Dr. Zhang’s extensive experience in electrical engineering, computer science and computational biology empowers him to build up highly predictive models for very complex data from handwritten document images to large-scale cancer genomic data. Over the past decade, Dr. Zhang has developed and significantly contributed a series of influential gene network inference algorithms which have been extensively used for identification of novel pathways and gene targets, as well as development of drugs for a variety of human diseases such as cancer, atherosclerosis, Alzheimer's, obesity and diabetes. His latest research that uncovered dramatic changes in gene-gene interaction patterns in Alzheimer’s disease and pinpointed an immune/microglia gene network as the top pathway causally linked to the disease was just published in Cell. His recent research that sheds a new light on targeted therapies against breast cancer was featured by the Second AACR International Conference on Frontiers in Basic Cancer Research (San Francisco, September 14-18, 2011). His work on predicting genetic interactions was identified by Nature Biotechnology as one of the breakthroughs in the field of computational biology in 2010. The discovery of a gene cluster that is causally linked to obesity and diabetes was highlighted in Nature in 2008. His early research on image pattern recognition significantly contributed to several large-scale pattern recognition systems including U.S. Handwritten Address Identification System which has been adopted by US Postal Office. Dr. Zhang was a recipient of the Best Paper Award of ICDAR 2003 ─ the Seventh International Conference on Document Analysis and Recognition.