Afrah Yahya Al Rezami | Data Analysis | Best Scholar Award

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Assoc. Prof. Dr. Afrah Yahya Al Rezami | Data Analysis | Best Scholar Award

University professor at Prince Sattam bin Abdulaziz University, Saudi Arabia

Assoc. Prof. Dr. Afrah Yahya Mohammed Al Rezami is a Yemeni academic specializing in Applied Statistics, currently serving at the College of Science and Humanities in Al Aflaj, Prince Sattam Bin Abdulaziz University, Saudi Arabia. She earned her Ph.D. and M.A. in Statistics from Al-Mustansiriya University, Iraq, and holds a Bachelor’s degree in Statistics from Sana’a University, Yemen. With extensive experience in statistical analysis, research supervision, and academic leadership, Dr. Al Rezami has held various roles, including Head of the Measurement and Evaluation Department and Supervisor of the Scientific Research Unit. Her expertise includes performance indicators, educational evaluation, and statistical modeling, and she has taught a wide range of undergraduate and graduate-level courses. Dr. Al Rezami is also an active member of data and research committees and has participated in numerous training workshops related to data analysis and statistical software.

Professional Profile

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Education

Assoc. Prof. Dr. Afrah Yahya Mohammed Al Rezami possesses a robust academic background in the field of statistics, spanning undergraduate to doctoral levels. She began her academic journey by earning a Bachelor’s degree in Statistics from Sana’a University, Yemen, in 1992, where she acquired foundational knowledge in statistical theory and quantitative analysis. Driven by her passion for the discipline, she pursued graduate studies at Al-Mustansiriya University in Iraq, obtaining her Master’s degree in Statistics in 2000. Her master’s work focused on enhancing her skills in data analysis, statistical modeling, and research methodologies. Building upon this, she continued her scholarly pursuits at the same university and was awarded a Ph.D. in Statistics in 2004. During her doctoral studies, she specialized in Applied Statistics, further strengthening her analytical capabilities and laying the groundwork for her future contributions in teaching, research, and institutional development.

Experience

Assoc. Prof. Dr. Afrah Yahya Mohammed Al Rezami has accumulated extensive academic and professional experience in the field of applied statistics, both in Yemen and Saudi Arabia. Her career began as an Instructor and later Assistant Professor in the Department of Statistics and Information at the College of Commerce and Economics, Sana’a University, Yemen. She transitioned to Saudi Arabia, where she joined Prince Sattam Bin Abdulaziz University (PSAU) in 2012, taking on multiple academic and administrative roles. At PSAU’s College of Science and Humanities in Al Aflaj, she has served as an Assistant Professor and currently holds the rank of Associate Professor in the Department of Mathematics. In addition to her teaching duties, Dr. Al Rezami has contributed significantly to academic development and quality assurance. She has served as the Head of the Measurement and Evaluation Department at the Applied College in Al Kharj, where she led efforts to assess academic programs and student performance. She is also the Supervisor of the Scientific Research Unit and an active member of the Data and Statistics Unit at the College of Humanities and Social Sciences. Her responsibilities have included overseeing statistical analysis for master’s and doctoral theses, evaluating institutional performance indicators, and participating in various workshops related to SPSS, Excel, Minitab, and Power BI. With a diverse teaching portfolio spanning statistical inference, linear programming, actuarial mathematics, and software-based analysis, Dr. Al Rezami continues to play a vital role in both instructional and institutional development at PSAU.

Research Interests

Assoc. Prof. Dr. Afrah Yahya Mohammed Al Rezami’s research interests are deeply rooted in the field of Applied Statistics, with a strong focus on data-driven approaches to support decision-making in education, institutional development, and social sciences. She is particularly engaged in educational measurement and evaluation, where she analyzes academic performance indicators and develops effective assessment strategies to enhance the quality of learning outcomes. Dr. Al Rezami is also skilled in statistical modeling and multivariate data analysis, supporting graduate students and faculty through the design and interpretation of complex datasets in master’s and doctoral research. Her interest in statistical software applications such as SPSS, Excel, Minitab, and Power BI reflects her dedication to practical analytics and modern data visualization techniques. In addition, she explores areas such as risk analysis, actuarial mathematics, and probability theory, applying these tools to real-world challenges in education and beyond. Her interdisciplinary approach allows her to contribute to both academic research and institutional improvement through informed statistical insight.

