Academic Profile : Faculty

BihanWen_NTU2020_long2.jpg picture
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 2019 as a Nanyang Assistant Professor. His research interests span areas of machine learning, computational imaging, computer vision, image and video processing, AI model security and robustness, etc. 

Dr. Bihan Wen is an IEEE Senior Member, SubCommittee Chair of IEEE Computational Imaging (CI) TC, and an elected member of IEEE Visual Signal Processing and Communications (VSPC) TC. He is an Associate Editor for IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT). He is currently a Guest Editor for IEEE Signal Processing Magazine (SPM), 2021-2023, IEEE Journal of Selected Topics in Signal Processing (JSTSP), 2023-2025, and Remote Sensing, 2023-2025. He served as the Publicity Chair of the IEEE Conference on AI (CAI) 2023, the Program Chair of the IEEE MIPR Conference 2022, 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 conferences such as ICIP, ICASSP, ICME, IJCAI, AAAI, etc. He received 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. Many works that he co-authored won paper awards, including the Best Paper Runner-Up from IEEE ICME 2020, the Best Paper Award from IEEE ICIEA 2023, and the Best Paper Award from IEEE MIPR 2023. He was ranked the World Top 2% Scientists in Artificial Intelligence, for the Year 2021 to 2023, consecutively, by Stanford University.

1. Machine Learning - Deep learning, transform learning, reinforcement Learning, etc. 

2. Visual Signal Processing - Image denoising, super-resolution, Inpainting, Low-light image and shadow removal, etc. 

3. Computer Vision - Robust image classification, segmentation, object detection, face recognition, etc. 

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

4. AI security - Adversarial attack and defense, backdoor attack, model ownership verification, etc. 

6. NP-hard problems - 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.

  • 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
  • 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
  • Project AI-SSR
  • Project AIR REUS 2
  • Reliable Artificial Intelligence for Satellite On-board Imaging
  • Satellite-based detection and characterization of Volcanic Ash Plumes
  • Theoreticall-Grounded and Robust Artificial Intelligence for Real-World Challenges
  • WiseSAR
Best Paper Award, from IEEE MIPR 2023
Best Paper Award, from IEEE ICIEA 2023
World Top 2% Scientists in Artificial Intelligence (AI), Year 2021-2023, by Stanford.
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:
IE 4483: Artificial Intelligence & Data Mining
IE 2108: Algorithm & Data Structure
IE 0005: Introduction to Data Science and Artificial Intelligence

Graduate Courses:
NM6005 Digital Signal Processing
EE6401 Advanced Digital Signal Processing
Supervision of PhD Students
Dr. Rongkai Zhang, graduated in 2022.
Dr. Tao Bai (co-supervised), graduated in 2022.