACM Trans. Manage. Inf. Syst. Volume 5 Issue 1, April 2014
Park Y and Ghosh J. PeGS: Perturbed Gibbs Samplers that Generate Privacy-Compliant Synthetic Data. Transactions on Data Privacy 7:3 (2014) 253 – 282
Ho JC, Ghosh J, Steinhubl SR, Stewart WF, Denny JC, Malin BA, Sun J. Limestone: High-throughput Candidate Phenotype Generation via Tensor Factorization. J Biomed Inform. 2014 Dec;52:199-211. doi: 10.1016/j.jbi.2014.07.001. Epub 2014 Jul 16.
Park Y, Shankar M, Park BH, Ghosh J. Graph Database in Large Scale Healthcare System: A Proposal for Efficient Data Management and Utilization. In The 5th International Workshop on Graph Data Management
Ho J, Ghosh J, Sun J. Marble: High-throughput Phenotyping from Electronic Health Records via Sparse Nonnegative Tensor Factorization. In KDD 2014.