Yangqin Feng Research Scientist Institute of High Performance Computing, A*STAR, Singapore 1 Fusionopolis Way, #16-16 Connexis North, Singapore 138632 Email: fengyangqin [at] outlook [dot] com

Welcome to my homepage. I am a research scientist at the Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore. Before joining IHPC, I received my PhD degree in Computer Science from Sichuan University in 2019, supervised by Professor Lei Zhang. From 2017 to 2018, I was a visiting PhD student at the Medical Imaging and Image Interpretation Group, School of Computer Science, University of Birmingham, United Kingdom, under the supervision of Prof. Hamid Dehghani.

My research interests are in machine learning and deep nerual networks. The related topics include representation learning, deep neural networks, image classfication, medical image analysis, etc.

Publication

• Category-aware test-time training domain adaptation
  IEEE Conference on Artificial Intelligence, 2024 (Spotlight Paper)
  Yangqin Feng, Xinxing Xu, Huazhu Fu, Yan Wang, Zizhou Wang, Liangli Zhen, Rick Siow Mong Goh, Yong Liu
  
  
• Cost-sensitive distribution alignment for improving automated medical diagnosis using retinal fundus photography
  IEEE Conference on Artificial Intelligence, 2024 (Spotlight Paper)
  Yangqin Feng, Xinxing Xu, Zizhou Wang, Yan Wang, Huazhu Fu, et al.
  
  
• Continuous disentangled joint space learning for domain generalization
  IEEE Transactions on Neural Networks and Learning Systems, 2024
  Zizhou Wang, Yan Wang, Yangqin Feng, Jiawei Du, Yong Liu, Rick Siow Mong Goh, and Liangli Zhen
  
  
• MedNAS: Multi-scale training-free neural architecture search for medical image analysis
  IEEE Transactions on Evolutionary Computation, 2024
  Yan Wang, Liangli Zhen, Jianwei Zhang, Miqing Li, Lei Zhang, Zizhou Wang, Yangqin Feng, Yu Xue, Xiao Wang, et al.
  
  
• Geometric correspondence-based multimodal learning for ophthalmic image analysis
  IEEE Transactions on Medical Imaging, 2024
  Yan Wang, Liangli Zhen, Tien-En Tan, Huazhu Fu, Yangqin Feng, Zizhou Wang, Xinxing Xu, Rick Siow Mong Goh, et al.
  
  
• Consistent representation via contrastive learning for skin lesion diagnosis
  Computer Methods and Programs in Biomedicine, 2023
  Zizhou Wang, Lei Zhang, Xin Shu, Yan Wang, Yangqin Feng
  
  
• Minimal-supervised medical image segmentation via vector quantization memory
  MICCAI, 2023
  Yanyu Xu, Menghan Zhou, Yangqin Feng, Xinxing Xu, Huazhu Fu, Rick Siow Mong Goh, Yong Liu
  
  
• Deep neural network augments performance of junior residents in diagnosing COVID-19 pneumonia on chest radiographs
  Diagnostics, 2023
  Yangqin Feng, Jordan Sim Zheng Ting, Xinxing Xu, Chew Bee Kun, Edward Ong Tien En, Hendra Irawan Tan Wee Jun, Yonghan Ting et al.
  
  
• Contrastive domain adaptation with consistency match for automated pneumonia diagnosis
  Medical Image Analysis, 2023
  Yangqin Feng, Zizhou Wang, Xinxing Xu, et al.
  
  
A feature space-restricted attention attack on medical deep learning systems
IEEE Transactions on Cybernetics, 2022
Zizhou Wang, Xin Shu, Yan Wang, Yangqin Feng, Lei Zhang, Zhang Yi.


