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

Sherin Zafar | Machine Learning  | Women Researcher Award

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Dr. Sherin Zafar | Machine Learning  | Women Researcher Award

Jamia Hamdard | India

PUBLICATION PROFILE

Scopus

🌟 DR. SHERIN ZAFAR: ACADEMIC AND RESEARCH PIONEER 

👩‍🏫 INTRODUCTION

Dr. Sherin Zafar is an accomplished Assistant Professor in the Department of Computer Science and Engineering at the School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi. Joining the institution in 2015, she has made remarkable contributions to teaching, research, and faculty development. With expertise in network security, machine learning, and health informatics, Dr. Zafar continues to inspire both students and colleagues alike.

🎓 EARLY ACADEMIC PURSUITS

Dr. Zafar’s academic journey began with a Bachelor’s degree in Computer Engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV), Bhopal, followed by a Master’s degree in the same field. Her passion for optimizing network protocols led her to complete her Ph.D. at Manav Rachna International Institute of Research and Studies (MRIIRS) in 2015, where she focused on creating secure protocols for Mobile Ad-Hoc Networks (MANETs) through biometric authentication.

💼 PROFESSIONAL ENDEAVORS

Since joining Jamia Hamdard, Dr. Zafar has been dedicated to academic growth and research excellence. Her professional endeavors span the fields of artificial intelligence (AI), health informatics, and wireless networks. A regular participant in faculty development programs (FDP), workshops, and international conferences, Dr. Zafar stays at the forefront of technological advancements, demonstrating her commitment to personal and professional growth.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Zafar’s research interests are centered around applying AI and computational techniques to real-world problems, especially in health and security. Her work in e-health, including maternal health improvement through AI-based systems, and the development of secure network protocols, highlights her commitment to impactful research. She has also explored the application of machine learning in smart city technologies and water quality monitoring.

🌍 IMPACT AND INFLUENCE

Dr. Zafar has made a significant impact in the academic community through her publications and collaborative research. Her work in healthcare AI, optimization techniques, and network security has been widely recognized and cited by scholars and professionals worldwide. Her contributions have advanced both theoretical and practical aspects of computer science and engineering.

📚 ACADEMIC CITATIONS AND PUBLICATIONS

Dr. Zafar’s academic footprint includes high-quality research papers published in top-tier journals and international conference proceedings. Her studies, including works on AI in healthcare and photo captioning for visually impaired individuals, have been published in journals like Heliyon, Proceedings on Engineering Sciences, and Multimedia Tools and Applications. These works have been indexed in Scopus and Web of Science, contributing to the ongoing academic dialogue.

🏆 HONORS & AWARDS

Throughout her career, Dr. Zafar has received several honors in recognition of her contributions to teaching and research. These accolades showcase her dedication to enhancing the educational landscape and driving innovations in technology and healthcare.

🛠️ LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Zafar continues her work at Jamia Hamdard, her legacy is one of inspiring innovation and fostering academic excellence. With a focus on AI, machine learning, and secure communications, her future research is poised to make lasting contributions to the fields of computer science and healthcare, inspiring future generations of researchers and professionals.

📜 FINAL NOTE

Dr. Sherin Zafar’s career is a testament to her passion for research and teaching. Through her groundbreaking research in AI, network security, and healthcare, Dr. Zafar has earned a well-deserved reputation as a leader in her field. As she continues her academic journey, her influence will undoubtedly shape the future of computer science and engineering, leaving a lasting legacy for years to come.

