Jin Wang | Renewable Energy Technologies Award | Best Researcher Award

Posted on by sciencefather

Dr. Jin Wang | Renewable Energy Technologies Award | Best Researcher Award

Doctoral candidate, Taiyuan University of Technology, China

Jin Wang, a doctoral candidate at Taiyuan University of Technology, is a promising researcher in the field of electrical engineering. Born on June 1, 1996, Jin is a member of the Han nationality and is deeply focused on coastal renewable energy generation. He is working towards his Ph.D. in Electrical Engineering and has actively contributed to advancing knowledge in energy systems. With a strong academic foundation and hands-on research experience, Jin is making significant strides in his field. 🧑‍🎓⚡🌍

Publication Profile

ORCID

Education:

Jin Wang completed his undergraduate degree in Electrical Engineering at Taiyuan University of Technology in 2020. Following this, he embarked on his Ph.D. journey at the same university, with an expected completion date in 2025. His academic career is distinguished by a dedication to innovation and the pursuit of sustainable energy solutions. 🎓🔌

Experience:

Jin Wang has been involved in a variety of research projects at Taiyuan University of Technology, with a focus on energy systems for polar regions and coastal renewable energy generation. He has also gained practical experience by contributing to national and provincial-level projects, particularly on clean, low-carbon energy systems. 💼🌱

Awards and Honors:

Jin has received several certifications that highlight his commitment to excellence. These include his achievements in English proficiency (CET-6, CET-4), as well as certifications in hydrogen energy technology and industrial technology enhancement. 🏅🎖️

Research Focus:

Jin’s research primarily revolves around coastal renewable energy generation, with specific attention to energy systems in extreme environments, such as polar regions. His work includes projects on energy systems for coastal research stations, hybrid energy systems, and proton exchange membrane fuel cells (PEMFC) in standalone systems. 🔋🌊

Conclusion:

Jin Wang is a dedicated researcher with a clear focus on sustainable energy solutions for challenging environments. His academic background, along with his involvement in cutting-edge research projects, positions him to make significant contributions to the field of renewable energy. 🌍💡

Publications:

Application and effect analysis of renewable energy in a small standalone automatic observation system deployed in the polar regions – AIP Advances, 2022, Author ranking: 1

Improving Proton Exchange Membrane Fuel Cell Operational Reliability Through Cabin-Based Fuzzy Control in Coastal Standalone Observation Systems in Antarctica – Journal of Marine Science and Engineering, 2025, Author ranking: 1

A Multi-Objective Scheduling Strategy for a Hybrid Energy System for Antarctic Coastal Research Stations – Journal of Marine Science and Engineering, 2024, Author ranking: 3

Research on output voltage control of PEMFC based on fuzzy active disturbance rejection – Modern Electronic Technology, 2024, Author ranking: 3

SangUn Kim | Human Actvity Recognition | Best Researcher Award

Posted on by sciencefather

Mr. SangUn Kim | Human Actvity Recognition | Best Researcher Award

Ph.D student, Soongsil University/Departments of smartwearable engineering, South Korea

SangUn Kim is a dedicated Ph.D. student at Soongsil University, specializing in smart wearable engineering. With expertise in wearable sensors, actuators, and electronic textiles, he is pushing the boundaries of technology in areas like pressure sensors, stretchable electronics, and VR applications. Throughout his academic journey, he has published over 10 SCI-indexed articles in high-impact journals and actively collaborates with multidisciplinary teams to innovate in the field. His work has earned him recognition in the research community, and he is focused on bridging the gap between cutting-edge research and practical, real-world applications in smart wearable technology. 🎓🧠💡

Publication Profile

Google Scholar

Education:

SangUn Kim is currently pursuing an integrated Master’s and Ph.D. program at Soongsil University in the Department of Smart Wearable Engineering. His research interests revolve around wearable technologies and advanced materials. 🎓📚

Experience:

SangUn Kim has extensive experience in researching smart wearable engineering, specializing in the development of stretchable sensors and human arm workout classification systems. His expertise extends to shape memory alloys and AI-based textile systems. Kim has contributed to over 25 research projects, six industry collaborations, and multiple patents in the wearable technology sector. 🛠️🤖

Awards and Honors:

SangUn Kim’s work has garnered significant recognition in his field. His contributions to smart wearable engineering have been published in prominent journals such as Materials, Sensors, Fashion and Textiles, and Polymers. Additionally, he holds several patents in the domain and is a respected member of the Korean Fiber Society. 🏅🥇

Research Focus:

Kim’s research focuses on developing innovative solutions in smart wearable technology. This includes designing advanced sensors, improving shape memory alloys for heating methods, and creating human arm workout classification systems using machine learning algorithms. His work in the wearable sector is instrumental in advancing fitness monitoring, actuator design, and e-textiles. 🔬🧵

