Osman Makkawi | Energy and Utilities Analytics | Best Researcher Award

Dr. Osman Makkawi | Energy and Utilities Analytics | Best Researcher Award

Liwa university | United Arab Emirates

Author Profile

Orcid

🧑‍🔬 Professional Summary

Dr. Osman Makkawi is an accomplished materials physicist and educator with over 10 years of experience in semiconductor materials, nanotechnology, and energy systems. His work focuses on 2D materials, optoelectronic devices, and graphene-based field-effect transistors (FETs). With a strong background in translational research, he has published extensively in high-impact journals and led collaborative innovation across academia and industry. He is passionate about graduate-level teaching and mentorship, aiming to inspire and develop future researchers in the field.

🔍 Research Interests

His primary research areas include emerging semiconductor devices and van der Waals heterostructures, synthesis of 2D materials for FET and optoelectronic applications, electrochemical energy storage, and sustainable hydrogen generation. Dr. Makkawi is particularly interested in applying nanotechnology to solve real-world energy challenges through translational research.

👨‍🏫 Professional Experience

Currently, Dr. Makkawi serves as an Assistant Professor of Physics & Applied Electric Circuit at Liwa College of Engineering, UAE (Jan 2023–Present), where he developed industry-relevant curricula and enhanced student engagement, increasing participation by 70%. He previously lectured at Sharjah Maritime Academy (2020–2023), where he significantly improved student pass rates through interactive teaching methods, and at the Academy of Engineering Science in Sudan (2008–2010), delivering courses in physics, chemistry, thermodynamics, and materials science.

🎓 Education

Dr. Makkawi earned his PhD in Material Physics and Chemistry from Harbin Institute of Technology, China (2013–2017), where he specialized in nanomaterial fabrication. He also holds an M.Sc. in Physics (Material Science) from Al-Neelian University, a Postgraduate Diploma in Education from the Open University of Sudan, and a B.Sc. in Physics (Honours) from the University of Khartoum.

🧪 Technical & Research Skills

His technical expertise includes 2D material fabrication (graphene, InSe, MoSe₂, h-BN), device applications such as supercapacitors, FETs, and hydrogen generation, and advanced characterization techniques (SEM, TEM, XRD, AFM, XPS, EDX). He is proficient in simulation and data analysis tools including COMSOL Multiphysics, OriginLab, and LabView.

📚 Teaching & Academic Service

Dr. Makkawi teaches graduate-level courses in advanced physics, nanotechnology, and electronic materials. He is actively involved in curriculum development that integrates modern industry needs, and he mentors graduate students in both research and professional development. He also serves as a peer reviewer for respected journals in nanotechnology and applied materials.

🌍 Professional Engagement

A regular participant in international conferences on materials science and sustainable energy, Dr. Makkawi collaborates with global research teams to develop advanced technologies for a greener future. His ongoing efforts contribute to a growing network of international academic and industry partnerships.

📖Publications

Optimized electrochemical performance and longevity in asymmetric supercapacitors using binder-free MOF-808/Ti₂N electrodes

Authors: Makkawi Osman; Md Rezaul Karim; Haseebul Hassan; Abdullatif Hakami; M. Musa Saad H.-E; M. Iqbal; Sidra Mumtaz
Journal: Journal of Energy Storage
Year: 2025

Enhanced photoresponse through van der Waals heterostructure integration: p-GaSe and n-MoSe₂ on h-BN substrate

Authors: Makkawi Osman; Haseebul Hassan; Muhammad Waqas Iqbal; Muhammad Hasnain Jameel; Samia Arain; Khaled Althubeiti; Mohammed Aljohani; Ehsan Elahi; Sidra Mumtaz
Journal: Journal of Materials Chemistry C
Year: 2024

Graphene Quantum Dots Decorated on Chromium Oxide and Zirconium Metal-Organic Framework Composite (GQDs@Zr-MOF/Cr₂O₃) for Asymmetric Supercapacitors and Hydrogen Production

Authors: H. Hassan; Misbah Shoaib; Khakemin Khan; Mohamed A. Ghanem; Makkawi Osman
Journal: Materials Chemistry and Physics
Year: 2024

Temperature optimization for enhancing the electrochemical performance of covalent triazine frameworks composite with Nb-based Mxene in asymmetric supercapacitors and hydrogen production

Authors: Makkawi Osman; Haseebul Hassan; Zubair Ahmad; Imad Barsoum; Sidra Mumtaz; Muhammad Waqas Iqbal; Ahmed Althobaiti; Alsharef Mohammad; Khakemin Khan
Journal: Journal of Energy Storage
Year: 2024

Enhanced ionic diffusion in a gold-augmented binary metal–organic framework composite with zirconium oxide for asymmetric supercapacitors and monosodium glutamate (MSG) detection

Authors: Haseebul Hassan; Muhammad Imran; Makkawi Osman; Abdullatif Hakami; Khakemin Khan; Ahmed Mahmoud Idris
Journal: Ionics
Year: 2024

Weiguo Cao | medical image processing | Best Innovation Award

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