Dr. Gang Hua’s research interests include computer vision, pattern recognition, and machine learning, with particular focuses on human centered visual computing, and large scale visual data analytics.

His research in human centered visual computing explores methods of robustly sensing humans from images and videos, with recent work on human detection, human motion analysis, face recognition, and automatic hand gesture recognition. He is also researching ways to effectively exploit human feedback in computational visual recognition, such as contextual modeling and active visual learning. His research in this theme has a wide range of applications that include intelligent video surveillance, interactive visual media annotation, and non-invasive vision based perceptual interfaces.

His research in large scale visual data analytics aims at building intelligent machines to automatically transform the massive quantity of unstructured real world visual media into structured semantic knowledge, which will benefit millions of users by facilitating access the greatest stores of visual data that have ever been accumulated. Applications of his research in this theme include social media sharing, large scale semantic based image and video search, object recognition and segmentation, and complex video event detection.

From 2010 to 2011, Dr. Hua was a Research Staff Member at IBM Research T. J. Watson Center, where he continues to hold an Academic Visiting Researcher position. He has also worked as a Senior Researcher at Nokia Research Center, Hollywood from 2009 to 2010, and a Scientist at Microsoft Live Labs Research from 2006 to 2009. He received the Richter Fellowship and the Walter P. Murphy Fellowship from Northwestern University in 2005 and 2002, respectively. He is a Senior Member of the IEEE and a Member of the ACM. As of October, 2011, he holds 6 US patent and has 14 more patents pending.