Dung Dinh

Dung Dinh is a seasoned professional in the field of computer science with a strong focus on deep learning and generative models. Experience includes serving as a Research Assistant at Singapore University of Technology and Design, where work centered on Conditional Table Generative Adversarial Networks and deep learning. Dung has also held positions as a Teaching Assistant at the University of Sydney and has interned as an Applied Scientist at Amazon, contributing to visual enhancement projects. Additional experience includes research internships at Google and Adobe, along with research work at the National Institute of Informatics and VCCorp, focusing on areas like traffic matrix volume prediction, natural language processing, and wireless sensor networks. Dung's academic background features an Engineer's degree and a Master of Science from Hanoi University of Science and Technology, and ongoing studies for a PhD at the University of Sydney.