Adams Wai Kin Kong
Associate Professor
College of Computing and Data Science
Nanyang Technological University
Nanyang Avenue,
Singapore, 639798
Office: N4-02a-017
Tel: 65-6513-8041
Fax: 65-6792-6559
E-mails: adamskong AT ntu.edu.sg / adamskong AT ieee.org
Biography
Dr. Adams Wai-Kin Kong received the Ph.D. degree from the University of Waterloo, Canada. Currently, he is an associate professor at the Nanyang Technological University, Singapore and the director of Master of Science in Artificial Intelligence programme. His research works have been published in major AI conferences and journals. One of his papers was selected as a spotlight paper by IEEE Transactions on Pattern Analysis and Machine Intelligence and another one was selected as Honorable Mention by Pattern Recognition. He is listed in Stanford University's Top 2% Scientists’ Study. His PhD students received Best Student Paper Awards in The IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), 2012 and IEEE International Conference on Bioinformatics and Bioengineering, 2013. In 2016, he received the best reviewer award from BTAS.
In the summer of 2008, he served
as an expert witness to the U.S. Department of Justice for the
child sexual abuse
case,
United States v, Michael Pepe.
He also serves as a consultant for other legal cases in Singapore and as
an associate editor for IEEE Transactions on Information Forensics and Security.
In 2022, Dr. Kong was nominated for the MSc in Business Analytics Teacher of the Year Award and received faculty award from his school. His recent research interests include pattern recognition, deep learning and their applications on power systems, healthcare, and biometrics.
What's New
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- Zhiyuan Zhou, Yueming Yin, Hao Han, Yiping Jia, Jun Hong Koh, Adams, Wai-Kin Kong and Mu, Yuguang, Journal of Chemical Information and Modeling, 2024.
- Yueming Yin, Hilbert Yuen In Lam, Yuguang Mu, Hoi Yeung Li, and Adams Wai Kin Kong, “Advancing Bioactivity Prediction through Molecular Docking and Self-Attention, IEEE Journal of Biomedical and Health Informatics, 2024
- Yi Huang, Mingzhi Lyu, Jeremy Andrew Styborski and Adams Kong, Leveraging Imperfect Restoration for Data Availability Attack, ECCV, 2024
- Jeremy Andrew Styborski, Mingzhi Lyu, Yi Huang and Adams Kong, Exploiting Supervised Poison Vulnerability to Strengthen Self-Supervised Defense, ECCV, 2024
- Yan Ren, Yanling Li and Adams Kong, Adaptive Multi-task Learning for Few-shot Object Detection, ECCV, 2024
- Jessica Sher En Loh, Naheed Anjum Arafat, Wei Xian Lim, Wai Lee Chan and Adams Kong “Finite Volume Features, Global Geometry Representations, and Residual Training for Deep Learning-based CFD Simulation”, ICML, 2024 (spotlight)
- Yueming Yin, Haifeng Hu, Jitao Yang, Chun Ye, Wilson Wen Bin Goh, Adams Wai-Kin Kong and Jiansheng Wu, “OLB-AC: Towards Optimizing Ligand Bioactivities Through Deep Graph Learning and Activity Cliffs, Bioinformatics, 2024
- Wei Xian Lim, Naheed Anjum Arafat, Wai Lee Chan and Adams Kong, “Multi-Order Loss Functions for Accelerating Unsteady Flow Simulations with Physics-Based AI”, IEEE CAI 2024
- Shilin Lu, Zilan Wang, Leyang Li, Yanzhu Liu, and Adams Kong, “MACE: Mass Concept Erasure in Diffusion Models”, CVPR 2024
- Wenwei Song, Wenxiong Kang, Adams Wai Kin Kong, Yufeng Zhang, Yitao Qiao, “Linear Adaptive Additive Angular Margin Loss for Video-based Hand Gesture Authentication”, International Journal of Computer Vision, 2024
- Yanling Li, Steven Thng, and Adams Wai Kin Kong, "Bridging the Gap between Vitiligo Segmentation and Clinical Scores", IEEE Journal of Biomedical and Health Informatics, 2024
- Bingzhi Chen, Yishu Liu, Zheng Zhang, Guangming Lu and Adams Wai Kin Kong, “ TransAttUnet: Multi-Level Attention-Guided U-Net With Transformer for Medical Image Segmentation " IEEE Transactions on Emerging Topics in Computational Intelligence, 2024
- Mingzhi Lyu, Huang Yi and Adams Kong, “Adversarial Attack for Robust Watermark Protection Against Inpainting-based and Blind Watermark Removers”, ACM MM, 2023
- Shilin Lu, Yanzhu Liu, and Adams Kong, “TF-ICON: Diffusion-Based Training-Free Cross-Domain Image Composition ”, ICCV 2023
- Xiaobao Guo, Nithish Muthuchamy Selvaraj, Zitong Yu, Adams Kong, Bingquan Shen and Alex Kot, ““Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning”, ICCV, 2023
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Nithish Muthuchamy Selvaraj, Xiaobao Guo, Adams Kong, Bingquan Shen and Alex Kot, "Adapter Incremental Continual Learning of Efficient Audio Spectrogram Transformers" INTERSPEECH 2023
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Fan Wang and Adams Kong, “A Practical Upper Bound for the Worst-Case Attribution Deviations”, CVPR, 2023
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- Yan Ren received HSE Champion award from Rolls-Royce@NTU Corporate
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Fan Wang received NeurIPS 2022 Scholar Award.
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Adams received 2022 SCSE Faculty Award
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Fan Wang and Adams Kong, "Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection", NeurIPS 2022
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Yew Lee Tan, Adams Kong, and Jung-jae Kim, "Pure Transformer with Integrated Experts for Scene Text Recognition", ECCV 2022
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Yi Huang and Adams Kong, “Transferable Adversarial Attack based on Integrated Gradients” ICLR, 2022
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Yew Lee Tan, Ernest Chew, Adams Kong, Jung-jae Kim, Joo-Hwee Lim
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Zechen Wang, Liangzhen Zheng, Sheng Wang, Mingzhi Lin, Zhihao Wang, Adams Wai-Kin Kong, Yuguang Mu, Yanjie Wei, Weifeng Li, “A fully differentiable ligand pose optimization framework guided by deep learning and a traditional scoring function'', Briefings in Bioinformatics, 2022
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