Lei Zhu, Ph.D., is a Distinguished Researcher and Master’s Supervisor at the School of Information Engineering, Nanchang University. He received his double bachelor’s degrees with First Class Honours in Computer Science and Applied Mathematics from the National University of Singapore (NUS) in 2017, and his Ph.D. in Computer Science from NUS in 2022. He subsequently conducted postdoctoral research at NUS and later joined the Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore, as a Research Scientist. His research focuses on artificial intelligence, medical image analysis, and intelligent healthcare systems, covering annotation-efficient learning, multimodal learning, medical imaging foundation models, large-scale AI systems, and clinical applications.

He has published 24 papers in SCI-indexed journals and leading international conferences, including 14 as first author. His representative work has appeared in Radiology, MICCAI, CVPR, ECCV, and ACM MM. His medical imaging research, conducted in collaboration with the National University Hospital (NUH), Singapore, and Siemens, has been deployed and clinically evaluated in real-world hospital settings. The developed system can analyze a complete lumbar spine MRI examination in approximately 47 seconds and improve radiologists’ reading efficiency by approximately 2.5–4× across different levels of clinical experience. The work has been featured by international media outlets including Channel NewsAsia, Healthcare Asia, and Healthcare IT News, and received the 2021 APSS-ASJ Best Clinical Research Award.

In large-scale AI systems, he has been a major contributor to Apache SINGA, a distributed deep learning system and an Apache Top-Level Project that has been recognized as one of the world’s top machine learning frameworks. The SINGA team received the 2024 ACM SIGMOD Systems Award, becoming the first team from Asia to receive this award. He also participated in the national-level AI Singapore RAPIER project as the MRI algorithm lead, responsible for multi-sequence 3D MRI model development and system integration.

Building on his experience in algorithm development, AI system engineering, and clinical translation, his current research focuses on multimodal medical imaging foundation models, annotation-efficient learning, robust learning with missing modalities, and medical AI systems and clinical applications.

🔬 Research Interests

• Medical Image Analysis

• Annotation-Efficient Learning (Semi-supervised and Weakly Supervised Learning) and Domain Adaptation

• Multimodal Learning and Medical Imaging Foundation Models

• Medical AI Systems and Clinical Applications

🚀 Student Recruitment

Students with backgrounds in computer science, artificial intelligence, mathematics, or related fields who are interested in research are welcome to join the group. The group recruits Master's students and welcomes undergraduate students for long-term research internships.

Graduate Programs:

•     Academic Master's Program: 081000 Information and Communication Engineering

•     Professional Master's Programs: 085410 Artificial Intelligence, 085409 Biomedical Engineering, 085401 New Generation Electronic Information Technology

The group provides:

•     Guidance on top-tier conference publications

•     Hospital collaborations and access to real-world clinical data

•     Support for outstanding students pursuing Master's or Ph.D. studies at universities in China or abroad

📬 Contact

📧 zhulei@ncu.edu.cn

Suggested email subject:

[Application] Name + University + Application Type (Master’s / Undergraduate Internship) + Background