Hamid Shahivandi | Computational Methods | Editorial Board Member

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Dr. Hamid Shahivandi | Computational Methods | Editorial Board Member

Shahed University | Iran

Hamid Shahivandi, Ph.D., is a passionate physicist specializing in computational materials science with a focus on perovskite solar cells. Based in Tehran, Iran, he has over a decade of academic experience as a researcher, lecturer, and laboratory supervisor. His innovative research combines precision and creativity, positioning him as a dedicated contributor to the fields of condensed matter physics and semiconductor technology.

Profile

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🎓 Early Academic Pursuits

Dr. Shahivandi embarked on his academic journey with a Bachelor’s in Physics from Lorestan University (2004–2008). He pursued further specialization in Solid-State Physics, completing his Master’s (2008–2011) and Ph.D. (2016–2020) at K. N. Toosi University of Technology, Tehran. His doctoral dissertation focused on the temperature-dependent performance of CH3NH3PbI3 perovskite solar cells, demonstrating his commitment to solving real-world challenges in renewable energy technologies.

💼 Professional Endeavors

Dr. Shahivandi has been an integral part of Shahed University since 2014, serving as both a Laboratory Supervisor and a Lecturer. His teaching portfolio spans foundational and advanced topics, including General Physics, Electricity and Magnetism, and Physical Properties of Materials. As a Teaching Assistant at K. N. Toosi University, he gained early exposure to educational excellence, fostering his skills in mentorship and pedagogy.

🔬 Contributions and Research Focus

Dr. Shahivandi’s research interests are deeply rooted in computational physics, with key contributions in:

  • Perovskite Solar Cells: Developing models to optimize performance and minimize degradation.
  • Carbon Nanotubes: Investigating catalytic growth mechanisms for double-walled carbon nanotubes.
  • Crystals: Studying the growth mechanisms of Calcium Fluoride and Germanium crystals.
    His theoretical and computational methodologies have led to several impactful publications in IEEE Journal of Photovoltaics and Solar Energy Materials & Solar Cells.

🌍 Impact and Influence

Dr. Shahivandi’s work on temperature effects and degradation mechanisms in perovskite solar cells has paved the way for more efficient renewable energy technologies. His insights into semiconductors and nanostructures have influenced peers and inspired collaborative research. His methodological rigor ensures that his findings resonate across academic and industrial communities.

🛠 Research Skills

Dr. Shahivandi excels in:

  • Computational Tools: Expertise in Molecular Dynamics Simulation and Density Functional Theory (DFT).
  • Analytical Techniques: Proficiency with Atomic Force Microscopy (AFM) and Vibrating-Sample Magnetometer (VSM).
  • Model Development: Skilled in mathematization and modeling of complex physical phenomena.
  • Project Management: Adept at leading and organizing multi-faceted research projects.

🏆 Awards and Honors

Dr. Shahivandi has been recognized for his scientific excellence and educational impact. His achievements include poster presentations at national nanoscience congresses and impactful research contributions published in leading journals.

🌟 Legacy and Future Contributions

Dr. Shahivandi’s legacy is marked by his dedication to advancing renewable energy technologies and materials science. Looking ahead, he aims to explore novel nanomaterials for energy applications and foster global collaborations to tackle pressing challenges in sustainable development.

Publication top notes

Temperature dependence of iodine vacancies concentration in CH3NH3PbI3 perovskite: A theoretical analysis

  • Authors: Hamid Shahivandi, Mohamadhosein Nosratjoo
    Journal: Physica B: Condensed Matter
    Year: 2024

Theory of light-induced degradation in perovskite solar cells

  • Authors: Hamid Shahivandi
    Journal: (No journal name provided)
    Year: 2020

Study of the effect of temperature on light-induced degradation in methylammonium lead iodine perovskite solar cells

  • Authors: Hamid Shahivandi, Majid Vaezzadeh, Mohammadreza Saeidi
    Journal: Solar Energy Materials and Solar Cells
    Year: 2020

Iodine Vacancy Formation Energy in CH3NH3PbI3 Perovskite

  • Authors: Hamid Shahivandi, Majid Vaezzadeh, Mohammadreza Saeidi
    Journal: IEEE Journal of Photovoltaics
    Year: 2020

Theoretical Study of Effective Parameters in Catalytic Growth of Carbon Nanotubes

  • Authors: Hamid Shahivandi, Majid Vaezzadeh, Mohammadreza Saeidi
    Journal: physica status solidi (a)
    Year: 2017

 

 

 

Fangxia Zhao | Computational Methods | Best Researcher Award

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Mrs. Fangxia Zhao | Computational Methods | Best Researcher Award

Associate Professor at Capital University of Economics and Business, China

👨‍🎓 Profiles

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Early Academic Pursuits 🎓

Dr. Fangxia Zhao embarked on her academic journey with a strong foundation in Transportation Engineering. Her advanced studies and research helped her gain a deep understanding of complex transportation networks and big data analytics. Over the years, she honed her expertise in the modeling of traffic systems, urban mobility, and data-driven optimization. Her academic pursuits, supported by several national-level projects, allowed her to make significant strides in theoretical research, laying the groundwork for her future professional achievements.