Top Noted Publications

Bayesian Estimation of the Pareto Model Based on Type-II Censoring Data by Employing Non-linear Programming

  • Authors: L.A. Al-Essa, F.S. Al-Duais, W. Aydi, A.Y. Al-Rezami
  • Journal: Alexandria Engineering Journal
  • Year: 2024
  • DOI: 10.1016/j.aej.2023.12.051
  • EID: 2-s2.0-85181767525
  • ISSN: 1110-0168
  • Publisher: Elsevier
  • Scope: Bayesian inference methods applied to censored Pareto distributions using non-linear optimization techniques.

Defining and Analyzing New Classes Associated with (λ,γ)-Symmetrical Functions and Quantum Calculus

  • Authors: H. Louati, A.Y. Al-Rezami, A.A. Darem, F. Alsarari
  • Journal: Mathematics (MDPI)
  • Year: 2024
  • DOI: 10.3390/math12162603
  • EID: 2-s2.0-85202574837
  • ISSN: 2227-7390
  • Publisher: MDPI
  • Scope: Introduces function classes based on symmetrical properties within the framework of quantum calculus.

Diagnostic Power of Some Graphical Methods in Geometric Regression Model Addressing Cervical Cancer Data

  • Authors: Z. Hussain, A. Akbar, M.M.A. Almazah, A.Y. Al-Rezami, F.S. Al-Duais
  • Journal: AIMS Mathematics
  • Year: 2024
  • DOI: 10.3934/math.2024198
  • EID: 2-s2.0-85182243851
  • ISSN: 2473-6988
  • Publisher: AIMS Press
  • Scope: Evaluates graphical techniques in diagnostic modeling for real-world biomedical data, particularly in cancer prediction.

Exploring Quasi-Probability Husimi-Distributions in Nonlinear Two Trapped-Ion Qubits: Intrinsic Decoherence Effects

  • Authors: L.A. Al-Essa, A.Y. AL-Rezami, F.M. Aldosari, A.-B.A. Mohamed, H. Eleuch
  • Journal: Optical and Quantum Electronics
  • Year: 2024
  • DOI: 10.1007/s11082-024-06284-z
  • EID: 2-s2.0-85183574852
  • ISSN: 0306-8919 (print), 1572-817X (electronic)
  • Publisher: Springer
  • Scope: Theoretical study on decoherence in quantum qubit systems using Husimi quasi-probability distributions.

Integration of Three Drought Indices Based on Triple Collocation and Multi-Scalar Weighted Amalgamated Drought Index

  • Authors: Z. Badar, M.M.A. Almazah, M.A. Raza, I. Hussain, F.S. Al-Duais, A.Y. Al-Rezami
  • Journal: Stochastic Environmental Research and Risk Assessment
  • Year: 2024
  • DOI: 10.1007/s00477-023-02623-w
  • EID: 2-s2.0-85179359120
  • ISSN: 1436-3240 (print), 1436-3259 (electronic)
  • Publisher: Springer
  • Scope: Combines drought indices using a novel statistical method for improved environmental risk modeling.

Conclusion

Given her sustained excellence in research, commitment to teaching, and contributions to statistical education and institutional evaluation, Dr. Afrah Yahya Mohammed AL Rezami is exceptionally well-suited for the Best Scholar Award. Her leadership, academic rigor, and impactful service to higher education mark her as a role model in the field of applied statistics.

Prof. Rita Santos Inácio | Data Science and Deep Learning | Best Researcher Award

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Prof. Rita Santos Inácio | Data Science and Deep Learning | Best Researcher Award

Professor, at Instituto Politécnico de Beja, Portugal.

Ana Rita Santos Inácio is a Quality Manager and Invited Adjunct Professor at the Polytechnic Institute of Beja. She holds a PhD in Food Science and Nutrition and has research experience in high-pressure technology applied to milk and cheese.

Professional Profile

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🎓 Education

– *PhD in Food Science and Nutrition*, Portuguese Catholic University of Porto – School of Biotechnology (2020)- *Master’s in Biotechnology – Food*, University of Aveiro (2013)- *Bachelor’s in Biotechnology*, University of Aveiro (2011)

💼 Experience

– *Quality Manager*, Sensory Laboratory, Polytechnic Institute of Beja (2023-present)- *Invited Adjunct Professor*, Department of Applied Technologies and Sciences, Polytechnic Institute of Beja (2020-present)- *Research Fellow*, University of Aveiro /QOPNA (2019-2020)

🔬 Research Interests

– *Food Science and Nutrition*: high-pressure technology, milk and cheese safety and quality- *Sensory Analysis*: sensory test sheets, sensory session planning and execution, data analysis- *Food Technology*: meat and fish technology, food safety and quality

🏆 Awards

– *”Summa Laude”*, PhD thesis (2020)- *FCT grant*, SFRH/BD/96576/2013 (2014-2019)