📚 TOP NOTES PUBLICATIONS 

Internet of things assisted deep learning enabled driver drowsiness monitoring and alert system using CNN-LSTM framework

Authors: S.P. Soman, Sibu Philip G., Senthil Kumar G., S.B. Nuthalapati, Suri Babu S., Zafar Sherin, K.M. Abubeker K.M.
Journal: Engineering Research Express
Year: 2024

Holistic Analysis and Development of a Pregnancy Risk Detection Framework: Unveiling Predictive Insights Beyond Random Forest

Authors: N. Irfan Neha, S. Zafar Sherin, I. Hussain Imran
Journal: SN Computer Science
Year: 2024

Correction to: A transformer based real-time photo captioning framework for visually impaired people with visual attention

Authors: A.K.M. Kunju Abubeker Kiliyanal Muhammed, S. Baskar S., S. Zafar Sherin, S. Rinesh S., A. Shafeena Karim A.
Journal: Multimedia Tools and Applications
Year: 2024

A transformer based real-time photo captioning framework for visually impaired people with visual attention

Authors: K.M. Abubeker K.M., S. Baskar S., S. Zafar Sherin, S. Rinesh S., A. Shafeena Karim A.
Journal: Multimedia Tools and Applications
Year: 2024

 Enhancing Heart Health Prediction with Natural Remedies Through Integration of Hybrid Deep Learning Models

Authors: L.M.S. Akoosh Lamiaa Mohammed Salem, F. Siddiqui Farheen, S. Zafar Sherin, S. Naaz Sameena, M.A. Afshar Alam
Journal: Journal of Natural Remedies
Year: 2024

Synergistic Precision: Integrating Artificial Intelligence and Bioactive Natural Products for Advanced Prediction of Maternal Mental Health During Pregnancy

Authors: N. Irfan Neha, S. Zafar Sherin, I. Hussain Imran
Journal: Journal of Natural Remedies
Year: 2024

Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

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Dr. Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

Korea University Anam Hospital AI Center | South Korea

Publication Profile

Scopus

Google Scholar

INTRODUCTION 🧑‍🎓

Dr. Kwang-Sig Lee is a distinguished academician, research leader, and innovator specializing in the integration of medical and social informatics. Currently serving as Vice Center Chief at the AI Center of Korea University Anam Hospital, Dr. Lee’s groundbreaking research combines artificial intelligence with diverse datasets, such as genetic, image, numeric, and text data. His expertise in AI-driven systems has led to revolutionary work in healthcare, focusing on predictive AI models and multimodal machine learning. His work has earned significant recognition, influencing both academic circles and real-world medical applications.

EARLY ACADEMIC PURSUITS 🎓

Dr. Lee’s academic journey began at Kon Kuk University in Seoul, South Korea, where he earned a Bachelor’s degree in Economics and Physics (1994-1999), with a GPA of 3.52/4.00. He furthered his studies at Iowa State University (1999-2004), earning dual Master’s degrees in Economics and Sociology, graduating with a GPA of 3.69/4.00. Dr. Lee’s pursuit of advanced studies led him to Johns Hopkins University, where he obtained his Ph.D./MSE in Sociology and Applied Mathematics with a focus on health systems, securing a GPA of 3.63/4.00.

PROFESSIONAL ENDEAVORS 💼

Dr. Lee’s professional career spans across multiple prestigious institutions. At present, he holds the role of Vice Center Chief at Korea University’s AI Center in the Medical School. His previous roles include serving as a Research Associate Professor at the same institution, and Senior Research Fellow positions at various research agencies, including Acorn, Enliple, Agilesoda, and National Health Insurance Service. Dr. Lee has also worked as an Assistant Professor at Yonsei University and Sungkyunkwan University, contributing his expertise in preventive medicine and biostatistics.

CONTRIBUTIONS AND RESEARCH FOCUS ON ARTIFICIAL INTELLIGENCE 🧬

Dr. Lee’s contributions to the field of medical and social informatics are vast and impactful. His research primarily focuses on the application of artificial intelligence (AI) in healthcare, especially through the use of machine learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer models. His work explores the integration of genetic, image, numeric, and text data, thereby providing a more holistic approach to solving complex health-related challenges. Dr. Lee is known for his expertise in “Wide & Deep Learning,” a method that synthesizes multiple AI approaches to offer more powerful insights and predictive models.

