Weiguo Cao | medical image processing | Best Innovation Award

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Dr. Weiguo Cao | medical image processing | Best Innovation Award

Mayo Clinic | United States

Publication Profile

Google Scholar

👨‍💻 Summary

Dr. Weiguo Cao is a Senior Research Fellow at the Mayo Clinic, specializing in computer vision, machine learning, and medical image processing. With a Ph.D. in Computer Science from the Chinese Academy of Sciences, his research bridges cutting-edge AI technologies with healthcare applications, focusing on diagnostic tools and medical image analysis.

🎓 Education

Dr. Cao completed his Ph.D. in Computer Science at the Institute of Computing Technology, Chinese Academy of Sciences, Beijing, in 2011. His dissertation was titled “3D Non-rigid Shape Analysis Technology and their Applications.”

💼 Professional Experience

Dr. Cao has held key roles at prestigious institutions. He is currently a Senior Research Fellow at Mayo Clinic (June 2021-present), following his tenure as a Postdoctoral Associate at the State University of New York (2017-2021). Previously, he worked as a Research Scientist at Alibaba Group (2016-2017) and the Institute of Computing Technology, Chinese Academy of Sciences (2011-2016).

📚 Academic Citations

Dr. Cao’s work is widely recognized, with numerous publications in medical imaging, computer vision, and AI. His research outputs have contributed to advancements in medical image segmentation, machine learning algorithms, and deep learning for clinical decision support.

💻 Technical Skills

Dr. Cao is proficient in Python, C++, MATLAB, and R for programming. His technical expertise spans image processing, including texture and shape analysis, medical image segmentation, and feature extraction. He has deep experience in machine learning, working with models like SVM, Random Forest, CNN, and RNN. He’s also skilled in software design, system architecture, and using tools like Keras, TensorFlow, PyTorch, and CUDA.

👨‍🏫 Teaching Experience

Throughout his career, Dr. Cao has mentored students and researchers, offering expertise in image processing, machine learning, and software development. His contributions to educational projects and research have supported the development of new AI applications in healthcare.

🔬 Research Interests

Dr. Cao’s research interests include medical image processing (detection, segmentation, and classification of medical images), machine learning (deep learning models like CNN and RNN for healthcare), pattern recognition, and software design for creating advanced diagnostic tools. His work aims to improve the accuracy and efficiency of clinical decision-making through AI-powered systems.

📚 Top Notes Publications 

3D-GLCM CNN: A 3-dimensional gray-level co-occurrence matrix-based CNN model for polyp classification via CT colonography

    • Authors: J. Tan, Y. Gao, Z. Liang, W. Cao, M.J. Pomeroy, Y. Huo, L. Li, M.A. Barish, …

    • Journal: IEEE Transactions on Medical Imaging

    • Year: 2020

An Investigation of CNN Models for Differentiating Malignant from Benign Lesions Using Small Pathologically Proven Datasets

    • Authors: Shu Zhang, Fangfang Han, Zhengrong Liang, Jiaxing Tan, Weiguo Cao, Yongfeng …

    • Journal: Computerized Medical Imaging and Graphics

    • Year: 2019

GLCM-CNN: Gray Level Co-occurrence Matrix Based CNN Model for Polyp Diagnosis

    • Authors: J. Tan, Y. Gao, W. Cao, M. Pomeroy, S. Zhang, Y. Huo, L. Li, Z. Liang

    • Journal: 2019 IEEE EMBS International Conference on Biomedical & Health Informatics

    • Year: 2019

SHREC’08 Entry: 3D Face Recognition Using Moment Invariants

    • Authors: D. Xu, P. Hu, W. Cao, H. Li

    • Journal: IEEE International Conference on Shape Modeling and Applications

    • Year: 2008

Real-Time Accurate 3D Reconstruction Based on Kinect v2

    • Authors: Li Shi-Rui, Li Qi, Li Hai-Yang, Hou Pei-Hong, Cao Wei-Guo, Wang Xiang-Dong, …

    • Journal: Journal of Software

    • Year: 2016

Shuaa S. Alharbi | Bioimage informatics | Best Researcher Award

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Dr. Shuaa S. Alharbi | Bioimage informatics | Best Researcher Award

Doctorate at Department of Information Technology, College of Computer, Qassim University, Saudi Arabia

👨‍🎓Professional Profiles

Orcid Profile

Scopus Profile

👩‍💻 Summary

Dr. Shuaa S. Alharbi is an Assistant Professor in the Department of Information Technology at the College of Computer, Qassim University, Saudi Arabia. With a strong interdisciplinary background, she specializes in machine learning and image processing, particularly their applications in biomedical fields. Her research focuses on leveraging deep learning techniques to analyze medical images and improve diagnostic accuracy. Dr. Alharbi is dedicated to advancing bioinformatics and medical image analysis using cutting-edge technology.

🎓 Education

Dr. Alharbi holds a Ph.D. in Computer Science from Durham University, UK (2020), and both an M.Sc. and B.Sc. in Computer Science from Qassim University (2007) and King Saud University (2014), respectively. Her academic journey has provided her with a solid foundation in computer science, further augmented by extensive research in machine learning and bioimaging.

💼 Professional Experience

Dr. Alharbi has accumulated years of academic experience. She started as a Teaching Assistant at Qassim University in 2008, then progressed to Lecturer in 2015. Since 2020, she has served as an Assistant Professor at the same institution. Throughout her career, she has mentored students and contributed significantly to the academic environment at Qassim University, particularly in the Information Technology Department.

📝 Academic Committees & Administrative Roles

Dr. Alharbi has been deeply involved in various administrative roles at Qassim University. She served as E-content Supervisor (2020-2022), and currently coordinates the IT Department (2020-present). She is also a Postgraduate Supervisor (2023-present) and has been a Permanent Member of the Standing Committee for Assistance in the Scientific Council since 2023, contributing to the advancement of educational practices and research policies at the university.

🔬 Research Interests

Dr. Alharbi’s research interests are at the intersection of machine learning, image processing, and bioinformatics. She focuses on the application of deep learning for medical image analysis, working to enhance disease detection and diagnostic precision. Her work includes developing novel deep learning architectures and data-driven models to solve complex problems in medical and biological imaging.

🖥️ Technical Skills

Dr. Alharbi is proficient in a range of technical skills, including machine learning and deep learning frameworks, image and signal processing, computer graphics, and bioinformatics. She is experienced with programming languages such as Python, MATLAB, C++, and Java, and is adept at using these tools to solve complex problems in medical image analysis and other interdisciplinary fields.

📚 Teaching Experience

In addition to her research, Dr. Alharbi has taught several graduate-level courses, including Data Science, Computer Graphics, and Health Information Systems. She has also supervised Master’s theses in fields like cybersecurity, blockchain, and medical image processing, contributing to the academic growth of students in the Information Technology and Cybersecurity programs.

🌍 Conferences & Seminars

Dr. Alharbi has presented her work at prestigious international conferences, such as the IEEE BIBM International Conference on Bioinformatics and Biomedicine (Spain) and the Medical Image Computing Summer School at UCL (London). These platforms have allowed her to collaborate with global experts and stay at the forefront of research in bioimaging and machine learning.

💡 Research Grants

Dr. Alharbi was awarded a Coffee Research Grant from the Saudi Ministry of Culture, under the Saudi Heritage Preservation Society, showcasing her active involvement in research funding and promoting innovation in her fields of expertise.

 

📖 Top Noted Publications