📚 Top Noted Publications

– Effect of high-pressure as a non-thermal pasteurisation technology for raw ewes’ milk and cheese safety and quality 🥛
– PhD thesis
– Effect of high-pressure on Serra da Estrela cheese 🧀
– Master’s thesis
– Second-generation bioethanol production: fermentation of acid sulphite liquor by free and immobilised Pichia stipitis 💡

Conclusion

Rita Santos Inácio’s research excellence, teaching experience, and professional activity make her a strong candidate for the Best Researcher Award. With further interdisciplinary collaboration and internationalization, she could further enhance the impact of her research and contribute to advancements in food science and nutrition.

Prof. Dr. Jasenka Gajdoš Kljusurić | Data Science and Deep Learning | Best Researcher Award

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Prof. Dr. Jasenka Gajdoš Kljusurić | Data Science and Deep Learning | Best Researcher Award

Prof, Faculty of Food Technology and Biotechnology at University of Zagreb, Croatia

Sylvain S. Guillou is a Full Professor of Fluid Mechanics at the University of Caen Normandy, France. He is the Director of the Applied Science Laboratory LUSAC and has over 176 publications, 38,900 reads, and 1,692 citations. His research focuses on computational physics, fluid dynamics, and geophysics, particularly in tidal turbines and marine renewable energies ¹.

Profile

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🎓 Education

– *HDR – Fluid Mechanics*, University of Caen (2004-2005)- Ph.D. in Applied Mathematics – Mechanics, University of Paris Pierre & Marie Curie (1993-1996)- (link unavailable) in Dynamics of Fluids – Numerical Modeling, Ecole Centrale de Nantes (1992-1993)

👨‍🔬 Experience

– *Full Professor*, University of Caen Normandy (2017-present)- *Associate Professor*, University of Caen Normandy (2005-2017)- *Assistant Professor*, University of Caen Normandy (1999-2005)- *Post-doctoral Researcher*, University of Caen (1996-1997)

🔍 Research Interest

– *Computational Physics*: Numerical simulations of complex fluid flows- *Fluid Dynamics*: Turbulence, sediment transport, and environmental fluid mechanics- *Geophysics*: Marine renewable energies, tidal turbines, and offshore wind energies

Awards and Honors 🏆

Although specific awards and honors are not detailed, Guillou’s editorial roles and conference organization demonstrate his recognition in the field ¹ ²: – *Associate Editor*, Energies, La Houille Blanche, and International Journal for Sediment Research- *Organizer*, International Conference on Estuaries and Coasts (ICEC-2018) and other conferences

📚 Publications 

– Numerical modeling of the effect of tidal stream turbines on the hydrodynamics and the sediment transport–Application to the Alderney Race (Raz Blanchard), France 🌊
– Modelling turbulence with an Actuator Disk representing a tidal turbine 🌟
– A two-phase numerical model for suspended-sediment transport in estuaries 🌴
– Wake field study of tidal turbines under realistic flow conditions 💨
– Tidal farm analysis using an analytical model for the flow velocity prediction in the wake of a tidal turbine with small diameter to depth ratio 🌊

Conclusion

Sylvain S. Guillou’s impressive research record, leadership roles, and editorial activities make him an excellent candidate for the Best Researcher Award. His contributions to computational physics, fluid dynamics, and geophysics have significantly advanced our understanding of these fields. With some potential for interdisciplinary collaborations and exploring emerging topics, Guillou is well-suited to receive this award ¹ ².

Manar Hamza | Computer Science Data mining | Best Researcher Award

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Dr. Manar Hamza | Computer Science Data mining | Best Researcher Award

professor at  Prince Sattam bin Abd El Aziz University, China

👩‍🏫 Experienced Computer Science Lecturer since 2005 with expertise in data mining, text mining, and information security. 💻 Holds a strong track record in research and academia, leveraging innovation and teamwork. Aims to thrive in challenging, dynamic, and team-oriented environments that foster growth. 🌍 Based in Sudan and Saudi Arabia, dedicated to academic excellence and community impact.

Professional Profiles:

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Education 🎓

Ph.D. in Computer Science from Omdurman Islamic University, Sudan (2018–2021). 🎓 Master’s Degree in Computer Science from Sudan University of Science and Technology (2003–2005). 🎓 B.Sc. in Computer Science from Omdurman Islamic University, Sudan (1995–1999). 📚 Comprehensive training in research skills, academic advising, and IT tools like Mendeley, Latex, and iThenticate.

