Abdulaziz Almaktoom | Resilience modeling | Best Researcher Award

Assoc Prof Dr. Abdulaziz Almaktoom | Resilience modeling | Best Researcher Award

Effat University | Saudi Arabia

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INTRODUCTION 🌟

Dr. Eng. Abdulaziz Turki Almaktoom is a highly distinguished academic and professional in the fields of Operations and Supply Chain Management. Holding a Ph.D. in Industrial Engineering, Dr. Almaktoom is known for his exceptional leadership, consultancy expertise, and a profound impact in higher education. As an Associate Professor and Chair of the Business Administration Department at Effat University, he has not only contributed to the academic sphere but also played an integral role in shaping the future of education in Saudi Arabia. His diverse skills span across Operations Management, Supply Chain Management, Data Analytics, Project Management, Risk Management, and many more.

EARLY ACADEMIC PURSUITS 📚

Dr. Almaktoom’s academic journey began with a keen interest in engineering and operations, leading him to pursue a Bachelor’s in Engineering Technology at Riyadh College of Technology. He continued to excel in his studies, earning a Master’s degree in Engineering Technology from Pittsburg State University, USA, before pursuing a Ph.D. in Industrial Engineering from Wichita State University, USA. His doctoral research focused on the reliability, robustness, and resilience of complex supply chain systems, showcasing his deep commitment to innovative solutions in operations.

PROFESSIONAL ENDEAVORS 💼

Dr. Almaktoom’s career is marked by a seamless blend of academia and industry. He has held significant roles such as Associate Professor, Chair of the Business Administration Department at Effat University, and Consultant for several prestigious firms in Saudi Arabia. His expertise spans across Project Management (PMP®), Risk Management (RMP®), Lean Six Sigma, and Supply Chain Analysis (CSCA®), making him a sought-after figure in both the education and business sectors. His contributions have led to the development of cutting-edge programs and curricula, helping shape future leaders in business administration and engineering.

CONTRIBUTIONS AND RESEARCH FOCUS 🔍

Dr. Almaktoom’s research interests lie primarily in Operations and Supply Chain Management, with a focus on optimization techniques, systems simulation, forecasting, lean and six sigma, and quality control. He has published over 50 scientific articles in renowned international journals and conferences, contributing significantly to the field’s knowledge base. Dr. Almaktoom is particularly known for leveraging advanced methodologies like Artificial Intelligence, Metaheuristics, and Data Analytics to drive forward-thinking solutions in supply chain management.

IMPACT AND INFLUENCE 🌍

Through his innovative approach to curriculum design and leadership, Dr. Almaktoom has created a lasting impact on the education sector. He has been instrumental in the development of new programs, including Ph.D. and B.Sc. degrees in Operations and Supply Chain Management and Entrepreneurship. His influence extends beyond academia through his involvement with various organizations like the IEOM Society International and his role as an advisor and mentor to numerous students, helping them succeed both academically and professionally. His research and teaching continue to inspire students and professionals alike.

ACADEMIC CITATIONS AND PUBLICATIONS 📖

Dr. Almaktoom has gained significant recognition in the academic world for his publications, which have earned him numerous citations. Ranked among the top 20 scientists in Decision Science and Operations Management in Saudi Arabia in 2024, his work continues to influence both the academic and professional communities. His research papers, especially those related to supply chain optimization and risk management, have been highly regarded and cited by peers in the industry.

HONORS & AWARDS 🏆

Throughout his career, Dr. Almaktoom has received numerous prestigious awards. These include being recognized as the Best Graduate Student at Wichita State University in 2015, the recipient of multiple international honors, and being ranked among the top scientists in Saudi Arabia in 2024. His accolades also include recognition for his academic excellence, including awards such as the Alpha Pi Mu Industrial Engineering Honor Society and membership in various elite organizations such as the Golden Key International Honor Society.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

Dr. Almaktoom’s work has already established a strong legacy in the academic and professional sectors. His pioneering role in developing innovative programs and guiding students to success continues to set a high standard for excellence. Looking forward, he aims to further contribute to the research and development of sustainable and efficient solutions in operations and supply chain management, particularly through emerging technologies like AI and machine learning.