IMPACT AND INFLUENCE 🌍

Dr. Lee’s innovative research has earned significant recognition both in academic and industrial circles. His work has been published in over 45 SCIE-indexed journals with a combined impact factor of 168. His Field-Weighted Citation Impact is 1.76, surpassing the average citation impact of KAIST in 2021. His expertise is frequently sought in both teaching and consultation, with Dr. Lee being an influential member of various academic committees. His ability to mentor graduate students and lead multidisciplinary research projects has significantly shaped the landscape of AI and healthcare.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Dr. Lee’s extensive publication record spans notable journals such as Cancers, European Radiology, International Journal of Surgery, and Journal of Medical Systems. His contributions have greatly impacted the scientific community, with a robust body of work related to medical AI, health informatics, and predictive modeling. In addition to his research articles, Dr. Lee has served as a guest editor for journals like Frontiers in Bioscience and Applied Sciences, as well as a reviewer for top-tier publications such as Nature Communications and Journal of Big Data.

HONORS & AWARDS 🏆

Throughout his academic career, Dr. Lee has been the recipient of numerous accolades, including full financial support during his tenure at Johns Hopkins University and Iowa State University. Additionally, he has been awarded for his academic excellence during his undergraduate studies at Kon-Kuk University. Dr. Lee’s consistent recognition for research excellence is evident from his impactful publications and active participation in the academic community, including his involvement in major research projects funded by government agencies.

FINAL NOTE ✨

Dr. Kwang-Sig Lee’s career is a testament to his dedication to advancing AI in medicine and social sciences. His expertise in combining machine learning with healthcare applications has paved the way for new innovations in predictive medicine, offering vital contributions to global healthcare systems. As he continues to lead research projects at the AI Center at Korea University, Dr. Lee’s legacy will be defined by his commitment to improving public health through cutting-edge technology and interdisciplinary research.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Dr. Lee’s future endeavors are poised to have a lasting impact on the fields of AI and healthcare. As the Vice Center Chief at one of the top medical schools, his work is expected to advance predictive healthcare models, fostering the development of more personalized and efficient healthcare solutions. With his expertise in “Wide & Deep Learning,” Dr. Lee is likely to continue influencing both the academic community and industry, shaping the future of AI-driven healthcare innovations.

TOP NOTES PUBLICATIONS 📚

Article: Graph Machine Learning With Systematic Hyper-Parameter Selection on Hidden Networks and Mental Health Conditions in the Middle-Aged and Old
  • Authors: K. Lee, Kwang-sig; B. Ham, Byung-joo
    Journal: Psychiatry Investigation
    Year: 2024
Article: A Machine Learning-Based Decision Support System for the Prognostication of Neurological Outcomes in Successfully Resuscitated Out-of-Hospital Cardiac Arrest Patients
  • Authors: S. Lee, Sijin; K. Lee, Kwang-sig; S. Park, Sang-hyun; S. Lee, Sung-woo; S. Kim, Sujin
    Journal: Journal of Clinical Medicine
    Year: 2024
Article: Clinical and Dental Predictors of Preterm Birth Using Machine Learning Methods: The MOHEPI Study
  • Authors: J. Park, Jung-soo; K. Lee, Kwang-sig; J. Heo, Ju-sun; K. Ahn, Ki-hoon
    Journal: Scientific Reports
    Year: 2024
Article: Explainable Artificial Intelligence on Safe Balance and Its Major Determinants in Stroke Patients
  • Authors: S. Lee, Sekwang; E. Lee, Eunyoung; K. Lee, Kwang-sig; S.B. Pyun, Sung Bom
    Journal: Scientific Reports
    Year: 2024

Feng Hu | Multi-modal feature recognition | Best Researcher Award

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Assoc Prof Dr. Feng Hu l Multi-modal feature recognition | Best Researcher Award

Communication University of China, China

Author Profile

Scopus

Early Academic Pursuits 🎓

Assoc. Prof. Dr. Feng Hu’s academic journey began with a deep interest in communication and information systems. He earned his Ph.D. in Communication and Information Systems from the prestigious Communication University of China (CUC), Beijing, in 2013. This educational foundation set the stage for his distinguished career in the fields of wireless communications, media convergence, and related technologies, shaping his future research and academic contributions.

