Vu Van Thieu

Lecturer, Department Of Computer Science

Ph.D. (Leiden Institute of Advanced Computer Science, Leiden University, Netherlands, 2012)
M.S. (University of Amsterdam, Netherlands, 2005)
B.S. (Hanoi University of Science and Technology, 1999)

Email: thieuvv@soict.hust.edu.vn

Research Areas

  • AI
  • Recommendation System
  • High Performance Computing

Research Interests

  • Classification
  • Risk management
  • Numerical computation
  • GPU computing
  • High performance computing

Profile

Dr. Vu Van Thieu received the Ph.D. degree in Computer Science from Leiden Institute of Advanced Computer Science, Leiden University, Netherlands in 2012. He is currently working at Computer Science Department, School of Information and Communication Technology (SoICT), Hanoi University of Science and Technology (HUST), Vietnam. His research interests include AI and High Performance Computing.

Publications

  • VN Do, HA Le, VT Vu, Theoretical Considerations on the Optimal Performance of Sub-100 Nanometer Top-Gated Graphene Field-Effect Transistors, Journal of Electronic Materials 48 (3), 1669-1678, 2019
  • VN Do, HA Le, VT Vu, Real-space and plane-wave hybrid method for electronic structure calculations for two-dimensional materials, Physical Review B 95 (16), 165130, 2017
  • PT Do, NK Le, VT Vu, Efficient maximum matching algorithms for trapezoid graphs, Electronic Journal of Graph Theory and Applications 5 (1), 7-20, 2017
  • DV Sang, LTB Cuong, V Van Thieu, Multi-task learning for smile detection, emotion recognition and gender classification, Proceedings of the Eighth International Symposium on Information and Communication Technology, ACM, 340-347, 2017

Current Projects

  • Research and develop a platform to support the organizations to manage national research projects (KC project, 2018-2020)
  • Develop software for managing the national collection of natural samples in Vietnam (KC project, 2016 – 2019).

Teaching

  • IT4865: Distributed computing
  • IT4130: Parallel programming
  • IT5408: High performance computing
  • IT4110: Scientific Computing
  • IT3020: Discrete Maths