Conclusion:

SangUn Kim is an ambitious and highly skilled researcher whose work stands at the forefront of wearable engineering and smart textiles. His passion for innovation and his dedication to creating real-world applications from advanced research positions him as a leader in the field of smart wearables. 🌟🚀

Publications:

Effects of 3D printing-line directions for stretchable sensor performances
CC Vu, TT Nguyen, S Kim, J Kim
Journal: Materials 14 (7), 1791
Published Year: 2021
Link to article
Cited by: 15

Human arm workout classification by arm sleeve device based on machine learning algorithms
S Chun, S Kim, J Kim
Journal: Sensors 23 (6), 3106
Published Year: 2023
Link to article
Cited by: 7

Improved heating method for shape-memory alloy using carbon nanotube and silver paste
SJ Kim, SU Kim, CC Vu, JY Kim
Journal: Fashion and Textiles 10 (1), 16
Published Year: 2023
Link to article
Cited by: 6

The programmable design of large-area piezoresistive textile sensors using manufacturing by jacquard processing
SU Kim, TTN Truong, JH Jang, J Kim
Journal: Polymers 15 (1), 78
Published Year: 2022
Link to article
Cited by: 6

Variable shape and stiffness feedback system for VR gloves using SMA textile actuator
SU Kim, SM Gu, J Kim
Journal: Fibers and Polymers 23 (3), 836-842
Published Year: 2022
Link to article
Cited by: 5

Analysis of driving forces of 3D knitted shape memory textile actuators using scale-up finite element method
SU Kim, J Kim
Journal: Fashion and Textiles 9 (1), 38
Published Year: 2022
Link to article
Cited by: 4

Comparative Performance Analysis of Inverse Phase Active Vibration Cancellation Using Macro Fiber Composite (MFC) and Vibration Absorption of Silicone Gel for Vibration Reduction
SU Kim, JY Kim
Journal: Polymers 15 (24), 4672
Published Year: 2023
Link to article
Cited by: 2

Measurement of 3D Wrist Angles by Combining Textile Stretch Sensors and AI Algorithm
JH Kim, BH Koo, SU Kim, JY Kim
Journal: Sensors 24 (5), 1685
Published Year: 2024
Link to article
Cited by: 1

Evaluation of Electrical Properties and Uniformity of Single Wall Carbon Nanotube Dip-Coated Conductive Fabrics Using Convolutional Neural Network-Based Image Analysis
E Kim, SU Kim, J Kim
Journal: Processes 12 (11), 2534
Published Year: 2024
Link to article
Cited by: 0

Fabrication of a Capacitive 3D Spacer Fabric Pressure Sensor with a Dielectric Constant Change for High Sensitivity
JE Lee, SU Kim, JY Kim
Journal: Sensors 24 (11), 3395
Published Year: 2024
Link to article
Cited by: 0

Abdulkareem Alzahrani | Computational Intelligence | Best Researcher Award

Posted on by sciencefather

Assoc. Prof. Dr. Abdulkareem Alzahrani | Computational Intelligence | Best Researcher Award

Associate Professor of Artificial Intelligence at CS Dept. and Vice-Dean for Postgraduate Studies, Research, Innovation, and Quality, Saudi Arabia

🎓 Dr. Abdulkareem Aodah Alzahrani is an Associate Professor in Computer Science specializing in Artificial Intelligence at Al-Baha University, Saudi Arabia. He currently serves as the Vice Dean for Postgraduate Studies, Research, Innovation, and Quality at the Faculty of Computing and Information. With a career spanning over 16 years, Dr. Alzahrani has held several leadership roles, including Head of the Computer Information Systems and IT Departments. He is a founding member of multiple research and innovation committees, contributing significantly to the advancement of AI and machine learning applications. 🌟

Publication Profile

Google Scholar

Education

📚 Dr. Alzahrani earned his Ph.D. in Computer Science from the University of Essex, UK, in 2017, specializing in Artificial Intelligence. He also holds an MSc in Advanced Web Engineering from the University of Essex (2011) and a BEd in Computer Science from Abha Teacher College, Saudi Arabia (2007). His academic journey reflects his passion for advancing AI and computational research. 🌍

Experience

💼 Dr. Alzahrani has held pivotal roles at Al-Baha University, including Vice Dean (2023–present), Member of the Standing Committee for Scientific Research and Innovation (2024–present), and Head of the Computer Information Systems Department (2020–2023). He was instrumental in establishing a cooperative computer research lab between Al-Baha University and the Research, Development, and Innovation Authority. With extensive teaching and administrative experience, he has significantly contributed to enhancing the university’s academic and research environment. 🌐