Professional Endeavors and Contributions 🌐

Dr. Feng Hu is a prominent figure in the domain of 5G/6G wireless communications, and his professional journey has been marked by several key roles. Since December 2018, he has been an Associate Professor at Communication University of China and a master tutor, where he plays a significant role in mentoring future engineers and researchers. He has also been an active member of the Working Group of Radio, Film, and Television Administration for Wireless Interactive Radio and Television, as well as a member of the Working Group of 5G Broadcast. These positions have allowed him to contribute to the development and regulation of cutting-edge technologies in the media and communications sector.

Research Focus and Impact 🔬

Dr. Hu’s research interests lie in the development of transmitting and receiving techniques for 5G and 6G wireless communications. His work focuses on optimizing wireless communication systems, utilizing machine learning, and exploring optimization theory to enhance the efficiency and performance of modern communication technologies. His research has significant implications for the advancement of wireless communication systems, contributing to the global transition to next-generation technologies and improving communication capabilities in various sectors.

Technical Skills and Expertise ⚙️

Dr. Hu is highly skilled in the areas of wireless communications, machine learning, and optimization theory. His expertise includes developing novel algorithms and techniques for 5G/6G systems, addressing challenges in data transmission, signal processing, and system optimization. He is proficient in applying advanced mathematical models and machine learning approaches to improve communication systems’ performance, reliability, and security, making him a key player in advancing the state-of-the-art in wireless communications.

Teaching Experience and Mentorship 🍎

As an Associate Professor and master tutor, Dr. Hu is deeply involved in shaping the next generation of professionals in communication and information systems. He has taught a variety of undergraduate and graduate-level courses, imparting his knowledge in wireless communications, machine learning, and optimization. His mentorship extends beyond the classroom, guiding students in research and academic pursuits, while fostering a culture of innovation and critical thinking in the field of communications.

Legacy and Future Contributions 🌱

Dr. Hu’s legacy is rooted in his pioneering work in the development of 5G/6G wireless communication systems and his significant contributions to the academic and professional communities. Looking ahead, he aims to continue pushing the boundaries of wireless communication technologies, with a particular focus on optimizing next-generation communication networks and integrating machine learning approaches to improve system efficiencies. His future contributions will likely influence both academic research and practical implementations in the rapidly evolving fields of wireless communications and media convergence.

Academic Citations and Recognition 🏆

Dr. Feng Hu’s research has garnered recognition in top-tier academic journals and conferences in the fields of communication systems and wireless technology. His work has not only contributed to the scientific community but has also influenced industry practices and standards in wireless communication. He continues to be a sought-after figure in academic circles, providing valuable insights into the development of 5G/6G systems and machine learning applications in communications.

Professional Affiliations and Leadership 🌍

Dr. Hu is an active member of several esteemed organizations, including IEEE and the Society of Communications, where he holds the prestigious title of Senior Member. His involvement in key working groups related to wireless interactive radio and television and 5G broadcast further highlights his leadership in shaping the future of communication technologies. These affiliations enhance his ability to drive impactful research and contribute to the global dialogue on the future of communication systems.

Future Outlook and Innovation 🚀

With his vast expertise in wireless communication systems and emerging technologies, Dr. Hu’s future endeavors will focus on leading innovations in 6G communication systems, integrating artificial intelligence and machine learning to enhance system performance, and tackling the challenges posed by next-generation wireless networks. His ongoing research will play a critical role in shaping the future of global communication, advancing both academic theory and practical applications in the field.