Professional Endeavors 💼

Dr. Zhao is currently an Associate Professor and Master’s Supervisor at the School of Management Engineering, where she also serves as the Head of the Department of Big Data. With years of academic leadership and research guidance, she has led cutting-edge projects funded by prestigious research bodies, including the Central University Research Fund and University Research Start-up Fund. Throughout her career, she has actively contributed to national and provincial research projects, consistently pushing the boundaries of transportation modeling and big data analytics.

Teaching Experience 👩‍🏫

Dr. Zhao is a dedicated educator, teaching courses such as:

  • Computer Network Technology and Applications
  • Data Structures
  • Principles and Applications of Databases
  • Python Programming Design
  • Green, Intelligent, and Shared Transportation

Her teaching focuses on equipping students with the skills needed to succeed in data science, network optimization, and smart transportation systems. She emphasizes hands-on learning and problem-solving, ensuring that her students are well-prepared for the challenges of modern transportation engineering.

Contributions and Research Focus 🔍

Dr. Zhao’s primary research interests include:

  • Complexity Modeling of Transportation Networks 🚗
  • Big Data Analysis in Transplantation 💉
  • Optimization of Urban Mobility 🏙️
  • Intelligent and Green Transportation 🌱

Her work has played a pivotal role in advancing transportation research, especially in the areas of electric vehicle behavior and network optimization. Through mathematical modeling, she has contributed to understanding how factors such as travel mode choice, vehicle scheduling, and urban road evolution influence the design of more efficient, sustainable, and intelligent transportation systems.

Academic Cites 📚

Dr. Zhao’s research has gained widespread recognition, particularly in the realms of transportation modeling and big data analytics. Her papers have been cited numerous times, including high-impact articles on the evolutionary dynamics of transportation networks, the role of electric vehicles, and the integration of bus services. Her work on the coevolution of population distribution and road networks has been particularly influential, establishing her as a key figure in the field of spatial economics and network theory.

Impact and Influence 🌟

Dr. Zhao’s influence in the academic community is reflected in her extensive publication record, including SCI-indexed papers in leading journals such as Physica A, Networks & Spatial Economics, and Plos One. With over 20 academic papers, she has made major contributions to the study of transportation networks, population distribution, and disaster prevention systems. Her research is widely cited, and her contributions are used by scholars and industry professionals to design smarter, more resilient transportation systems.

Technical Skills 💻

Dr. Zhao is a skilled data scientist, proficient in a variety of technical tools essential for big data analysis and computational modeling. Her expertise includes:

  • Python Programming 🐍
  • Database Management 🗄️
  • Network Design Optimization 🛠️
  • Data Visualization 📊
  • Algorithm Development ⚙️

These skills allow her to analyze complex datasets, develop robust optimization models, and design effective algorithms that improve transportation efficiency and sustainability. Additionally, her involvement in developing software like the School Bus Scheduling Solver and MaaS Systems highlights her technical prowess in real-world applications.

Invention Patents and Software Copyrights 💡

In addition to her research papers, Dr. Zhao holds a national invention patent for the Railway Disaster Prevention System and has developed two software copyrights:

  • School Bus Scheduling Solver
  • MaaS System Based on Knowledge Graphs

These patents and software showcase her ability to transform research ideas into practical solutions, driving innovation in the field of transportation safety and mobility services.Dr. Zhao’s legacy is marked by her pioneering work in the intersection of transportation, data science, and urban development, setting the stage for future breakthroughs in smart mobility and sustainable transportation systems.

Top Noted Publications

Multi-depot vehicle scheduling with multiple vehicle types on overlapped bus routes

  • Authors: Shang, H., Liu, Y., Wu, W., Zhao, F.
    Journal: Expert Systems with Applications, 2023

Role of electric vehicle driving behavior on optimal setting of wireless charging lane

  • Authors: Zhao, F., Shang, H., Cui, J.
    Journal: Physica A: Statistical Mechanics and Its Applications, 2023

Integration of conventional and customized bus services: An empirical study in Beijing

  • Authors: Shang, H., Chang, Y., Huang, H., Zhao, F.
    Journal: Physica A: Statistical Mechanics and Its Applications, 2022