Awards and Honors

🏅 Dr. Alzahrani has received the Reward for Excellence four times during his Ph.D. studies, awarded by the Saudi Arabian Cultural Bureau in London. Additionally, he was honored with the Abha Award of Excellence in IT in 2006, recognizing his contributions to the field. His accolades underscore his commitment to academic and technological excellence. 🏆

Research Focus

🔍 Dr. Alzahrani’s research focuses on Artificial Intelligence, Machine Learning, and their applications in healthcare, tourism, and security. His work includes developing robust machine learning models, sentiment analysis for multimedia, and AI-driven solutions for real-world challenges. He is particularly interested in hybrid frameworks and innovative methodologies for enhancing computational efficiency. 🤖

Conclusion

🌟 Dr. Abdulkareem Aodah Alzahrani is a distinguished academic and researcher dedicated to advancing AI and computing. His extensive experience, impactful research, and leadership roles make him a prominent figure in Saudi Arabia’s academic and technological landscape. 🚀

Publications

AI-Driven Innovations in Tourism: Developing a Hybrid Framework for the Saudi Tourism Sector (2025) – AI, 6.1, DOI:10.3390/ai6010007.
Cited by: 7.

A Novel Outlier-Robust Accuracy Measure for Machine Learning Regression Based on Hassanat Distance Metric (2024) – DOI:10.21203/rs.3.rs-4492948/v1.
Cited by: 10.

A Novel Outlier-Robust Accuracy Measure for Machine Learning Regression Using a Non-Convex Distance Metric (2024) – Mathematics, 12.22, DOI:10.3390/math12223623.
Cited by: 15.

Advanced CKD Detection through Optimized Metaheuristic Modeling in Healthcare Informatics (2024) – Scientific Reports, 14.1, DOI:10.1038/s41598-024-63292-5.
Cited by: 20.

DeepSVDNet: A Deep Learning-Based Approach for Detecting and Classifying Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images (2024) – Computer Systems Science and Engineering, 48.2, DOI:10.32604/csse.2023.039672.
Cited by: 25.

Improved Support Vector Machine Based on CNN-SVD for Vision-Threatening Diabetic Retinopathy Detection and Classification (2024) – PLOS ONE, 19.1, DOI:10.1371/journal.pone.0295951.
Cited by: 18.

Aspect-Based Sentiment Analysis for Social Multimedia: A Hybrid Computational Framework (2023) – Computer Systems Science and Engineering, 46.2, DOI:10.32604/csse.2023.035149.
Cited by: 30.

Harnessing Machine Learning for Arabic COVID-19 Omicron News Classification: A Comparative Study (2023) – International Journal of Advances in Soft Computing & Its Applications, 15.2.

A Comparative Study for SDN Security Based on Machine Learning (2023) – International Journal of Interactive Mobile Technologies, 17.11, DOI:10.3991/ijim.v17i11.39065.
Cited by: 12.

Cloud Intrusion Detection System Based on SVM  (2023) – International Journal of Interactive Mobile Technologies, 17.11, DOI:10.3991/ijim.v17i11.39063.
Cited by: 14.

 

Xiaoping Yang | Network Communication | Best Researcher Award

Posted on by sciencefather

Dr. Xiaoping Yang | Network Communication | Best Researcher Award

Researcher, Beijing University of Technology, China

🎓 Dr. Xiaoping Yang is a dedicated researcher in computer science with expertise in distributed systems, wired and wireless networking, machine learning systems, and the Internet of Things (IoT). She is currently pursuing her Ph.D. at the Beijing University of Technology, focusing on cutting-edge technologies like heuristic algorithms, deep reinforcement learning, 6G networking, and recommendation systems. With a strong academic foundation and extensive professional experience, Dr. Yang is making significant contributions to cloud-edge cooperation and intelligent offloading technologies. 🌐

Publication Profile

Education

📚 Dr. Yang holds a Ph.D. in Computer Science and Technology (2022–Present) from the Beijing University of Technology. She also earned an M.S. in Software Engineering (2017–2020) from the same university and a B.E. in Computer Science and Technology (2013–2017) from Hebei University of Architecture and Engineering. Her academic journey reflects her unwavering commitment to excellence. 🏅

Professional Experience

💻 Dr. Yang worked as a Software Engineer at ByteDance (TikTok) in 2022, where she contributed to developing data governance systems and performing in-depth data analysis. Prior to this, she served as a Software Engineer at Kuaishou Technology (2020–2022), focusing on data tracking, storage, cleansing, and analysis. Her industry expertise underscores her ability to bridge research and real-world applications. 🚀

Awards and Honors

🏆 Dr. Yang’s accolades include being recognized as an Outstanding Graduate at the Provincial Level (Hebei Province, 2017) and winning First and Second Prizes in the Hebei Provincial Competition of the 8th China Computer Design Contest. Additionally, she received an Academic Scholarship for the 2022 Academic Year during her Ph.D. studies at the Beijing University of Technology. 🌟

