Surgeon at Peking University People’s Hospital, China
Dr. Xiuyuan Chen is an accomplished thoracic surgeon and researcher specializing in minimally invasive thoracic surgery, precision resection of early-stage lung cancer, and perioperative multidisciplinary treatment of locally advanced lung cancer. His innovative research integrates artificial intelligence into surgical navigation systems, aiming to improve precision and patient outcomes. With an MD in Surgery from Peking University and postdoctoral training in oncology at the University of Michigan, he has built a strong foundation in both clinical expertise and cutting-edge research. Dr. Chen has secured competitive funding, including the National Natural Science Foundation of China Youth Fund, and has contributed to China’s “New Generation Artificial Intelligence” initiative. His publications in high-impact journals such as Frontiers in Oncology, Thoracic Cancer, and Autophagy have gained international recognition. Actively involved in professional organizations, he is committed to advancing thoracic surgery through innovation, collaboration, and clinical application, making significant contributions to both academic research and patient care.
Professional Profile
Google Scholar | Scopus Profile | ORCID Profile
Education
Dr. Xiuyuan Chen earned his MD in Surgery from Peking University, where he developed a strong foundation in clinical medicine and surgical techniques. He later advanced his expertise through a postdoctoral fellowship in oncology at the University of Michigan, gaining exposure to global research methodologies and cutting-edge cancer treatments. His interest in integrating technology into healthcare led him to pursue additional training in artificial intelligence and data science through specialized programs such as the Deep Learning Nanodegree from Udacity and courses in machine learning and data analysis from Coursera and the University of Michigan. This combination of clinical and technological education has allowed him to bridge the gap between surgery and AI-based innovations. His multidisciplinary academic background not only strengthened his surgical skills but also equipped him with the ability to design and implement AI-assisted tools for thoracic surgery, positioning him at the forefront of modern medical research and innovation.
Professional Experience
Dr. Xiuyuan Chen currently serves as Associate Professor and Senior Attending in the Department of Thoracic Surgery at Peking University People’s Hospital, where he performs complex thoracic surgeries and leads research initiatives. His professional journey began as a resident in the same department, later advancing to chief resident and attending physician roles. He also completed a postdoctoral fellowship at the University of Michigan Rogel Cancer Center, where he engaged in oncology research with an emphasis on translational medicine. Over the years, he has participated in key national and international research projects, including collaborations between Michigan Medicine and Peking University. His work spans both patient care and advanced research, integrating surgical precision with AI-assisted decision-making. Dr. Chen’s professional career reflects a balance of clinical excellence, academic leadership, and collaborative research, enabling him to make impactful contributions to both healthcare practice and the development of innovative surgical technologies.
Research Interest
Dr. Xiuyuan Chen’s research interests lie at the intersection of thoracic surgery, oncology, and artificial intelligence. He focuses on developing AI-assisted surgical planning systems and multi-dimensional integrated surgical navigation tools that enhance precision in lung cancer surgeries. His work also explores the use of advanced imaging algorithms for anatomical mapping and the integration of deep learning techniques to predict surgical outcomes. Additionally, he is interested in the application of targeted therapy, immunotherapy, and chemotherapy in perioperative management for locally advanced lung cancer. Dr. Chen aims to bridge the gap between medical technology and clinical application, ensuring that innovations directly translate to improved patient care. He is committed to multidisciplinary research that combines data science, biomedical engineering, and surgery, while also contributing to national initiatives in AI for healthcare. His vision is to create intelligent surgical systems that can standardize complex procedures and optimize treatment strategies for thoracic oncology patients.
Award and Honor
Dr. Xiuyuan Chen has received recognition for his innovative contributions to thoracic surgery and oncology research. He was awarded the prestigious National Natural Science Foundation of China Youth Fund for his study on circular RNA mechanisms in lung cancer. As a key researcher in China’s “New Generation Artificial Intelligence” major project under the Science and Technology Innovation 2030 initiative, he has contributed to the development of AI-driven solutions in surgical navigation. His research collaborations with Michigan Medicine have also earned acknowledgment for advancing translational cancer research. In addition to funded projects, Dr. Chen’s publications in internationally recognized journals have been cited widely, reflecting the academic and clinical value of his work. His active involvement in professional societies, such as the International Association for the Study of Lung Cancer and the Society of Thoracic Surgeons, further demonstrates his leadership in the field. These honors reflect his dedication to advancing science and improving patient care.
Research Skill
Dr. Xiuyuan Chen possesses a diverse set of research skills that combine clinical expertise with technological innovation. His proficiency in thoracic surgery is complemented by advanced capabilities in artificial intelligence applications for medical imaging and surgical planning. He is skilled in developing and applying deep learning algorithms for anatomical segmentation and 3D reconstruction in lung cancer surgery. His expertise extends to designing translational research studies that integrate laboratory findings with clinical applications, particularly in targeted therapy, immunotherapy, and molecular oncology. Dr. Chen has experience managing multidisciplinary research teams, securing competitive grants, and conducting collaborative studies across institutions and countries. He is adept at data analysis, statistical modeling, and interpretation of complex biomedical datasets. His ability to merge AI-driven solutions with surgical precision positions him as a leader in next-generation surgical innovations, with the skills to drive impactful research that advances both academic knowledge and patient treatment outcomes.
