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Fangyijie (Fang) Wang (王方义杰)

AI researcher in medical imaging analysis

Fangyijie is a self-driven AI researcher keen to apply state-of-the-art Deep Learning algorithms to real-world computer vision applications. Interested in developing AI applications to assist healthcare workers in clinical decision-making. Skilled administrator of cloud computing and state-of-the-art technology ranging from Big Data to AI.

About

I am a PhD researcher from University College Dublin Shcool of Medicine, Ireland, working with Dr. Kathleen M. Curran at SFI ML-Labs. My research is situated at the intersection of artificial intelligence and medical image analysis, with the goal of enhancing healthcare through the application of machine intelligence. Before my PhD, I was a Data Engineer at Verizon Connect, Citigroup. I earned my Master’s degrees in Statistics and Computer Science from University College Dublin, and Bachelor’s degree in Software Engineering from Nanjing University of Information Science & Technology.

Publications

Wang, F., Curran, K. M, & Silvestre, G. (2024). Semi-supervised Cervical Segmentation on Ultrasound by A Dual Framework for Neural Networks. ISBI 2025 Fetal Ultrasound Grand Challenge. (oral) doi:10.48550/arXiv.2503.17057

Jieyun Bai, Zihao Zhou, Zhanhong Ou, Gregor Koehler, Raphael Stock, Klaus Maier-Hein, Marawan Elbatel, Robert Martí, Xiaomeng Li, Yaoyang Qiu, Panjie Gou, Gongping Chen, Lei Zhao, Jianxun Zhang, Yu Dai, Fangyijie Wang, Guénolé Silvestre, Kathleen Curran, Hongkun Sun, Jing Xu, Pengzhou Cai, Lu Jiang, Libin Lan, Dong Ni, Mei Zhong, Gaowen Chen, Víctor M. Campello, Yaosheng Lu, Karim Lekadir (2024). PSFHS Challenge Report: Pubic Symphysis and Fetal Head Segmentation from Intrapartum Ultrasound Images. Medical Image Analysis, doi:10.1016/j.media.2024.103353

Ye, Z., Chen, T., Wang, F., Zhang, H., & Zhang, L. (2024). LV-Mamba: Integrating Denoising Mechanism with Mamba for Improved Segmentation of the Pediatric Echocardiographic Left Ventricle. Proceedings of 2024 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024) doi:10.48550/arXiv.2402.08506

Wang, F., Whelan, K., Silvestre, G., & Curran, K. M. (2024). Generative Diffusion Model Bootstraps Zero-shot Classification of Fetal Ultrasound Images In Underrepresented African Populations. Perinatal, Preterm and Paediatric Image Analysis. MICCAI PIPPI 2024. (oral) doi:10.1007/978-3-031-73260-7_13

Ye, Z., Chen, T., Wang, D., Wang, F., & Zhang, L. (2024). HFE-Mamba: High-Frequency Enhanced Mamba Network for Efficient Segmentation of Left Ventricle in Pediatric Echocardiograms. IEEE Access, 12, 123038–123048. doi:10.1109/ACCESS.2024.3424546

Murphy, J, Wang, F., Mazhar Qureshi, M., & Namee, B.M., 2024. From Ground to Orbit: Enhancing Satellite Autonomy with AI-Powered Anomaly Detection. Proceedings of 38th Annual Small Satellite Conference, Automation - Research and Academia, SSC24-WV-04. https://digitalcommons.usu.edu/smallsat/2024/all2024/34/.

Aleem, S., Wang, F., Maniparambil, M., Arazo, E., Dietlmeier, J., Curran, K., Connor, N., & Little, S. (2024). Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero-shot Medical Image Segmentation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (pp. 5184-5193). (oral) doi:10.1109/CVPRW63382.2024.00526

Wang, F., Silvestre, G., & Curran, K. M. (2023). Evaluate Fine-tuning Strategies for Fetal Head Ultrasound Image Segmentation with U-Net. Irish Machine Vision and Image Processing Conference Proceedings (IMVIP 2023), 350–353. Irish Pattern Recognition and Classification Society. doi:10.5281/zenodo.8205689

Pallonetto, F., Mangina, E., Finn, D., Wang, F., & Wang, A. (2014). A restful API to control a energy plus smart grid-ready residential building: demo abstract. Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings (ACM BuildSys 2014), 180–181. doi: 10.1145/2674061.2675023

Preprints

Wang, F., Silvestre, G., & Curran, K. M. (2024). Segmenting Fetal Head with Efficient Fine-tuning Strategies in Low-resource Settings: an empirical study with U-Net. arXiv [Eess.IV]. Retrieved from http://arxiv.org/abs/2407.20086

Ye, Z., Chen, T., Wang, F., Zhang, H., & Zhang, L. (2024). P-Mamba: Marrying Perona Malik Diffusion with Mamba for Efficient Pediatric Echocardiographic Left Ventricular Segmentation. arXiv [Cs.CV]. Retrieved from http://arxiv.org/abs/2402.08506

Wang, F., Silvestre, G., & Curran, K. (2024). MiTU-Net: A fine-tuned U-Net with SegFormer backbone for segmenting pubic symphysis-fetal head. arXiv [Eess.IV]. The 5th place in the MICCAI 2023 Challenge Pubic Symphysis-Fetal Head Segmentation. Retrieved from http://arxiv.org/abs/2401.15513

Wang, F., Silvestre, G., & Curran, K. M. (2024). Lightweight Framework for Automated Kidney Stone Detection using coronal CT images. arXiv [Eess.IV]. Retrieved from http://arxiv.org/abs/2311.14488

Wang, F., & Salter-Townshend, M. (2023). Novel Models for Multiple Dependent Heteroskedastic Time Series. arXiv [Stat.ME]. Retrieved from http://arxiv.org/abs/2310.17760

Experience

  • PhD Researcher, University College Dublin, Dublin, Ireland
  • Intern, Réaltra Space Systems Engineering, Dublin, Ireland
  • Data Engineer, Verizon Connect, Dublin, Ireland
  • Data Warehouse BI Developer, Citigroup, Dublin, Ireland
  • Localization Tester, Keywords Studio, Dublin, Ireland

Education

  • 2022 - 2026, PhD, School of Medicine, University College Dublin, Dublin, Ireland
  • 2020 - 2022, MSc Statistics, University College Dublin, Dublin, Ireland
  • 2013 - 2014, MSc Computer Science, University College Dublin, Dublin, Ireland
  • 2012 - 2013, BSc Software , South East Technological University, Waterford, Ireland
  • 2009 - 2013, BEng Software Engineering, Nanjing University of Information Science and Technology, Nanjing, China