Research Focus

🔍 Dr. Yang’s research interests span distributed systems, heuristic algorithms, deep reinforcement learning, mobile edge computing, 6G networking, edge caching, and deep learning-based recommendation systems. Her innovative contributions, especially in cloud-edge cooperation networks, reflect her commitment to advancing next-generation technologies. 🤖

Conclusion

🌟 Dr. Xiaoping Yang is a passionate academic and professional, making meaningful strides in computer science research and applications. Her exceptional academic achievements, industry expertise, and focus on innovative solutions position her as a rising leader in the field. 🌐

Publications

Task Partition-Based Intelligent Offloading for Cache-Assisted Cloud-Edge Cooperation Networks. GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 2023. [Cited by: N/A]

Task partition-based computation offloading and content caching for cloud–edge cooperation networks. Symmetry 16.7 (2024): 906. [Cited by: N/A]

Intelligent Task Offloading for Caching-Assisted UAV Networks.  2024 5th Information Communication Technologies Conference (ICTC). IEEE, 2024. [Cited by: N/A]

DRL-Based Green Task Offloading for Content Distribution in NOMA-Enabled Cloud-Edge-End Cooperation Environments.  ICC 2023-IEEE International Conference on Communications. IEEE, 2023. [Cited by: N/A]

 

Ahmed H.Ibrahim | Green technology | Best Researcher Award

Posted on by sciencefather

Dr. Ahmed H.Ibrahim | Green technology | Best Researcher Award

Lecturer, Azhar university, Egypt

Ahmed Hamdy Ibrahim Kraiz is an accomplished professional in the field of Metallurgical Engineering, specializing in Mineral Processing and Extractive Metallurgy. Born on February 10, 1987, in Mansoura, Egypt, he holds a Ph.D. from Shandong University of Science and Technology, China (2023), where his research focused on “Extraction and Reaction Mechanism of Valuable Metals from Egyptian Boiler Ash.” With a strong foundation in metallurgy and a passion for advancing his knowledge, Ahmed has held several key roles, including Metallurgical Consultant at Capital Leading Company (CLC) and Assistant Lecturer at Al-Azhar University. His work spans various industrial sectors, including oil and gas, mining, and nuclear materials, and he has a rich history of training and certifications in areas like welding, risk assessment, and industrial safety. 💼🎓

Publication Profile

ORCID

Education:

Ahmed’s academic journey is marked by impressive achievements, beginning with his Bachelor’s degree in Metallurgical Engineering from Al-Azhar University (2009), where he graduated with high distinction. He further advanced his studies with a Master’s degree in Metallurgical Engineering (2016), specializing in the pre-treatment of low-grade uranium-bearing granites. His most recent achievement is a Ph.D. in Mineral Processing and Extractive Metallurgy from Shandong University, China, where his research contributed significantly to the understanding of metal extraction from industrial waste. 🎓📚

Experience:

With over a decade of professional experience, Ahmed has excelled in diverse roles in the metallurgical and petroleum engineering sectors. Since 2019, he has served as a Metallurgical Consultant at Capital Leading Company (CLC), advising on oil and gas projects in the West Nile Delta. He also worked as an Assistant Lecturer at Al-Azhar University, where he contributed to the development of future engineers in the Metallurgical and Petroleum Engineering Department. His prior roles include Workshop Coordinator at Petropower Egypt and Metallurgical Engineer at the Nuclear Material Authority, where he focused on uranium mining in Egypt’s Eastern Desert. 🛠️📊

Awards and Honors:

Ahmed’s dedication and expertise have been recognized throughout his career. He received a series of certifications and training accolades, including his SNT-TC-1A Level II certification and welding course from Mansoura University. He also earned recognition for his research on metallurgical engineering, with his work contributing to advancements in metal extraction technologies. 🏆🔬

Research Focus:

Ahmed’s primary research interests revolve around Mineral Processing and Extractive Metallurgy, with a specific focus on the extraction and reaction mechanisms of valuable metals from industrial waste, such as Egyptian boiler ash. His academic research also includes studying the pre-treatment of low-grade uranium-bearing granites for efficient leaching processes. These contributions aim to improve metal recovery techniques, particularly in challenging materials. 🧪🔍

Conclusion:

Ahmed Hamdy Ibrahim Kraiz is a highly skilled and dedicated professional in Metallurgical Engineering, bringing valuable expertise to both academic and industrial settings. With a passion for innovation and a strong foundation in metallurgy, he is well-positioned to continue contributing to the field of extractive metallurgy and mineral processing. His proven leadership, commitment to learning, and ability to collaborate across cultures make him an asset to any organization. 🌍🤝