FINAL NOTE

Dr. Abdulaziz Turki Almaktoom’s career exemplifies the power of dedication, innovation, and leadership in academia and industry. With a robust track record of impactful contributions in education, research, and professional development, Dr. Almaktoom’s legacy will undoubtedly continue to inspire future generations of students, researchers, and professionals across the globe. His forward-thinking approach and commitment to excellence ensure that his influence will resonate for years to come.

TOP NOTES PUBLICATIONS 📚

Blockchain-Assisted Hierarchical Attribute-Based Encryption Scheme for Secure Information Sharing in Industrial Internet of Things
    • Authors: A. Sasikumar, L. Ravi, M. Devarajan, A. Selvalakshmi, A.T. Almaktoom, A.S. Almazyad, G. Xiong, A.W. Mohamed

    • Journal: IEEE Access

    • Year: 2024

Corrections to “Blockchain-Assisted Hierarchical Attribute-Based Encryption Scheme for Secure Information Sharing in Industrial Internet of Things”
    • Authors: A. Sasikumar, L. Ravi, M. Devarajan, A. Selvalakshmi, A.T. Almaktoom, A.S. Almazyad, G. Xiong, A.W. Mohamed

    • Journal: IEEE Access

    • Year: 2024

Deep Reinforcement Learning for Multiobjective Scheduling in Industry 5.0 Reconfigurable Manufacturing Systems
    • Authors: M. Bezoui, A. Kermali, A. Bounceur, S.M. Qaisar, A.T. Almaktoom

    • Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

    • Year: 2024

Hybrid Metaheuristics for Industry 5.0 Multi-Objective Manufacturing and Supply Chain Optimization
    • Authors: M. Bezoui, A.T. Almaktoom, A. Bounceur, S.M. Qaisar, M. Chouman

    • Journal: 21st International Learning and Technology Conference: Reality and Science Fiction in Education, L and T 2024

    • Year: 2024

Multiple criteria decision-making for determining the optimal wind farm site under uncertainty
    • Authors: A.T. Almaktoom, M.M. Samkari

    • Journal: International Journal of Critical Infrastructures

    • Year: 2024

 

xian Zhang | Geosciences | Best Researcher Award

Dr. xian Zhang | Geosciences | Best Researcher Award

Hunan University of Finance and Economics | China

 PUBLICATION PROFILE

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INTRODUCTION 🧑‍🏫

Dr. Xian Zhang is a distinguished academic in the field of information technology and management, currently serving as a Lecturer at the School of Information Technology and Management, Hunan University of Finance and Economics since 2023. With a robust educational background and a strong research profile, Dr. Zhang has made significant contributions to the field of electromagnetic data processing and signal identification. His research spans a wide range of topics, particularly focusing on the processing of magnetotelluric data and noise elimination methods.

EARLY ACADEMIC PURSUITS 🎓

Dr. Zhang embarked on his academic journey with a focus on computer science and engineering. He earned his D.D. from Shaoyang University in 2016, followed by an M.D. from Hunan Normal University in 2019. His academic pursuits culminated in a Ph.D. from Central South University in 2022, laying a strong foundation for his future research endeavors. These early years of study instilled in him a deep understanding of data analysis and computational methods, which he later applied to his work on electromagnetic data.

PROFESSIONAL ENDEAVORS 💼

Since 2023, Dr. Zhang has been contributing to the academic community as a Lecturer at the School of Information Technology and Management, Hunan University of Finance and Economics. His professional career has been characterized by a commitment to both teaching and groundbreaking research. In his role, he imparts knowledge to future professionals in the field, shaping the next generation of experts in data analysis and information technology.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Dr. Zhang’s research is centered on signal processing, with a particular emphasis on magnetotelluric and electromagnetic data. His work on separating magnetotelluric signals, utilizing advanced computational techniques like composite multiscale dispersion entropy and orthogonal matching pursuit, has garnered recognition within the scientific community. Additionally, his exploration of machine learning techniques, such as grey wolf optimization and detrended fluctuation analysis, has brought innovative approaches to electromagnetic signal identification and noise reduction.