Experience 🖥️

Lecturer in Computer Science at Prince Sattam bin Abdul-Aziz University, Saudi Arabia (2013–present). 👩‍💼 Supervisor and Coordinator roles in quality, academic advising, and measurement (2014–2020). 🇸🇩 Lecturer at Omdurman Islamic University, Sudan (2005–2012). 👩‍🔬 E-teaching and training specialist with Arab Board experience (2023).

Awards and Honors 🏆

Certificates of Appreciation from PSAU for contributions to quality, development, and academic planning. 🙌 Recognized for voluntary services, including extracurricular activities and technical support for students and staff. ⭐ Esteemed arbitrator in scientific and innovation conferences. 📜 Active contributor to enhancing the learning environment with innovative solutions.

Research Focus 🔍

Data mining, text mining, and information security are core research areas. 📊 Interested in qualitative research, outcome-based education, and e-learning systems. 🌐 Advocates for advancing academic IT tools like Prezi, Mendeley, and iThenticate. 🛡️ Exploring cybersecurity methods and their application in education and industry.

✍️Publications Top Note :

1. Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

Published in: SN Computer Science, 2024, 5(5), 549

Summary: This paper proposes a novel classification model for urban-related tweets using arithmetic optimization integrated with deep learning to support sustainable urban living solutions.

2. Enhancing Traffic Flow Prediction in Intelligent Cyber-Physical Systems

Published in: IEEE Transactions on Consumer Electronics, 2024, 70(1), pp. 1889–1902

Summary: Introduces a Bi-LSTM approach enhanced with a Kalman filter for accurate traffic flow prediction, addressing challenges in intelligent cyber-physical systems.

Citations: 5

3. Deer Hunting Optimization with Deep Learning-Driven Automated Fabric Defect Detection and Classification

Published in: Mobile Networks and Applications, 2024, 29(1), pp. 176–186

Summary: Utilizes the Deer Hunting Optimization algorithm with deep learning to achieve high accuracy in detecting and classifying fabric defects.

Citations: 1

4. Automatic Recognition of Cyberbullying in the Web of Things and Social Media Using Deep Learning Framework

Published in: IEEE Transactions on Big Data, 2024

Summary: Develops a deep learning-based framework to detect and prevent cyberbullying within social media and IoT environments.

5. Artificial Rabbit Optimizer with Deep Learning for Fall Detection in IoT Environment

Published in: AIMS Mathematics, 2024, 9(6), pp. 15486–15504

Summary: Introduces the Artificial Rabbit Optimizer combined with deep learning to enhance fall detection systems for disabled individuals in IoT environments.

Citations: 1

6. Computational Linguistics-Based Arabic Poem Classification and Dictarization Model

Published in: Computer Systems Science and Engineering, 2024, 48(1), pp. 98–114

Summary: Proposes a computational linguistics model to classify Arabic poems and enhance their dictarization process.

7. Abstractive Arabic Text Summarization Using Hyperparameter Tuned Denoising Deep Neural Network

Published in: Intelligent Automation and Soft Computing, 2024, 38(2), pp. 153–168

Summary: Develops a deep neural network with hyperparameter tuning for effective abstractive summarization of Arabic texts.

Citations: 1

8. Chaotic Equilibrium Optimizer-Based Green Communication With Deep Learning Enabled Load Prediction in IoT Environment

Published in: IEEE Access, 2024, 12, pp. 258–267

Summary: Presents a Chaotic Equilibrium Optimizer combined with deep learning to improve green communication and load prediction in IoT systems.

Citations: 2

9. Land Use and Land Cover Classification Using River Formation Dynamics Algorithm With Deep Learning on Remote Sensing Images

Published in: IEEE Access, 2024, 12, pp. 11147–11156

Summary: Leverages the River Formation Dynamics algorithm integrated with deep learning for efficient land use and land cover classification using remote sensing data.

Citations: 4

10. Prediction of Sleep Quality Using Wearable-Assisted Smart Health Monitoring Systems

Published in: Journal of King Saud University – Science, 2023, 35(9), 102927

Summary: Utilizes wearable technology and statistical data to predict sleep quality, providing insights into personalized smart health monitoring systems.

Citations: 1

Conclusion

The candidate’s extensive experience, academic qualifications, and contributions to computer science, particularly in data mining and information security, make them a strong contender for the Research for Best Researcher Award. With some strategic enhancements to highlight impactful research and global contributions, their profile could exemplify the qualities of an award-winning researcher in computer science.