 Top Noted Publications 📖

SDDA: A progressive self-distillation with decoupled alignment for multimodal image–text classification

Authors: Chen, X., Shuai, Q., Hu, F., Cheng, Y.
Journal: Neurocomputing
Year: 2025

EmotionCast: An Emotion-Driven Intelligent Broadcasting System for Dynamic Camera Switching

Authors: Zhang, X., Ba, X., Hu, F., Yuan, J.
Journal: Sensors
Year: 2024

 Asymptotic performance of reconfigurable intelligent surface assisted MIMO communication for large systems using random matrix theory

Authors: Hu, F., Zhang, H., Chen, S., Zhang, J., Feng, Y.
Journal: IET Communications
Year: 2024

Real-Time Multi-Service Adaptive Resource Scheduling Algorithm Based on QoE

Authors: Li, W., Li, S., Hu, F., Yin, F.
Conference: 2024 IEEE 12th International Conference on Information and Communication Networks, ICICN 2024
Year: 2024

5G RAN Slicing Resource Allocation Based on PF/M-LWDF

Authors: Hu, F., Qiu, J., Chen, A., Yang, H., Li, S.
Conference: 2024 4th International Conference on Computer Communication and Artificial Intelligence, CCAI 2024
Year: 2024

Jing An | Artificial Intelligence | Best Researcher Award

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Dr. Jing An | Artificial Intelligence | Best Researcher Award

Yancheng Institute of Technology, China

👨‍🎓Professional Profile

Scopus Profile

👨‍🏫 Summary

Dr. Jing An is a distinguished professor and master tutor at Yancheng Institute of Technology, China. He specializes in intelligent manufacturing engineering, industrial big data fault diagnosis, and residual life prediction. With numerous patents and software copyrights, Dr. An has published over 20 SCI/EI indexed papers and contributed to key academic texts. His pioneering research in artificial intelligence-based fault diagnosis has earned him prestigious awards, including first-place recognition in the China Commerce Federation Science and Technology Award .

🎓 Education

Dr. An holds a Ph.D. in Computer Science from Hohai University (2021) and a Master’s degree in Computer Science from Harbin University of Science and Technology (2006). His academic foundation has strongly influenced his research in AI and fault diagnosis.

💼 Professional Experience

Having joined Yancheng Institute of Technology in 2006, Dr. An is also the Vice President of Science and Technology for Jiangsu Province’s “Double Innovation Plan.” He has led numerous provincial-level projects, and his expertise has extended to more than 10 industry partnerships 🚀.

📚 Academic Citations

Dr. An has authored over 20 peer-reviewed papers in prestigious journals such as IEEE Access and Mathematical Problems in Engineering. His impactful research on AI-based fault diagnosis methods is frequently cited within the academic community .

🔧 Technical Skills

Dr. An is skilled in AI-based fault diagnosis, deep learning, machine learning, and industrial big data analytics. He has expertise in Convolutional Neural Networks (CNNs) and intelligent manufacturing systems, focusing on improving machinery reliability and efficiency .

🧑‍🏫 Teaching Experience

Dr. An has been recognized as an outstanding teacher twice at Yancheng Institute of Technology. He teaches courses in intelligent manufacturing engineering and industrial big data fault diagnosis, preparing students to advance in the field of AI and data science .

🔍 Research Interests

Dr. An’s research is focused on developing intelligent systems for fault diagnosis in rotating machinery, predictive maintenance, and the application of deep learning techniques in industrial big data. His work aims to enhance manufacturing processes and equipment reliability .

📖Top Noted Publications

Hybrid Mechanism and Data-Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics-Informed Neural Networks

Authors: Cheng, J., Lu, J., Liu, B., An, J., Shen, A.

Journal: Fatigue and Fracture of Engineering Materials and Structures

Year: 2024

Bearing Intelligent Fault Diagnosis Based on Convolutional Neural Networks

Authors: An, J., An, P.

Journal: International Journal of Circuits, Systems and Signal Processing

Year: 2022

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Authors: An, J., Ai, P., Liu, C., Xu, S., Liu, D.

Journal: IEEE Access

Year: 2021

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment

Authors: An, J., Ai, P.

Journal: Mathematical Problems in Engineering

Year: 2020

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning

Authors: An, J., Ai, P., Liu, D.

Journal: Shock and Vibration

Year: 2020