Role of transportation network on population distribution evolution

  • Authors: Zhao, F.X., Shang, H.Y.
    Journal: Physica A: Statistical Mechanics and Its Applications, 2021

 

 

Muhammad Abubaker | Computational Methods | Best Researcher Award

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Mr. Muhammad Abubaker | Computational Methods | Best Researcher Award

PhD Scholar at Kyungpook National University, South Korea

Muhammad Abubaker is a dedicated researcher and Ph.D. candidate at Kyungpook National University (KNU), South Korea, specializing in computational fluid dynamics (CFD) and energy systems. His research primarily focuses on the Lattice Boltzmann Method (LBM) for simulating fluid dynamics, particularly in lithium-ion batteries, thermal management of electric vehicle (EV) batteries, and energy harvesting systems.

🎓Profile

🧑‍🎓 Early Academic Pursuits

Muhammad Abubaker’s academic journey has been marked by a strong foundation in Mechanical Engineering, starting with his undergraduate studies at Bahauddin Zakariya University, Multan, Pakistan, where he completed his B.Sc. in Mechanical Engineering. His early interest in thermal systems engineering was reflected in his M.Sc. at the University of Engineering and Technology, Taxila, where he researched the effect of vapor velocity on condensate retention on pin-fin tubes, a crucial study for improving heat transfer systems. His academic excellence during these years was recognized with multiple scholarships, including the MSc Scholarship from UET Taxila and later, the prestigious Ph.D. Kings Scholarship at Kyungpook National University, South Korea.

💼 Professional Endeavors

Abubaker’s professional journey includes a rich teaching career as a Lecturer at COMSATS University Islamabad, Sahiwal, Pakistan, where he taught courses on Thermodynamics, Fluid Mechanics, Power Plants, and Renewable Energy Technologies. His commitment to teaching excellence was reflected in his design of outcome-based education (OBE) courses, as well as his innovative hands-on approach to learning through semester projects on heat exchangers, power plant schematics, and aeroplane models. His contributions to curriculum design and ISO compliance further demonstrate his leadership within academia.

🧪 Contributions and Research Focus

Muhammad Abubaker’s primary research focus is in the development and application of Lattice Boltzmann Method (LBM) for simulating complex multicomponent fluid dynamics in various systems. His work on Li-ion battery wettability is groundbreaking, as it addresses key challenges in battery performance and safety. Through his innovative use of LBM, he has investigated the electrolyte wetting behavior in lithium-ion batteries, offering insights into optimizing battery designs for better performance and longevity.

Abubaker is also focused on thermal management of electric vehicle (EV) batteries—a crucial aspect of improving EV performance and energy efficiency. His research into thermal LBM in porous media and energy harvesting systems, such as solar panels and flexible structures, aims to push the boundaries of energy conversion and sustainability. His work on energy systems, particularly in solar energy technology and energy harvesters, is a testament to his commitment to advancing green energy solutions.

🌍 Impact and Influence

Abubaker’s research has had significant impact, particularly in the field of energy storage and battery technology, with implications for industries ranging from automotive to consumer electronics. His work on battery electrode-electrolyte interfaces is helping solve critical issues related to wettability and ion transport, thereby contributing to the development of more efficient and durable lithium-ion batteries.

📚 Academic Cites and Scholarly Contributions

Abubaker’s academic contributions are well-recognized in the scholarly community, as evidenced by his numerous journal publications in highly regarded peer-reviewed journals, such as Energy Reports, Thermal Science, and Applied Thermal Engineering. His Google Scholar Profile highlights the growing recognition of his work, with citations that underscore the relevance and impact of his research. Notable papers such as “Wetting Performance Analysis of Porosity Distribution in NMC111 Layered Electrodes in Li-Ion Batteries” and “Wetting Characteristics of Li-ion Battery Electrodes” have made significant strides in advancing battery technology and thermal management.

⚙️ Technical Skills

Abubaker is highly proficient in advanced computational techniques and tools essential for modern engineering and energy research. His technical skills in Lattice Boltzmann Method (LBM), COMSOL Multiphysics, Ansys, ICEM CFD, C++, and CUDA for parallel processing make him an expert in simulating and modeling complex systems. These skills are crucial for his work in energy harvesting, thermal systems, and fluid dynamics, particularly in the context of Li-ion battery performance, fluid-solid interaction, and energy conversion systems.

👨‍🏫 Teaching Experience and Mentorship

Abubaker’s academic career is not only defined by his research but also by his dedication to teaching and mentoring students. As a Lecturer, he developed and implemented Outcome-Based Education (OBE) courses, designed course assessments, and introduced hands-on project-based learning for students. His experience in mentoring final-year projects (including topics like PV panel cooling and ground-coupled heat exchangers) reflects his ability to guide students through complex engineering challenges.

