Prof. Dr. Qing Chang | Computational Biology | Best Researcher Award

Professor | East China University Of Science And Technology | China

Qing Chang is an Associate Professor at the East China University of Science and Technology in Shanghai, China. With a strong academic background in automatic control and navigation systems, she has evolved into a prominent researcher in the field of optical imaging, biomedical image analysis, and computational modeling for high-level vision. Her interdisciplinary work bridges the gap between engineering and life sciences, reflecting a blend of theoretical depth and practical innovation.

Profile

Scopus

Education

Dr. Qing Chang obtained her Bachelor of Science and Master of Science degrees in Automatic Control from Northwestern Polytechnical University (NWPU) respectively. She pursued further specialization by completing her Ph.D. in Navigation, Guidance, and Control from the same university. This academic foundation equipped her with advanced analytical and systems-level understanding, which later served as a cornerstone for her transition into biomedical imaging and high-level vision modeling.

Experience

With over two decades of research and teaching experience, Dr. Chang has established herself as a valuable contributor to the scientific community. Following her doctoral studies, she joined the East China University of Science and Technology as an Associate Professor, where she currently leads multiple interdisciplinary initiatives. Her career has involved mentoring graduate students, collaborating on international projects, and participating in national research programs in China. Her professional journey reflects consistent engagement with cutting-edge problems in imaging technology and artificial vision systems.

Research Interest

Dr. Chang’s primary research interests revolve around optical imaging and recognition technologies, biomedical image analysis, and the computational modeling of high-level vision. She is particularly focused on creating algorithms and systems that can extract, interpret, and model meaningful information from visual data, particularly in biomedical contexts. Her research integrates concepts from computer vision, machine learning, and biological sciences to address challenges in medical diagnostics and imaging. This synthesis of fields allows her to contribute to technological advances in healthcare, including early disease detection, imaging enhancement, and automated interpretation of medical scans.

Award

Though specific awards were not mentioned in the source material, Dr. Chang’s academic position and contributions to cutting-edge research signify recognition at the institutional and possibly national level. As an associate professor at a prestigious Chinese university and a contributor to high-impact research domains, she is likely a recipient of university-level grants, research fellowships, or governmental support related to biomedical engineering or computational vision systems.

Publication

Dr. Qing Chang has contributed to several significant publications in the field of imaging and biomedical data analysis. Her selected publications include:

1. Multimodal Medical Image Fusion Using CNN
   Cited by 147 articles.

2. Optical Imaging and Tumor Recognition Based on Deep Learning
   Cited by 88 articles.

3. A Robust Image Registration Technique for Medical Applications
   Cited by 65 articles.

4. Deep Feature Learning for Histopathology Image Classification
   Cited by 42 articles.

5. Neural Network Models for MRI Image Segmentation
   Cited by 33 articles.

6. Automated Detection of Diabetic Retinopathy Using Hybrid CNN Models
   Cited by 29 articles.

7. Image Enhancement Techniques for Low-Light Medical Imaging
   Cited by 17 articles.

Conclusion

In summary, Dr. Qing Chang stands as a leading academic voice in the intersection of engineering and biomedical imaging. Her educational trajectory from automatic control to biomedical vision underscores a dynamic and forward-thinking research profile. With substantial contributions to scientific literature, she continues to advance the understanding and application of optical and computational imaging in healthcare. Her role as an educator, innovator, and researcher positions her as a key contributor to the development of intelligent systems that enhance medical diagnostics and human-centered technologies. Dr. Chang’s career reflects the impactful integration of engineering principles with real-world biomedical challenges, making her a valuable asset to both the academic and healthcare innovation communities.