Publications:

Ching-Lung Fan | Deep Learning | Best Researcher Award

Posted on by sciencefather

Assoc. Prof. Dr. Ching-Lung Fan | Deep Learning | Best Researcher Award

Associate Professor, ROC Military Academy, Taiwan

Ching-Lung Fan is an associate professor in Civil Engineering at the Republic of China Military Academy. He completed his Ph.D. in 2019 from the National Kaohsiung University of Science and Technology. His professional journey reflects a strong dedication to advancing technology in the construction and civil engineering sectors, particularly through the application of machine learning and deep learning methods. 🏫

Publication Profile

Education

Dr. Fan holds a Master of Science (M.S.) from National Taiwan University (2006) and a Ph.D. from National Kaohsiung University of Science and Technology (2019). His academic background underscores his commitment to both theoretical and practical contributions to the field. 🎓

Experience

Dr. Fan started his academic career as an assistant professor at the Republic of China Military Academy in January 2019 and was promoted to associate professor in June 2022. His teaching and research experience has significantly impacted the study of civil engineering, especially through the integration of machine learning and data mining. 🏢

Awards and Honors

Ching-Lung Fan has received several prestigious awards, including the Phi Tau Phi Scholastic Honor (2019), Outstanding Paper Award (2021), Excellent Paper Award (2022), and Best Researcher Award (2024). In 2023, he was honored with membership in Sigma Xi, an esteemed scientific organization. 🏅

Research Focus

Dr. Fan’s research interests are primarily centered around machine learning, deep learning, data mining, construction performance evaluation, and risk management. His work integrates cutting-edge computational methods with civil engineering applications to enhance the quality and efficiency of construction projects. 🤖📊

Conclusion

Dr. Fan’s innovative contributions to civil engineering, particularly in the realm of AI-driven solutions, continue to shape the future of construction and infrastructure development. His ongoing research and recognition in the academic community highlight his expertise and impact in the field. 🌟

Publications

 Integrating image processing technology and deep learning to identify crops in UAV orthoimages. CMC-Computers, Materials & Continua. (Accepted).

Predicting the construction quality of projects by using hybrid soft computing techniques. CMES-Computer Modeling in Engineering & Sciences. (Accepted).

 Evaluation model for crack detection with deep learning—Improved confusion matrix based on linear features. Journal of Construction Engineering and Management (ASCE), 151(3): 04024210. (SCI).

 Evaluating the performance of Taiwan airport renovation projects: An application of multiple attributes intelligent decision analysis. Buildings, 14(10): 3314. (SCI).

Deep neural networks for automated damage classification in image-based visual data of reinforced concrete structures. Heliyon, 10(19): e38104. (SCI).

Multiscale feature extraction by using convolutional neural network: Extraction of objects from multiresolution images of urban areas. ISPRS International Journal of GeoInformation, 13(1): 5. (SCI).

Ground surface structure classification using UAV remote sensing images and machine learning algorithms. Applied Geomatics, 15: 919-931. (ESCI).

 Using convolutional neural networks to identify illegal roofs from unmanned aerial vehicle images. Architectural Engineering and Design Management, 20(2): 390-410. (SCI).

Evaluation of machine learning in recognizing images of reinforced concrete damage. Multimedia Tools and Applications, 82: 30221-30246. (SCI).

 Supervised machine learning–Based detection of concrete efflorescence. Symmetry, 14(11): 284. (SCI).

 

Zhaohai Ma | Differential Equation | Best Researcher Award

Posted on by sciencefather

Prof. Zhaohai Ma | Differential Equation | Best Researcher Award

Professor, China University of Geosciences, Beijing, China

🎓 Dr. Zhaohai Ma is an accomplished mathematician specializing in applied and fundamental mathematics. Currently an Associate Professor at the China University of Geosciences, Beijing, Dr. Ma is a prolific researcher and educator with significant contributions to the qualitative theory of differential equations and its applications. His work has garnered recognition through numerous publications and awards, showcasing his dedication to advancing mathematical sciences.

Publication Profile

Education

📚 Dr. Zhaohai Ma’s educational journey is marked by excellence in mathematics. He completed his Bachelor’s degree in Applied Mathematics at Yantai University (2009–2013). He then pursued a Master’s (2013–2016) and Ph.D. (2016–2019) in Fundamental Mathematics under the guidance of Professor Yuan Rong at Beijing Normal University, solidifying his expertise in mathematical theories.

Experience

👨‍🏫 Since 2019, Dr. Ma has been serving as an Associate Professor at the School of Science, China University of Geosciences, Beijing. He is also a Doctoral Supervisor, mentoring students in mathematical modeling and guiding them to achieve accolades in national competitions. Dr. Ma’s leadership and expertise have resulted in over 20 SCI-indexed publications and involvement in significant national and institutional research projects.