Publications Top Notes
Title: Artificial intelligence driven 3D reconstruction for enhanced lung surgery planning
Authors: X Chen, C Dai, M Peng, D Wang, X Sui, L Duan, X Wang, X Wang, …
Year: 2025
Citation: 1
Title: Deep learning algorithm for automatic prediction of visceral pleural invasion of lung cancer based on surgical video
Authors: H Xu, W Mu, R Zou, C Cao, Z Sun, S Cheng, T Guan, H Li, X Chen, …
Year: 2023
Citation: 1
Title: An atlas of anatomical variants of subsegmental pulmonary arteries and recognition error analysis
Authors: H Xu, H Zhao, J Jin, J Geng, C Sun, D Wang, N Hong, F Yang, X Chen
Year: 2023
Citation: 8
Title: Circular RNA, circular RARS, promotes aerobic glycolysis of non‐small‐cell lung cancer by binding with LDHA
Authors: H Li, Q Huang, H Guo, X Chen, X Li, M Qiu
Year: 2023
Citation: 7
Title: AI-based chest CT semantic segmentation algorithm enables semi-automated lung cancer surgery planning by recognizing anatomical variants of pulmonary vessels
Authors: X Chen, H Xu, Q Qi, C Sun, J Jin, H Zhao, X Wang, W Weng, S Wang, …
Year: 2022
Citation: 16
Title: A fully automated noncontrast CT 3‐D reconstruction algorithm enabled accurate anatomical demonstration for lung segmentectomy
Authors: X Chen, Z Wang, Q Qi, K Zhang, X Sui, X Wang, W Weng, S Wang, …
Year: 2022
Citation: 27
Title: Total nodule number as an independent prognostic factor in resected stage III non-small cell lung cancer: a deep learning-powered study
Authors: X Chen, Q Qi, Z Sun, D Wang, J Sun, W Tan, X Liu, T Liu, N Hong, F Yang
Year: 2022
Citation: 7
Title: Lung cancer organoids analyzed on microwell arrays predict drug responses of patients within a week
Authors: Y Hu, X Sui, F Song, Y Li, K Li, Z Chen, F Yang, X Chen, Y Zhang, X Wang, …
Year: 2021
Citation: 237
Title: Circular RNA circHIPK3 modulates autophagy via MIR124-3p-STAT3-PRKAA/AMPKα signaling in STK11 mutant lung cancer
Authors: X Chen, R Mao, W Su, X Yang, Q Geng, C Guo, Z Wang, J Wang, …
Year: 2020
Citation: 287
Title: Validation of a serum 4-microRNA signature for the detection of lung cancer
Authors: X Yang, W Su, X Chen, Q Geng, J Zhai, H Shan, C Guo, Z Wang, H Fu, …
Year: 2019
Citation: 19
Title: High throughput scaffold-based 3D micro-tumor array for efficient drug screening and chemosensitivity testing
Authors: X Yan, L Zhou, Z Wu, X Wang, X Chen, F Yang, Y Guo, M Wu, Y Chen, …
Year: 2019
Citation: 78
Title: Silencing of long noncoding RNA MIR22HG triggers cell survival/death signaling via oncogenes YBX1, MET, and p21 in lung cancer
Authors: W Su, S Feng, X Chen, X Yang, R Mao, C Guo, Z Wang, DG Thomas, …
Year: 2018
Citation: 154
Title: The identification of sub-centimetre nodules by near-infrared fluorescence thoracoscopic systems in pulmonary resection surgeries
Authors: Y Mao, C Chi, F Yang, J Zhou, K He, H Li, X Chen, J Ye, J Wang, J Tian
Year: 2017
Citation: 50
Title: Comparison between sublobar resection and lobectomy for the surgical treatment of elderly patients with early stage non-small-cell lung cancer (STEPS): an open label …
Authors: F Yang, X Sui, X Chen, J Wang
Year: 2017
Citation: 1
Title: Overexpression of LINC00152 correlates with poor patient survival and knockdown impairs cell proliferation in lung cancer
Authors: S Feng, J Zhang, W Su, S Bai, L Xiao, X Chen, J Lin, RM Reddy, …
Year: 2017
Citation: 41
Conclusion
Dr. Chen is a deserving candidate for the Best Researcher Award due to his exceptional contributions in advancing thoracic surgery through innovative AI-assisted techniques and multidisciplinary cancer treatment approaches. His research has significantly impacted both clinical practice and patient outcomes, with strong evidence of leadership in funded projects and influential publications. With his dedication to translational medicine, commitment to improving surgical precision, and potential to lead groundbreaking international collaborations, he is poised to make even greater contributions to research and society in the future.