Assist Prof Dr. Suncheng Xiang | Machine Learning and AI Applications | Best Researcher Award

Shanghai Jiao Tong University | China

PUBLICATION PROFILE

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🎓 EARLY ACADEMIC PURSUITS

Dr. Suncheng Xiang’s academic journey began with a B.S. in Electrical Engineering and Automation from Changsha University of Science & Technology (2010–2014), where he demonstrated early promise through multiple scholarships and honors. He pursued an M.S. in Software Engineering at the National University of Defense Technology (NUDT) from 2014 to 2017, continuing his academic excellence with multiple recognitions, including first-class scholarships and “Outstanding Student” awards. His scholarly momentum led to a Ph.D. in Computer Science and Technology at Shanghai Jiao Tong University (SJTU) from 2017 to 2022, where he laid the foundation for his work at the intersection of artificial intelligence and medical technology.

💼 PROFESSIONAL ENDEAVORS

Currently serving as an Assistant Professor at the School of Biomedical Engineering, SJTU, since August 2022, Dr. Xiang is also co-affiliated with the Institute of Medical Robotics, reflecting his interdisciplinary engagement. His teaching portfolio includes courses like Artificial Intelligence and Medicine and Medical Imaging Intelligence Technology, and he has served as a lead TA in core computing courses during his academic years. His professional memberships with IEEE and ACM further demonstrate his integration into the global scientific community.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Xiang’s research lies at the convergence of machine learning, computer vision, and biomedical applications, with significant work in domain adaptation, image generation, 3D reconstruction, and multimodal foundation models. He has contributed to both theoretical advancements and real-world solutions, evident in his published preprints on arXiv, which explore topics such as polyp re-identification, medical image segmentation, and gesture recognition. His innovation extends to patents—notably in vessel re-identification using transfer learning and a reusable implantable drive mechanism.

🌍 IMPACT AND INFLUENCE

As an active reviewer for more than 40 peer-reviewed journals—including prestigious outlets like IEEE Transactions on Medical Imaging, Pattern Recognition, and Machine Learning—Dr. Xiang holds a Distinguished Reviewer title. He is also an associate editor for several journals such as Biomedical Engineering Communications and Intelligent Manufacturing. His presence at major conferences like CVPR, ICCV, MICCAI, and EMNLP as a reviewer, session chair, or workshop organizer highlights his growing influence in global academic discourse. Additionally, his invited talks at leading institutions such as Fudan University, Wuhan University, and international platforms demonstrate his thought leadership.

📈 ACADEMIC CITES

Dr. Xiang’s open-source philosophy and dedication to knowledge sharing are reflected in his active GitHub repository, where he shares code and models related to his publications. This contributes to his growing academic citations and impact, as his works are used by fellow researchers and practitioners alike. Although specific citation metrics aren’t listed, his consistent involvement in high-profile research and collaboration across multidisciplinary teams suggests a rising citation trajectory.

🌟 LEGACY AND FUTURE CONTRIBUTIONS

Looking ahead, Dr. Xiang’s leadership in multimodal cognitive learning, AI for healthcare, and robotic surgery is poised to contribute significantly to next-generation biomedical systems. His ongoing national and municipal-level projects, including the National Natural Science Foundation of China Youth Project and Shanghai Municipal Health Commission projects, indicate sustained support and expectations from the research community. With a rich portfolio in teaching, mentorship, and interdisciplinary collaboration, Dr. Xiang is building a legacy that bridges technical innovation with clinical translation.

 📚 TOP NOTES PUBLICATIONS

Vm-unet: Vision mamba unet for medical image segmentation

• • Authors: J. Ruan, J. Li, S. Xiang

  • Journal/Conference: arXiv preprint arXiv:2402.02491

  • Year: 2024

Malunet: A multi-attention and light-weight unet for skin lesion segmentation

• • Authors: J. Ruan, S. Xiang, M. Xie, T. Liu, Y. Fu

  • Journal/Conference: 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

  • Year: 2022

Unsupervised domain adaptation through synthesis for person re-identification

• • Authors: S. Xiang, Y. Fu, G. You, T. Liu

  • Journal/Conference: 2020 IEEE International Conference on Multimedia and Expo (ICME)

  • Year: 2020

Less is more: Learning from synthetic data with fine-grained attributes for person re-identification

• • Authors: S. Xiang, D. Qian, M. Guan, B. Yan, T. Liu, Y. Fu, G. You

  • Journal/Conference: ACM Transactions on Multimedia Computing, Communications and Applications

  • Year: 2023

Learning from self-discrepancy via multiple co-teaching for cross-domain person re-identification

• • Authors: S. Xiang, Y. Fu, M. Guan, T. Liu

  • Journal/Conference: Machine Learning

  • Year: 2023

Rethinking illumination for person re-identification: A unified view

• • Authors: S. Xiang, G. You, L. Li, M. Guan, T. Liu, D. Qian, Y. Fu

  • Journal/Conference: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

  • Year: 2022