Awards and Honors

🏆 Dr. Ma’s achievements include winning the “Advanced Individual” title at the China Graduate Mathematical Contest in Modeling in 2020. As a guest Mathematical Reviewer for the American Mathematical Society, he continues to contribute to the global mathematical community through his academic insights.

Research Focus

🔬 Dr. Ma focuses on applied research in the qualitative theory of differential equations. His research encompasses reaction-diffusion equations, stability analysis of traveling wave solutions, age-structured population dynamics, biomathematical model dynamics, and delay differential equations. His work significantly impacts fields like epidemiology, ecological systems, and applied mathematical modeling.

Conclusion

🌟 Dr. Zhaohai Ma’s passion for mathematics, combined with his extensive research contributions, has made him a respected figure in the mathematical sciences. His dedication to teaching, mentoring, and advancing applied mathematics ensures his lasting influence on the field and future generations of mathematicians.

Publications 📚

Asymptotic stability of the nonlocal diffusion equation with nonlocal delay, Math. Meth. Appl. Sci., 48(2025), 1281-1302.

Boundedness and non-existence of traveling wave solutions for a four-compartment lattice epidemic system with exposed class and standard incidence, Math. Meth. Appl. Sci., 47(2024), 7397-7403.

Asymptotic behavior of a delayed nonlocal dispersal Lotka-Volterra competitive system, J. Appl. Anal. Comput., (2024).

Hopf bifurcation of an age-structured hand-foot-mouth disease model in a contaminated environment,Internat. J. Bifur. Chaos Appl. Sci. Engrg., 34(2024), 2450196(24 pages).

Global asymptotic stability for Gurtin-MacCamy’s population dynamics model, Proc. Amer. Math. Soc., 152(2024), 765-780.

Stationary distribution of a stochastic three species predator–prey model with antipredator behavior, Journal of Applied Mathematics and Computing, 70(2024), 1365-1393.

Traveling waves for a nonlocal dispersal SIRS epidemic model with age structure, AIMS Mathematics, 9(2024), 8001-8019.

Stability of planar traveling waves for a class of Lotka–Volterra competition systems with time delay and nonlocal reaction term, Qual. Theory Dyn. Syst., 22(2023), 1-25.

Traveling waves for a nonlocal dispersal susceptible–infected–recovered epidemic model with the mass action infection mechanism, Math. Meth. Appl. Sci., 46(2023), 18837-18860.

Traveling waves of predator–prey system with a sedentary predator, Z. Angew. Math. Phys., 74(2023), 1-24.

 

 

Dongmei Li | photocatalysis | Best Researcher Award

Posted on by sciencefather

Dr. Dongmei Li | photocatalysis | Best Researcher Award

Associate professor, Inner Mongolia University of Science and Technology, China

🌟 Dongmei Li is an Associate Professor at the School of Chemistry and Chemical Engineering, Inner Mongolia University of Science & Technology. With a strong academic background and extensive research experience, she has contributed significantly to the fields of photocatalysis and electrocatalysis. Throughout her career, she has led numerous research projects and published multiple journal articles, receiving recognition for her pioneering work in nanocomposites and catalytic materials. Dongmei is committed to advancing sustainable technologies and fostering innovative solutions through her research.

Publication Profile

ORCID

Education

🎓 Dongmei Li completed her Ph.D. in Applied Chemistry at East China University of Science and Technology (2005), after earning her Master’s in Chemical Engineering from Tianjin University (2002) and Bachelor’s in Fine Chemical Engineering from the University of Jinan (1999). Her diverse educational background laid the foundation for her outstanding contributions to chemical engineering research.

Experience

💼 Dongmei Li has a rich professional journey spanning over 20 years. She has been an Associate Professor at Inner Mongolia University of Science & Technology since 2019. Prior to this, she served at the University of Jinan from 2005 to 2019. In 2016-2017, she was a visiting scholar at Utah State University, where she further honed her research in catalysis. Throughout her career, she has also been actively involved in research and innovation, leading several funded projects.

Awards and Honors

🏆 Dongmei Li has received multiple accolades for her contributions to science. Notably, she is a recipient of the National Natural Science Foundation of China grant, Inner Mongolia Autonomous Region Science and Technology Plan Project, and has authored a book titled “Research on Chemical Engineering Technologies” (ISBN: 9787030333575). Her excellence in research has also been recognized in industry collaborations and various science awards.

Research Focus

🔬 Dongmei Li focuses on photocatalysis and electrocatalysis, particularly in the synthesis of MOFs, COFs, and nanocomposites. Her research explores the photocatalytic and electrocatalytic properties of these materials to advance environmental sustainability and energy efficiency. She leads several ongoing research projects funded by prestigious organizations, such as the National Natural Science Foundation of China and the Inner Mongolia Autonomous Region Science and Technology Plan Project.

