Academic Profile : Faculty

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Asst Prof Wen Bihan
Nanyang Assistant Professor, School of Electrical & Electronic Engineering
External Links
 
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. He joined Nanyang Technological University in March 2019 and now is a Nanyang Assistant Professor. His research interests span areas of machine learning, computational imaging, computer vision, image and video processing, data analytics, etc. 

Dr. Bihan Wen is an elected member and subcommittee chair of the IEEE Computational Imaging (CI) Technical Committee. He is currently serving as an associate editor for IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), and MDPI Micromachines. He is also a Guest Editor for IEEE Signal Processing Magazine. He is the Program Chair of IEEE MIPR Conference 2022. He is the Lead Organizer of the LCI workshops at ICCV 2019 and 2021, and the IEEE SPACE webinar 2020-2021. He regularly serves as the Area Chair for IEEE ICIP, ICASSP and ICME, and the program committees for many AI conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV, IJCAI, AAAI). He is the recipient of the 2022 Early Career Teaching Excellence Award and 2021 Inspirational Mentor for Koh Boon Hwee Award from NTU; the 2016 Yee Fellowship from UIUC; and the 2012 Professional Engineers Board (PEB) Gold Medal. One paper he co-authored won the Best Paper Runner-Up from IEEE ICME 2020.

1. Machine Learning - Deep learning, Transform learning, Tensor modeling, Reinforcement Learning, etc. 

2. Image and Video Processing - Denoising, Super-Resolution, Inpainting, Enlightening, etc. 

3. Computer Vision - Robust image classification / segmentation, Object detection, Anomaly detection, Face recognition, etc. 

4. Computational Imaging - Magnetic resonance imaging (MRI), Computed tomography (CT), X-Ray, Synthetic-aperture radar (SAR), etc. 

5. NP-Hard Problems - Blind compressed sensing, Ill-posed inference, Sparse Coding, Combinatorial problems, etc. 

We have multiple openings and are ALWAYS looking for GOOD and Highly Self-Motivated 

a) PhD students 

b) Post-doc Research Fellows 

c) Research Associates / Project Officer 

If you are interested of working with me, please send your resume / CV. Only qualified candidates will be contacted.

 
  • Autonomous Inspection for Maritime and Urban Industries
  • Data-driven Models For Analyzing Smart Sensors And Meters In Water Distribution Networks
  • Development of fundamental AI technologies for medical AI applications
  • Machine Learning based Analysis of 3D X-Ray PCB Images for Hardware Assurance
  • Novel Noise Disentanglement Using Flow-based Joint Image and Noise Modelling: A Computational Imaging Application to Cardiovascular MR
  • P1.3 Big Data for Robot Joints Self-Learning and Transfer Learning Analytics & Controlling Motorized Mobile Platform Using Deep Learning and EEG
  • P1.3 Big Data for Robot Joints Self-learning and Transfer Learning Analytics & Controlling Motorized Platform Using Deep Learning and EEG
  • Physics-Driven Machine Learning for Computational Imaging
  • Radar Based Perception Using Artificial Intelligent
  • Reliable Artificial Intelligence for Satellite On-board Imaging
  • Robust Machine Learning with Rigorous Formulations
  • Theoreticall-Grounded and Robust Artificial Intelligence for Real-World Challenges
  • WiseSAR
Awards
Early Career Teaching Excellence Award, 2022
Inspirational Mentorship for Koh Boon Hwee Award, 2021
Best Paper Runner-Up Award, IEEE ICME 2020
Nanyang Assistant Professorship Award, 2019
 
Fellowships & Other Recognition
Yee Memorial Fellowship, UIUC, 2016
Nomination for the Harold L. Olesen Best Teaching Award, UIUC, 2013
Professional Engineers Board (PEB) Gold Medal, Singapore, 2012
 
Courses Taught
Undergrad Courses:
EE/IM 4483: Artificial Intelligence & Data Mining
EE 2008: Algorithm & Data Structure
EE 0005: Introduction to Data Science and Artificial Intelligence

Graduate Courses:
NM6005 Digital Signal Processing