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

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👨‍💻 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

Lewis Njualem | Blockchain | Best Researcher Award

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Dr. Lewis Njualem l Blockchain | Best Researcher Award

California State University San Bernardino, United States

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DR. LEWIS A. NJUALEM: PIONEER IN SUPPLY CHAIN INNOVATION 🌍📊

EARLY ACADEMIC PURSUITS 🎓

Dr. Lewis A. Njualem embarked on an illustrious academic journey, earning a Ph.D. in Systems & Engineering Management from Texas Tech University in 2018. His dissertation, under the guidance of Dr. Milton Smith, explored the transformative effects of enterprise resource planning (ERP) systems on direct procurement in asset-intensive industries. Earlier, he obtained an MBA in Operations & Supply Chain Management from the University of Houston-Victoria and a Bachelor of Science in Computer Science with a focus on Information Systems. His academic foundation began with an Associate in Science from Houston Community College.

PROFESSIONAL ENDEAVORS & INDUSTRY EXPERIENCE 💼

With over 21 years of professional experience across industries such as mining, aerospace, energy, and telecommunications, Dr. Njualem is a recognized expert in ERP systems, specifically SAP MM, PP, PM, and PS modules. His work includes leading projects for companies like Rio Tinto, Glencore, and Caterpillar, where he implemented cutting-edge supply chain solutions. Notably, he served as a Lead Architect for New Gold Inc., managing SAP operations for globally operating mine sites.

His certifications as a SAP Certified Application Associate and APICS Certified Supply Chain Professional further validate his technical expertise and commitment to operational excellence.

CONTRIBUTIONS TO RESEARCH & ACADEMIA 📚

Dr. Njualem’s research focuses on supply chain sustainability, blockchain technology applications, and ERP usability improvements. His working paper on integrating blockchain with ERP systems highlights innovative solutions for enhancing transparency, traceability, and security in enterprise engineering change management.

As an Assistant Professor at California State University, San Bernardino, he develops and teaches courses in supply chain management, business analytics, and enterprise systems. His dedication extends to mentoring students, participating in the NSF STEM initiative, and actively contributing to departmental and university committees.

IMPACT AND INFLUENCE 🌟

Dr. Njualem’s influence extends beyond academia to the global supply chain industry. He has been recognized for his excellent oral presentation at the 2021 IEEE 8th International Conference on Industrial Engineering and Applications. As a reviewer for the International Journal of Supply and Operations Management, he continues to shape the field’s discourse.

His roles as SAP Faculty Director and disciplinary lead in STEM learning underscore his commitment to fostering innovation and knowledge dissemination in his field.

ACADEMIC CITES & TEACHING EXCELLENCE 🎓

Dr. Njualem has designed and taught numerous courses, including Advanced Enterprise Resource Planning, Applied Business Statistics, and Managing the Supply Chain. He is also celebrated for mentoring students toward SAP TERP 10 certifications and for integrating experiential learning into his teaching approach.

LEGACY AND FUTURE CONTRIBUTIONS 🌍

With a career spanning academia and industry, Dr. Njualem’s legacy is defined by his transformative contributions to ERP systems, supply chain optimization, and blockchain integration. His vision for the future includes enhancing global sustainability practices through innovative technologies and mentoring the next generation of leaders in supply chain management and business analytics.

Dr. Njualem’s work continues to bridge the gap between theoretical research and practical applications, ensuring lasting impact in both academia and industry.