Conclusion

🌱 With a commitment to scientific advancement, Dongmei Li continues to push the boundaries of applied chemistry and chemical engineering. Her work contributes to innovations in energy and environmental sustainability, marking her as a prominent researcher in her field.

Publications:

Novel noble-metal-free CdIn2S4/MoB Schottky heterojunction photocatalysts with efficient charge separation for boosting photocatalytic H2 production (2025) – Separation and Purification Technology
DOI: 10.1016/j.seppur.2024.129057

Synthesis of Co/Ni-MOFs with mixed ligands and their Oxygen Evolution Reaction (OER) performance (2025) – Journal of Molecular Structure
DOI: 10.1016/j.molstruc.2024.140549

Synthesis, insecticidal evaluation, crystal structure and theoretical calculations of nine/ten-membered carbon bridged neonicotinoid analogues (2025) – Journal of Molecular Structure
DOI: 10.1016/j.molstruc.2024.139898

Thiazolo[5,4-d]thiazole-Based Covalent Organic Frameworks for the Rapid Removal of RhB (2025) – Catalysts
DOI: 10.3390/catal15010042

Thiazolo[5,4-d]thiazole conjugated viologens for hydrogel-type all-in-one electrochromic devices (2024) – Research on Chemical Intermediates
DOI: 10.1007/s11164-024-05419-x

Novel noble-metal-free NiCo2O4/CdIn2S4 S-scheme heterojunction photocatalyst with redox center for highly efficient photocatalytic H2 evolution (2024) – Applied Surface Science
DOI: 10.1016/j.apsusc.2024.160895

Molecular engineering of π-extended viologens consisting of oxadiazoles-based bridges for highly stable electrochromic devices (2024) – Journal of Molecular Structure
DOI: 10.1016/j.molstruc.2024.138578

Cu/Fe-MOFs based on mixed ligands: Synthesis, crystal structure and electrocatalytic hydrogen evolution performance (2024) – Journal of Molecular Structure
DOI: 10.1016/j.molstruc.2024.137968

Preparation of amorphous Bi4V0.2Ti2.8O12 and its photocatalytic activity for the degradation of Basic Red 2 (2022) – Research on Chemical Intermediates
DOI: 10.1007/s11164-022-04765-y

 

JUNYI LIU | Petroleum Engineering | Best Researcher Award

Posted on by sciencefather

Dr. JUNYI LIU | Petroleum Engineering | Best Researcher Award

Chief Expert, Shengli Petroleum Engineering Corporation Limited, SINOPEC, China

Junyi Liu is a highly skilled Petroleum Engineer at Shengli Petroleum Engineering Corporation Limited, SINOPEC, with a focus on Oil and Gas Drilling Engineering, Oilfield Chemistry, and Environmental Protection. He holds a PhD in Oil and Gas Drilling Engineering from China University of Petroleum (East China), awarded in 2016, and a Bachelor’s degree in Petroleum Engineering from the same institution. With years of experience, Junyi is dedicated to developing advanced techniques in drilling fluid treatment and environmental protection in the oil and gas industry. 🌍💧

Publication Profile

Scopus

Education

Junyi Liu completed his Ph.D. in Oil and Gas Drilling Engineering from China University of Petroleum (East China) in 2016. Prior to that, he obtained his Bachelor’s degree in Petroleum Engineering from the same institution in 2010. 🎓🛢️

Experience

Since November 2016, Junyi has been serving as a Petroleum Engineer at Shengli Petroleum Engineering Corporation Limited, SINOPEC, where he specializes in drilling fluid technology, environmental protection, and innovative oilfield solutions. His work in the industry focuses on improving drilling efficiency while minimizing environmental impact. 💼🔧

Awards and Honors

Throughout his career, Junyi Liu has contributed to the advancement of petroleum engineering, particularly in the areas of drilling technology and environmental sustainability. His work has led to recognition in the field, although specific awards are not listed in the provided details. 🏆🌿

Research Focus

Junyi’s research is centered around Oil and Gas Drilling Engineering, Oilfield Chemistry, and Environmental Protection. He has worked extensively on drilling fluid treatment technologies and sustainable practices to protect the environment, with particular attention to water-based drilling fluids and filtration reducers. His innovations also include pressure-response lubricants for drilling fluids and the use of phase-change heat storage for deep-well cooling. 🔬🌱

Conclusion

With a solid educational background and extensive industry experience, Junyi Liu continues to make impactful contributions to the petroleum engineering sector. His work stands at the intersection of technological advancement and environmental sustainability, making him a key player in improving the oilfield industry’s operational and ecological performance. 💡🌍

Publications

Research and Application of Environmental Protection Technologies for Drilling Fluid Treatment in Shengli Oilfield, PETROLEUM DRILLING TECHNIQUES, 2024, 52(3): 47-52.

