Quang Nhat NGUYEN, Ph.D.
Lecturer Hanoi University of Science and Technology School of Information and Communication Technology
Address: No. 1, Dai-Co-Viet road, Hanoi, Vietnam E-mail: quang.nguyennhat [AT] hust.edu.vn /                quangnn [AT] soict.hust.edu.vn

 

Quang Nhat NGUYEN is currently a lecturer in the School of Information and Communication Technology, Hanoi University of Science and Technology, Vietnam.

He received his degrees of engineer in informatics and master in information technology from Hanoi University of Technology in 1997 and 2000 respectively. From 1998 to 2001, he was the lead of software development teams in several Vietnam and U.S. software companies in Vietnam. From February 2000 to October 2001, he was a lecturer at the Genetic School (a joint education program between Genetic Computer School, Singapore and Hanoi University of Technology).

He received his Ph.D. degree in computer science from the International Doctoral School, University of Trento, Italy in 2006. His Ph.D. research was on mobile recommender system, completed with the Ph.D. dissertation entitled "On-the-Move Interactive Decision Support for Recommender Systems", under the supervision of Prof. Francesco Ricci. From November 2004 to December 2005, he was a research assistant in the Electronic Commerce and Tourism Research Laboratory, ITC-irst (FBK) institute, Italy. From April 2007 to December 2008, he was a researcher and lecturer in the Faculty of Computer Science, Free University of Bolzano, Italy. He has been a lecturer in the School of Information and Communication Technology, Hanoi University of Science and Technology since February 2009.

Since 2012, he has participated in several large-scale ICT projects, as an R&D principle investigator and Software architect, in application domains such as e-government, smart city, intelligent transportation, health, tourism and retail. He has been particularly interested in applied artificial intelligence, big data, open-source technologies, and software architecture.

His R&D interests include machine learning (i.e., especially deep learning), computer vision, recommender systems, personalization, intelligent mobile services.