🔮 Legacy and Future Contributions

Muhammad Abubaker is well on his way to leaving a lasting legacy in the fields of energy systems, thermal management, and computational fluid dynamics. His innovative use of Lattice Boltzmann Methods in energy storage and battery systems is paving the way for advancements in battery technology and electric vehicle efficiency.Looking ahead, his future contributions could play a pivotal role in addressing the global need for sustainable energy solutions. His ongoing work on energy harvesting and thermal systems optimization could lead to more efficient renewable energy technologies that are critical for a sustainable future.

📖Publication Top Notes

 

Jie Li | Computational Methods | Best Researcher Award

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Assoc. Prof. Dr. Jie Li | Computational Methods | Best Researcher Award

Teacher at Chongqing University of Science and Technology, China

Li Jie is an accomplished doctor, associate professor, and master’s supervisor at Shanghai Jiaotong University, where he also serves as a postdoctoral fellow. As the deputy director of the 2011 Collaborative Innovation Center for Smart Security in Chongqing, he leads initiatives in smart neurosurgery and participates actively in various professional committees related to artificial intelligence and smart transportation. An Associate Editor for IEEE Transactions on Emerging Topics in Computational Intelligence, he has contributed significantly to international conferences.

Profile🎓

Early Academic Pursuits🌱

Li Jie began his academic journey with a strong focus on artificial intelligence and smart technologies, laying a solid foundation for his future endeavors. His time at Tsinghua University and later at the University of Rhode Island enriched his understanding and broadened his research perspectives, preparing him for a distinguished career in academia and industry.

Professional Endeavors 💼

As a postdoctoral fellow at Shanghai Jiaotong University, Li Jie has undertaken significant leadership roles, including serving as the deputy director of the 2011 Collaborative Innovation Center for Smart Security in Chongqing. His involvement with the Smart Neurosurgery Group and various professional committees reflects his commitment to advancing healthcare through innovative technology and collaboration.

Contributions and Research Focus 🔍

Li Jie’s research primarily centers on smart security and neurosurgery, where he utilizes artificial intelligence to enhance medical practices. He has hosted 16 funded projects and has published over 40 academic papers in high-impact journals, showcasing his dedication to contributing valuable knowledge to the field.

Impact and Influence 🌍

With a reputation as a thought leader, Li Jie has made significant contributions that have influenced both academia and industry. His role as an Associate Editor for IEEE Transactions on Emerging Topics in Computational Intelligence and participation in various international conferences underscore his influence in shaping research agendas and fostering collaborations.

Academic Citations 📚

Li Jie’s work is widely recognized, as evidenced by his 40 published papers and the acclaim received for his book, “Artificial Intelligence.” His research has garnered citations that highlight its relevance and impact, establishing him as a respected figure in his field.

Technical Skills ⚙️

Possessing a robust set of technical skills, Li Jie excels in areas such as computational intelligence, data analysis, and machine learning. His expertise in securing over 40 invention patents demonstrates his innovative approach and practical application of technology in research.

Teaching Experience 👨‍🏫

As a master’s supervisor and associate professor, Li Jie has mentored numerous students, instilling in them a passion for research and innovation. His teaching methods emphasize practical applications of theory, preparing students for successful careers in technology and science.

Legacy and Future Contributions 🔮

Li Jie’s legacy is marked by his commitment to advancing smart technologies in healthcare. Looking ahead, he aims to expand his research collaborations internationally and engage in interdisciplinary projects, furthering the impact of his work on society and technology. His vision for the future underscores a dedication to innovation that will shape the next generation of researchers and practitioners.

Publication Top Notes📖

Metric learning based multi-branch network for tongue manifestation recognition
  • Authors: Ren, S., Wu, R., Luo, Q., Wang, Y., Li, J.
    Publication Year: 2024
FASCNet: An Edge-Computational Defect Detection Model for Industrial Parts
  • Authors: Li, J., Wu, R., Zhang, S., Chen, Y., Dong, Z.
    Publication Year: 2024
Multi-scale attention-based lightweight network with dilated convolutions for infrared and visible image fusion
  • Authors: Li, F., Zhou, Y., Chen, Y., Dong, Z., Tan, M.
    Publication Year: 2024
A Mixed-Precision Transformer Accelerator With Vector Tiling Systolic Array for License Plate Recognition in Unconstrained Scenarios
  • Authors: Li, J., Yan, D., He, F., Dong, Z., Jiang, M.
    Publication Year: 2024
A novel medical text classification model with Kalman filter for clinical decision making
  • Authors: Li, J., Huang, Q., Ren, S., Deng, B., Qin, Y.

           Publication Year: 2023