IMPACT AND INFLUENCE 🌍

Dr. Zhang’s research has not only advanced the field of electromagnetic signal processing but also impacted the methods used in geophysics, specifically in noise elimination and feature extraction from complex data sets. His work has influenced both theoretical developments and practical applications in geophysical exploration. Furthermore, his interdisciplinary approach bridges the gap between data science, physics, and engineering, offering insights into improving electromagnetic signal processing technologies.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Dr. Zhang’s scholarly contributions are well-documented in numerous peer-reviewed journals. His work has been published in prestigious journals, including Earth Planets and Space, Acta Geophysica, Oil Geophysical Prospecting, Machine Learning: Science and Technology, and Geophysical Prospecting. His notable journal articles cover a wide range of topics, from noise removal techniques to advanced signal processing methods using machine learning algorithms. These publications have significantly contributed to the body of knowledge in the areas of signal processing and geophysical exploration.

HONORS & AWARDS 🏆

Dr. Zhang’s exceptional research efforts have been recognized with various accolades, including the prestigious Hunan Xiaohe Science and Technology Talent Award in 2024. This recognition underscores his outstanding contributions to science and technology, particularly in the realm of geophysical data processing and electromagnetic signal analysis. His work continues to inspire and influence future research in these fields.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

As Dr. Zhang continues to develop his research and academic career, his contributions to signal processing and electromagnetic data analysis are expected to have lasting effects on both academia and industry. His future work is poised to further bridge the gap between theoretical research and practical applications, particularly in environmental monitoring, resource exploration, and technological advancements in data processing. His legacy will be defined by his ability to solve complex scientific problems and inspire innovation in data-driven technologies.

FINAL NOTE 📝

Dr. Xian Zhang’s career reflects a deep commitment to advancing the field of electromagnetic signal processing. His impressive academic background, coupled with his ongoing professional contributions, solidifies his role as a leading figure in his field. With a growing portfolio of research, honors, and impactful publications, Dr. Zhang’s work continues to push the boundaries of what is possible in data analysis and signal processing. His future endeavors are sure to influence both academia and practical applications across various industries.

TOP NOTES PUBLICATIONS 📚

Controlled-source electromagnetic noise attenuation via a deep convolutional neural network and high-quality sounding curve screening mechanism
    • Authors: Yecheng Liu, Diquan Li, Jin Li, Xian Zhang

    • Journal: GEOPHYSICS

    • Year: 2025

Noise Elimination for Wide Field Electromagnetic Data via Improved Dung Beetle Optimized Gated Recurrent Unit
    • Authors: Zhongyuan Liu, Xian Zhang, Diquan Li, Shupeng Liu, Ke Cao

    • Journal: Geosciences

    • Year: 2025

Coordinate Attention-Temporal Convolutional Network for Magnetotelluric Data Processing
    • Authors: Jin Li, Hong Cheng, Jiayu Wang, Xian Zhang, Jingtian Tang

    • Journal: IEEE Transactions on Geoscience and Remote Sensing

    • Year: 2024

Intelligent processing of electromagnetic data using detrended and identification
    • Authors: Xian Zhang, Diquan Li, Bei Liu, Yanfang Hu, Yao Mo

    • Journal: Machine Learning: Science and Technology

    • Year: 2023

Deep structure of the Rongcheng geothermal field, Xiongan New Area: Constraints from resistivity data and boreholes
    • Authors: Yunqi Zhu, Diquan Li, Yanfang Hu, Xian Zhang, Fu Li, Feng Ma, Guiling Wang

    • Journal: Geothermics

    • Year: 2023

 

Benjamin Teo | Energy and Utilities Analytics | Best Researcher Award

Dr. Benjamin Teo | Energy and Utilities Analytics | Best Researcher Award

Imperial College London | United Kingdom

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👨‍🔬 Summary

Dr. Benjamin H. W. Teo is a dedicated researcher with a focus on sustainable energy technologies, adsorption science, and additive manufacturing. Currently a UKRI Postdoctoral Fellow at Imperial College London, he explores solar technology performance and its integration with other renewable systems. Dr. Teo’s research also extends to polymer crystallization, Metal-Organic Frameworks (MOFs), and their applications in energy systems. With over 18 published journal articles and several international conference presentations, he has become a leading expert in his field, combining theoretical modeling with practical, industry-oriented solutions to address climate change.