TOP NOTED PUBLICATIONS 📖

Leveraging Blockchain Technology in Supply Chain Sustainability: A Provenance Perspective
    • Authors: LA Njualem
    • Journal: Sustainability
    • Year: 2022
Exploring the effects of enterprise resource planning systems on direct procurement: An upstream asset-intensive industry perspective
    • Authors: L Njualem, M Smith
    • Journal: International Journal of Supply and Operations Management (IJSOM)
    • Year: 2018
A Conceptual Framework of the Impact of Globalization on the Mining Industry Supply Chain Networks
    • Authors: LA Njualem, O Ogundare
    • Journal: 2021 IEEE 8th International Conference on Industrial Engineering and
    • Year: 2021
A sustainability model for globalized mining supply chain
    • Authors: LA Njualem, O Ogundare
    • Journal: International Journal of Supply and Operations Management
    • Year: 2023
An Exploratory Study About Integrating Enterprise Engineering Change Management into Blockchain Technology
    • Authors: LA Njualem, C Pandey
    • Journal: Journal of Theoretical and Applied Electronic Commerce Research
    • Year: 2025
A computational model for gender asset gap management with a focus on gender disparity in land acquisition and land tenure security
    • Authors: O Ogundare, L Njualem
    • Journal: arXiv preprint arXiv:2404.09164
    • Year: 2024

Sogand Dehghan | social network analysis | Best Innovation Award

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Ms. Sogand Dehghan | social network analysis | Best Innovation Award

Ms. Sogand Dehghan at K. N. Toosi University of Technology, Iran

👨‍🎓Professional Profiles

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👩‍💻 Summary

Ms. Sogand Dehghan an Information Technology specialist with expertise in data analysis and software development. My work primarily focuses on collecting, cleaning, and analyzing data from various sources to create actionable reports and dashboards for organizational decision-making. I am passionate about using data-driven strategies to help businesses achieve their goals, with a particular interest in social media analysis and its alignment with organizational objectives. Additionally, I enjoy developing data-driven software solutions that enhance operational efficiency.

🎓 Education

Ms. Sogand Dehghan earned my Master’s Degree in Information Technology from K.N. Toosi University of Technology (2019-2022) and my Bachelor’s Degree in Information Technology with a grade of 97% from Payame Noor University (2012-2016). My thesis, titled “Provision of an Efficient Model for Evaluation of Social Media Users Using Machine Learning Techniques,” focused on leveraging machine learning to assess social media engagement and user behavior.

💼 Professional Experience

Ms. Sogand Dehghan currently hold two key roles: as an Instructor at National Skills University, where I teach courses on Advanced Programming and Data Analysis (since Sep 2024), and as a Data Analyst at GAM Arak Industry, where I focus on data mining, machine learning, and visualizing data insights using tools like Power BI, Python, SQL Server, and SSRS (since Jan 2024). Additionally, I serve as a Software Developer at GAM Arak Industry, working with C#, ASP.NET Core, and SQL Server to build scalable software solutions (since Apr 2023). In my previous role at Kherad Sanat Arvand (Apr 2022 – Jun 2023), I honed my skills in data analysis and dashboard development.

📚 Academic Citations

My research has been published in prestigious journals. My paper, “The Credibility Assessment of Twitter Users Based on Organizational Objectives,” was published in Computers in Human Behavior (Sep 2024), where I developed a model for assessing the credibility of Twitter users by integrating profile data with academic sources like Google Scholar. Another notable publication, “The Evaluation of Social Media Users’ Credibility in Big Data Life Cycle,” appeared in the Journal of Information and Communication Technology (Sep 2023), in which I reviewed existing frameworks for evaluating social media user credibility.

🔧 Technical Skills

My technical skill set includes expertise in C#, ASP.NET, Python, and SQL Server for software development. I specialize in Data Visualization with Power BI, Data Mining, Machine Learning, and Social Network Analysis. Additionally, I have a solid foundation in Text Mining and Data Modeling, which enables me to provide comprehensive solutions for data-driven challenges in various organizational contexts.

👨‍🏫 Teaching Experience

As an Instructor at National Skills University, I teach Advanced Programming and Data Analysis. I focus on equipping students with the skills needed to thrive in the data-driven world of technology. My approach integrates real-world data problems with theoretical knowledge to help students apply their learning in practical scenarios.

🔍 Research Interests

My research interests lie in the intersection of Machine Learning and Social Network Analysis. I am particularly interested in developing models to evaluate social media user credibility, integrating heterogeneous data sources for organizational decision-making, and exploring the broader implications of big data in evaluating trust and influence within social networks.