|Academic Profile |
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Asst Prof Wen Bihan
Assistant Professor, School of Electrical & Electronic Engineering
Phone: +65 67904708
Office: S2 B2B 54
|Dr. Bihan Wen received the B.Eng. degree in Electrical and Electronic Engineering (EEE) from Nanyang Technological University (NTU), Singapore, in 2012, the MS and PhD degrees in Electrical and Computer Engineering from University of Illinois at Urbana-Champaign (UIUC), USA, in 2015 and 2018, respectively. From 2018 to 2019, he was with Dolby Laboratories, California, USA, and YITU Technology, Singapore. He joined Nanyang Technological University as an Assistant Professor in March 2019. His research interests span areas of machine learning, computational imaging, computer vision, image and video processing, and big data applications. |
He is an elected member of the IEEE Computational Imaging (CI) Technical Committee. He served as the Area Chair and Program Committee for IJCAI and ICIP 2019. He also co-organized the CSLSC 2017 and MIPR 2019 conference as the Session Chairs. He was the recipient of the 2016 Yee Fellowship, and the 2012 Professional Engineers Board (PEB) Gold Medal. He won the 1st Place Award in the 3MT Thesis Competition at ICME 2018, the Best Presentation Award at 2018 Midwest Research Summit in USA, and the Best Talk Award at 2018 CSL Student Conference. A paper he co-authored won the 10% Best Paper Award at ICIP 2014.
|1. Machine Learning|
- Deep learning, Transform learning, Dictionary learning, Tensor modeling, etc.
2. Image and Video Processing
- Denoising, Super-Resolution, Inpainting, Restoration, etc.
3. Computer Vision
- Robust classification / segmentation, Object detection, Crowd counting, Image retrieval, etc.
4. Computational Imaging
- Magnetic resonance imaging (MRI), Computed tomography (CT), Synthetic-aperture radar (SAR), etc.
5. Inverse Problems
- Blind compressed sensing, Ill-posed inference, Data reconstruction and modeling, etc.
We are ALWAYS looking for GOOD and Highly Motivated
a) PhD students
b) Post-doc Research Fellows
c) Research Associates
If you are interested of working with me, please send your resume / CV.
- Robust Machine Learning with Rigorous Formulations
- Theoreticall-Grounded and Robust Artificial Intelligence for Real-World Challenges
- B. Wen, S. Ravishankar, and Y. Bresler. (2019). VIDOSAT - High-dimensional Sparsifying Transform Learning for Online Video Restoration. IEEE Transactions on Image Processing, 28(4), 1691--1704.
- D. Liu, B. Wen, Y. Fan, C. C. Loy, T. S. Huang. (2018). Non-Local Recurrent Network for Image Restoration. Neural Information Processing Systems (NeurIPS).
- D. Liu, B. Wen, X. Liu, Zhangyang Wang, and T. Huang. (2018). When Image Denoising Meets High-Level Vision Tasks: A Deep Learning Approach. International Joint Conference on Artificial Intelligence (IJCAI).
- B. Wen, Y. Li, L. Pfister, and Y. Bresler. (2017). Joint Adaptive Sparsity and Low-rankness on the Fly: An Online Tensor Reconstruction Method for Video Denoising. IEEE International Conference on Computer Vision (ICCV).
- B. Wen, S. Ravishankar, and Y. Bresler. (2016). Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications. International Journal of Computer Vision, 114(2-3), 137--167.