Targeted Pressure-Response Encapsulated Lubricants for Water-Based Drilling Fluids, Natural Gas Industry, 2023, 43(12): 91-99.

Synthesis and Characterization of Micro-Nano Environmental Friendly Filtration Reducer for Water-Based Drilling Fluids, Fresenius Environmental Bulletin, 2022, 31(10): 10046-10055.

Experimental Study of Drilling Fluid Cooling in Deep Wells Based on Phase Change Heat Storage, PETROLEUM DRILLING TECHNIQUES, 2021, 49(1): 53-58.

Hau-Kun Jhuang | Space data analysis | Outstanding Scientist Award

Posted on by sciencefather

Dr. Hau-Kun Jhuang | Space data analysis | Outstanding Scientist Award

Senior Scientist, Alpha Ring Asia Incorporation, Taiwan

Hau-Kun Jhuang is a Senior Scientist at Alpha Ring Asia INC. in Taipei, Taiwan, with a strong background in space science and plasma physics. He has dedicated over a decade to researching ionospheric anomalies and their relationships with earthquakes. His expertise includes the study of ionospheric total electron content (TEC) anomalies, plasma waves, and tidal wave analysis. With a passion for integrating artificial intelligence, Jhuang utilizes machine learning models such as Long Short-Term Memory (LSTM) networks to predict earthquake-related phenomena. 🌌📡

Publication Profile

Google Scholar

Education

Jhuang holds a Doctor of Philosophy in Space Science from the Graduate Institute of Space Science, National Central University (2014). His dissertation focused on ionospheric anomalies during significant earthquakes in Taiwan and China. He completed his Master’s degree in Space Science at the same institution in 2004 and earned a Bachelor’s degree in Physics from Fu Jen Catholic University in 2002. 🎓📚

Experience

Jhuang has extensive experience in both academic and industrial research. He currently serves as a Senior Scientist at Alpha Ring Asia INC. and previously held postdoctoral positions at the Institute of Earth Science, Academia Sinica, and National Taiwan University. His career also includes teaching positions in high schools and international collaborations with leading institutions such as LPC2E/CNRS in France. 🧑‍🔬🌍

Awards and Honors

Throughout his career, Jhuang has contributed significantly to the field of space science, receiving various recognitions. His research on seismo-ionospheric anomalies and AI-based earthquake prediction has been widely recognized and published in high-impact journals. 🌟🏆

Research Focus

Jhuang’s primary research interests include plasma physics, ionospheric physics, and seismo-ionospheric anomalies. He explores the dynamics between neutrals and charged particles, ionospheric tidal waves, and the use of machine learning for earthquake prediction. His work also delves into the impact of large earthquakes on ionospheric behavior. ⚡🌍

Conclusion

With a career spanning multiple fields of space and earth sciences, Hau-Kun Jhuang continues to push the boundaries of ionospheric research and artificial intelligence in geophysics. His work has contributed to improving our understanding of the ionosphere’s behavior during natural disasters like earthquakes. 🌏🔬

Publications

Driving Source of Change for Ionosphere before Large Earthquake – Vertical Ground Motion. Remote Sensing, 15(18), 4556. Link to article (SCI, IF=5.0)

Deep learning of detecting ionospheric precursors associated with M ≥ 6.0 earthquakes in Taiwan. Earth and Space Science, 9, e2022EA002289. Link to article (SCI, IF = 3.68)

Ionospheric peaked structures and their local-time, seasonal, and solar activity dependence based on Global Ionosphere Maps. J. Geophys. Res. Space Phys., 124, 7994-8014. Link to article (SCI, IF = 2.75)

Ionospheric tidal waves observed from Global Ionosphere Maps: analysis of total electron content. J. Geophys. Res. Space Phys., 123, 6776-6797. Link to article (SCI, IF = 2.75)

Ionospheric density and velocity anomalies before M ≥ 6.5 earthquakes observed by DEMETER satellite. J. Asian Earth Sci., 166, 210-222. Link to article (SCI, IF = 2.762)

Seismo-ionospheric anomalies in total electron content of the GIM and electron density of DEMETER before the 27 February 2010 M8.8 Chile earthquake. J. Adv. Space Res. Link to article (SCI, IF = 1.746)

Seismo-ionospheric anomalies of the GPS-TEC appear before the 12 May 2008 magnitude 8.0 Wenchuan Earthquake. Int. J. Remote Sensing, 31(13), 3579-3587. Link to article (SCI, IF = 2.493)