🎓 Education

Dr. Teo completed his Ph.D. in Mechanical Engineering from Nanyang Technological University (NTU), Singapore (2014-2019). His doctoral research focused on the green synthesis and modulation of MOFs to enhance water adsorption properties for cooling applications. Prior to this, he earned a Bachelor’s degree in Mechanical Engineering with First Class Honours from NTU (2011-2014), and a Diploma in Mechatronics from Temasek Polytechnic, Singapore (2006-2009).

💼 Professional Experience

Dr. Teo’s professional career has been marked by key roles in leading institutions. As a UKRI Postdoctoral Fellow at Imperial College London (Sep 2023 – Present), he investigates solar cell performance in combination with sustainable technologies and conducts advanced heat transfer simulations. From 2019 to 2023, he worked as a Research Fellow at Nanyang Technological University, leading studies on polymer crystallization in additive manufacturing and contributing to industry collaborations. He also held the role of Project Officer (2019) at NTU, where he conducted extensive research on water adsorption in MOFs and zeolites for cooling system applications.

📚 Academic Cites & Publications

Dr. Teo has contributed extensively to the academic community with 18 journal publications, including 10 as the first author. His work covers topics such as MOF-based adsorption cooling systems and additive manufacturing, with publications in prestigious journals like Applied Thermal Engineering and Journal of Industrial and Engineering Chemistry. His research has garnered significant attention, evidenced by citations in high-impact journals. He has also shared his findings at numerous international conferences, including as an invited keynote speaker.

🛠️ Technical Skills

Dr. Teo possesses a wide range of technical skills, including material characterization techniques like X-ray diffraction (XRD), BET nitrogen adsorption, and scanning electron microscopy (SEM). He is proficient in computational modeling, utilizing Grand Canonical Monte Carlo (GCMC) simulations, phase-field modeling, and thermodynamic frameworks via MATLAB. His expertise also extends to additive manufacturing, where he studies polymer crystallization, melt flow viscosity, and their implications for 3D printed materials.

👩‍🏫 Teaching Experience

Dr. Teo has a strong background in teaching, currently serving as a Graduate Teaching Assistant at Imperial College London (Apr 2024 – Present), where he leads revision lectures and tutorials on Fluid Mechanics. He also volunteered as a Tutor at Nanyang Technological University (Aug 2022 – May 2023), receiving exceptional student feedback. As a Research Mentor, he has guided over 30 students through their final-year projects, with many achieving high academic success. Additionally, he taught Gas Turbine Engine Labs and other courses during his time at NTU, earning recognition for his effective teaching.

🔬 Research Interests

Dr. Teo’s research interests include sustainable energy technologies, particularly solar photovoltaic systems and their integration with other green technologies. He is also deeply involved in additive manufacturing, especially in studying polymer crystallization and its impact on the mechanical properties of 3D printed materials. Additionally, his work in adsorption science focuses on the development of MOFs for water adsorption and cooling applications, aiming to enhance energy efficiency and contribute to climate change mitigation strategies.

📚 Top Notes Publications

Mesoscale simulations of spherulite growth during isothermal crystallization of polymer melts via an enhanced 3D phase-field model
    • Authors: Weidong Li, How Wei Benjamin Teo, Kaijuan Chen, Jun Zeng, Kun Zhou, Hejun Du

    • Journal: Applied Mathematics and Computation

    • Year: 2023

Investigation of polyamide 12 isothermal crystallization through the application of the phase‐field model
    • Authors: How Wei Benjamin Teo, Van Thai Tran, Kaijuan Chen, Kim Quy Le, Hejun Du, Jun Zeng, Kun Zhou

    • Journal: Polymers for Advanced Technologies

    • Year: 2023

Effects of build positions on the thermal history, crystallization, and mechanical properties of polyamide 12 parts printed by Multi Jet Fusion
    • Authors: H. W. B. Teo

    • Journal: Virtual and Physical Prototyping

    • Year: 2022

Non-isothermal crystallization behaviour of polyamide 12 analogous to multi-jet fusion additive manufacturing process
    • Authors: H. W. B. Teo

    • Journal: Polymer

    • Year: 2021

Experimental and modeling investigation on the viscoelastic-viscoplastic deformation of polyamide 12 printed by Multi Jet Fusion
    • Authors: H. W. B. Teo

    • Journal: International Journal of Plasticity

    • Year: 2021