Special Session 13
Special Session 13: Frontiers in Multimodal Data Understanding: Vision, Remote Sensing, and Biomedical Applications
Description:
This special session focuses on recent advances in
multimodal data understanding, highlighting how the
integration of computer vision, remote sensing, and
biomedical imaging is driving new frontiers in intelligent
perception and decision-making. With the rapid growth of
heterogeneous data sources—ranging from medical images and
microscopy data to satellite imagery and multi-sensor
observations—there is an increasing demand for robust,
scalable, and interpretable AI models capable of learning
across modalities, scales, and domains.
Session organizers
Assoc. Prof. Kangjian He, Yunnan University, China
Assoc. Prof. Yanan Guo, Beijing Information Science and
Technology University, China
Assoc. Prof. Liye Mei, Hubei University of Technology, China
Asst. Prof. Ruichao Hou, Nanjing University, China
Asst. Prof. Yanyu Liu, Yunnan University of Finance and
Economics, China
The topics of interest include, but are not limited
to:
• Multimodal and cross-domain image fusion and
representation learning
• Foundation and large vision-language models for integrated
multimodal tasks
• High-resolution image processing, 3D reconstruction, and
change detection
• Cross-sensor and cross-temporal data analysis for remote
sensing and earth observation
• Biomedical data analytics, medical artificial
intelligence, and digital health
• Multimodal learning for natural scene understanding and
environmental monitoring
• Scalable, efficient, and trustworthy AI for large-scale
and safety-critical multimodal data
Submission method
Submit your Full Paper (no less than 8 pages) or your paper
abstract-without publication (200-400 words) via
Online Submission System, then choose Special Session 13
(Frontiers in Multimodal Data Understanding: Vision, Remote Sensing, and Biomedical Applications)
Template Download
Introduction of session organizers
Assoc. Prof. Kangjian He
Yunnan University, China
Kangjian He received the Ph.D. degree from Yunnan University, Kunming, China, where he also completed postdoctoral research. He is currently an Associate Professor and Doctoral Supervisor at the School of Information Science and Engineering, Yunnan University. His research interests include image processing, multimodal information fusion, intelligent healthcare, and artificial intelligence. He has published over 50 papers as first or corresponding author in prestigious international journals and conferences such as IEEE TMM, TIM, TCE, TETCI, JBHI, AAAI , ICASSP, etc. His works have been cited more than 1,900 times, and he has an h-index of 21.
Assoc. Prof. Yanan Guo
Beijing Information Science and Technology University, China
Yanan Guo received the B.S. degree from Hubei Polytechnic University in 2014 and the Ph.D. degree from Yunnan University in 2019. She is currently employed at the School of Information and Communication Engineering, Beijing Information Science and Technology University. She has published over thirty papers in refereed journals, including IEEE TRANSACTIONS ON MULTIMEDIA, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, and IEEE TRANSACTIONS ON IMAGE PROCESSING. Her current research interests include computer vision, pattern recognition, and machine learning.
Assoc. Prof. Liye Mei
Hubei University of Technology, China
Liye Mei received the Ph.D. degree in Engineering from Wuhan University. He is currently a Master’s Supervisor in the School of Computer Science, Hubei University of Technology, and an Adjunct Supervisor with the Industrial Research Institute of Wuhan University. He was selected for the Hubei Province Young Science and Technology Talent Morning Hight Lift Project. His research interests include biomedical image intelligent analysis, optical diagnostics, and multimodal image fusion and processing. He has published more than 100 papers in top-tier journals and conferences such as Light: Science & Applications, Pattern Recognition, MICCAI, IEEE TGRS, and ACS Photonics. One of his papers was recognized as an ESI Highly Cited Paper, and his work has been cited over 852 times according to Google Scholar.
Asst. Prof. Ruichao Hou
Nanjing University, China
Ruichao Hou received his Ph.D. degree in Computer Science and Technology from Nanjing University in 2023. He is currently an Assistant Researcher at the Software Institute of Nanjing University, where he also serves as Deputy Secretary-General of the JITAS Embodied AI Special Committee and as a member of the CAAI Embodied AI Special Committee. His research interests include multimedia computing and embodied AI. He was selected for Nanjing University’s Program for Outstanding Ph.D. Candidates and received the First Prize in Science and Technology from JITAS. He has published more than 20 papers in top-tier journals and conferences such as TCSVT, TCI, ICMR, and ICME. One of his papers was recognized as an ESI Highly Cited Paper, and his work has been cited over 850 times according to Google Scholar.
Asst. Prof. Yanyu Liu
Yunnan
University of Finance and Economics, China
Yanyu Liu received Ph.D. degree in information and communication engineering from Yunnan University, Yunnan, China, in 2023. He is currently working as a lecturer at Yunnan University of Finance and Economics. His work focuses on the application of deep learning in medical image analysis and fusion, contributing to the advancement of clinical diagnostic technologies. He has participated in multiple national and provincial-level research projects, and has published several papers in core journals and international conferences in the field of image processing and AI, including IEEE Journal of Biomedical and Health Informatics, IEEE Signal processing letters, Expert Systems with Applications, Neurocomputing etc. His works have been cited more than 428 times, and he has an h-index of 14.