• Adversarial multimodal fusion with attention mechanism for skin lesion classification using clinical and dermoscopic images
  Medical Image Analysis, 2022
  Yan Wang, Yangqin Feng, Lei Zhang, Joey Tianyi Zhou, Yong Liu, Rick Siow Mong Goh, and Liangli Zhen
  
  
• Diagnostic performance of a deep learning model deployed at a national Covid-19 screening facility for detection of pneumonia on frontal chest radiographs
  Healthcare, 2022
  Jordan ZT Sim, Yong-Han Ting, Yuan Tang, Yangqin Feng, Xiaofeng Lei, Xiaohong Wang, Wen-Xiang Chen, Su Huang, Sum-Thai Wong, Zhongkang Lu, Yingnan Cui, Soo-Kng Teo, Xin-Xing Xu, Wei-Min Huang, Cher-Heng Tan
  
  
• Deep supervised domain adaptation for pneumonia diagnosis from chest X-ray images
  IEEE Journal of Biomedical and Health Informatics, 2022
  Yangqin Feng, Xinxing Xu, Yan Wang, Xiaofeng Lei, Soo Kng Teo, Jordan Sim Zheng Ting, Yonghan Ting, Liangli Zhen, Joey Tianyi Zhou, Yong Liu, Cher Heng Tan
  
  
• WDCCNet: Weighted double-classifier constraint neural network for mammographic image classification
  IEEE Transactions on Medical Imaging, 2022
  Yan Wang, Zizhou Wang, Yangqin Feng, Lei Zhang
  
  
• Few-shot domain adaptation with polymorphic transformers
  MICCAI, 2021
  Shaohua Li, Xiuchao Sui, Jie Fu, Huazhu Fu, Xiangde Luo, Yangqin Feng, Xinxing Xu, Yong Liu, Daniel Ting, Rick Siow Mong Goh
  
  
• Deep adversarial domain adaptation for breast cancer screening from mammograms
  Medical Image Analysis, to be published, 2021
  Yan Wang, Yangqin Feng, Lei Zhang, Zizhou Wang, Qing Lv, Zhang Yi
  
  
• A dual simple recurrent network model for chunking and abstract processes in sequence learning
  Frontiers in Psychology, to be published, 2021
  Lituan Wang, Yangqin Feng, Qiufang Fu, Jianyong Wang, Xunwei Sun, Xiaolan Fu, Lei Zhang, Zhang Yi
  
  
• Feature-sensitive deep convolutional neural network for multi-instance breast cancer detection
  IEEE/ACM Transactions on Computational Biology and Bioinformatics, to be published, 2021
  Yan Wang, Lei Zhang, Xin Shu, Yangqin Feng, Yi Zhang, Qing Lv
  
  
• Application of deep neural networks to improve diagnostic accuracy of rheumatoid arthritis using diffuse optical tomography
  Quantum Electronics, 2020
  Yangqin Feng, Daniel Lighter, Lei Zhang, Yan Wang, Hamid Dehghani
  
  
• Deep neural networks improve diagnostic accuracy of rheumatoid arthritis using diffuse optical tomography
  European Conference on Biomedical Optics, 2019
  Hamid Dehghani, Yangqin Feng, Daniel Lighter, Lei Zhang, Yan Wang
  
  
• Deep manifold preserving autoencoder for classifying breast cancer histopathological images
  IEEE/ACM transactions on computational biology and bioinformatics, 2018
  Yangqin Feng, Lei Zhang, Juan Mo
  
  
• Exudate-based diabetic macular edema recognition in retinal images using cascaded deep residual networks
  Neurocomputing, 2018
  Juan Mo, Lei Zhang, Yangqin Feng
  
  
• Breast cancer cell nuclei classification in histopathology images using deep neural networks
  International journal of computer assisted radiology and surgery, 2018
  Yangqin Feng, Lei Zhang, Zhang Yi
  
  
• A multi-level context fusion network for exudate segmentation in retinal images
  ICACI, 2017
  Juan Mo, Lei Zhang, Yangqin Feng
  
  
• A neural network model of chunking and abstract processes in implicit sequence learning: OR1505
  International Journal of Psychology, 2016
  Qiufang Fu, Lituan Wang, Yangqin Feng, Jianyong Wang, Xiaolan Fu, Lei Zhang, Zhang Yi
  
  

Awards and Honours

• The 2ed Prize in the National University of Singapore Shih-chang Wang Prize in Radiology, 2024.
• The COVID-19 Resilience Medal, Singapore National Award, 2023.
• Best Paper Winner at the MICCAI Workshop on Ophthalmic Medical Image Analysis, 2022.
• The National Healthcare Innovation and Productivity (HIP) Medal for “best practice medal - automation, it and robotics innovation”, Singapore, 2021. (Team Award)
• The Singapore IT Leaders Award, 2021. (Team Award)
• A*STAR COVID Award, A*STAR, 2021