Gang Hua

Gang Hua
Born	1979 China
Occupation	Computer scientist
Years active	2006–present
Known for	Computer vision, pattern recognition, facial recognition technology at Microsoft

Gang Hua (; born 1979) is a Chinese-American expert in computer science, focusing on computer vision and pattern recognition. He holds the titles of IEEE Fellow, IAPR Fellow, and ACM Distinguished Scientist. Hua played a pivotal role in advancing Microsoft's Facial Recognition technology.

Biography

Gang Hua currently serves as Director of Applied Science at Amazon (company), where he oversees the creation of personalized, proactive, autonomous, and multi-modal conversational agents for Alexa+. His research portfolio includes agentic and embodied AI, deep learning, computer vision, pattern recognition, machine learning, recommendation systems, and robotics, all aimed at developing general Artificial Intelligence with practical implementations in both cloud and edge computing environments.

Before joining Amazon, Hua was Vice President at the Multimodal Experiences Research Lab of Dolby Laboratories, directing innovation in next-generation personalized and immersive media technologies. He has also held leadership roles as CTO of Convenience Bee and Chief Scientist/Managing Director at Wormpex AI Research. During his tenure at Microsoft from 2015 to 2018, he acted as a science and technical advisor to the CVP of the Computer Vision Group, led Computer Vision Science Teams in Redmond and Taipei ATL as director, and contributed as a principal researcher and research manager within Microsoft Research. Between 2011 and 2015, Hua was an associate professor of Computer Science at Stevens Institute of Technology, taking a leave in 2014-15 to work on Amazon-Go. His earlier positions include visiting researcher and research staff member at IBM Thomas J. Watson Research Center (2010–14), senior researcher at Nokia Research Center Hollywood (2009–10), and scientist at Microsoft Live Labs (2006–09).

Hua obtained his Ph.D. in Electrical Engineering and Computer Engineering from Northwestern University in 2006. He earned an M.S. in Pattern Recognition and Intelligent Systems in 2002 and a B.S. in Control Engineering and Science in 1999 from Xi'an Jiaotong University, where he was admitted to the Special Class for Gifted Young in 1994.

Services

He is appointed general chair for the IEEE/CVF International Conference on Computer Vision scheduled for 2027 and previously served as program chair for the IEEE/CVF Conference on Computer Vision and Pattern Recognition in both 2019 and 2022. Hua contributes to the editorial boards of IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, and IAPR Journal of Machine Vision and Applications. His past editorial roles include associate editor-in-chief for Computer Vision and Image Understanding (2015–2020), associate editor positions for IEEE Transactions on Image Processing (2012–2015, 2017–2019), IEEE Transactions on Circuit Systems and Video Technologies (2015–2019), as well as serving as Vision and View Department editor for IEEE MultiMedia Magazine (2011–2016).

Awards

In recognition of his contributions to computer vision, Hua was named Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA) in 2022. He was honored as a Fellow of the Institute of Electrical and Electronics Engineers in 2018 for his advancements in facial recognition within images and videos. In 2016, he achieved Fellow status with the International Association for Pattern Recognition due to his work on visual computing and learning from unconstrained images/videos, alongside being designated Distinguished Scientist by the Association for Computing Machinery for his impact on multimedia and computer vision fields. Additionally, he received the IAPR Young Biometrics Investigator Award in 2015 for his research on unconstrained face recognition.