Xiaolin Yang | CImage analysis | Best Researcher Award

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Dr. Xiaolin Yang | Image analysis | Best Researcher Award

Dr at China university of mining and technology, China

Xiaolin Yang is a skilled Business Analyst and Postdoctoral Researcher at Henan Investment Group. With a solid background in mineral process engineering, his expertise spans industry research, project management, and production optimization. Xiaolin holds a Bachelor’s and a Ph.D. in Mineral Process Engineering from the China University of Mining and Technology, specializing in mineral processing, machine learning, and image analysis. His dedication to academic excellence and practical application makes him a valuable asset in the mineral industry.

Publication Profile

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Education🎓 

.Bachelor of Mineral Process Engineering | China University of Mining and Technology, 2015–2019 | Focus: Mineral separation methods and equipment. Doctor of Mineral Process Engineering | China University of Mining and Technology, 2019–2024 | Research areas: Mineral processing, machine learning, image analysis. Xiaolin’s academic journey emphasized innovation in mineral separation, blending engineering with data science to improve mineral processing efficiency and accuracy.

Experience💼 

Postdoctoral Researcher | Henan Investment Group, 2024–Present | Xiaolin’s role involves comprehensive industry research, preparing assessment reports, and offering investment insights and recommendations. His project management tasks focus on feasibility assessments and evaluating the effectiveness of production processes, aiming to optimize industrial production and implement innovative solutions in mineral processing.

Awards and Honors🏆 

Published Author | Xiaolin has authored notable academic articles, such as in Journal of Materials Research and Technology (2021), Energy (2022), and Expert Systems with Applications (2024). His work, recognized for its significance in mineral processing and machine learning, highlights his expertise in utilizing advanced algorithms for practical industry challenges.

Research Focus🔍

Research Interests | Xiaolin’s research delves into mineral processing, machine learning applications, and image analysis. His studies, including deep learning for ash determination in coal flotation, explore novel algorithms to enhance mineral processing accuracy, bridging engineering and artificial intelligence for industrial optimization.

Publication  Top Notes

Multi-scale neural network for accurate determination of ash content in coal flotation concentrate

Authors: Yang, X., Zhang, K., Thé, J., Tan, Z., Yu, H.

Journal: Expert Systems with Applications, 2025, 262, 125614

Description: This paper presents a multi-scale neural network model that accurately determines ash content in coal flotation concentrate using froth images, leveraging deep learning to enhance mineral processing efficiency.

STATNet: One-stage coal-gangue detector for real industrial applications

Authors: Zhang, K., Wang, T., Yang, X., Tan, Z., Yu, H.

Journal: Energy and AI, 2024, 17, 100388

Description: The STATNet model is introduced as a coal-gangue detection system using a one-stage deep learning algorithm, tailored for industrial application with a focus on real-time processing.

COFNet: Predicting surface area of covalent-organic frameworks

Authors: Wang, T., Yang, X., Zhang, K., Tan, Z., Yu, H.

Journal: Chemical Physics Letters, 2024, 847, 141383

Description: COFNet utilizes deep learning to predict the specific surface area of covalent-organic frameworks, combining structural image analysis with statistical features for accurate predictions.

Enhancing coal-gangue detection with GAN-based data augmentation

Authors: Zhang, K., Yang, X., Xu, L., Tan, Z., Yu, H.

Journal: Energy, 2024, 287, 129654

Description: This study employs GAN-based data augmentation and a dual attention mechanism to improve coal-gangue object detection, aiming to refine accuracy in complex industrial environments.

Multi-step carbon price forecasting using hybrid deep learning models

Authors: Zhang, K., Yang, X., Wang, T., Tan, Z., Yu, H.

Journal: Journal of Cleaner Production, 2023, 405, 136959

Description: A hybrid deep learning model for multi-step forecasting of carbon prices is proposed, integrating multivariate decomposition to enhance predictive reliability.

PM2.5 and PM10 concentration forecasting with spatial–temporal attention networks

Authors: Zhang, K., Yang, X., Cao, H., Tan, Z., Yu, H.

Journal: Environment International, 2023, 171, 107691

Description: This article introduces a spatial–temporal attention mechanism for PM2.5 and PM10 forecasting, using convolutional neural networks with residual learning to tackle air quality predictions.

Ash determination of coal flotation concentrate using hybrid deep learning model

Authors: Yang, X., Zhang, K., Ni, C., Tan, Z., Yu, H.

Journal: Energy, 2022, 260, 125027

Description: This work features a hybrid model that utilizes deep learning and attention mechanisms to determine ash content in coal flotation, contributing to process optimization.

Influence of cation valency on flotation of chalcopyrite and pyrite

Authors: Yang, X., Bu, X., Xie, G., Chehreh Chelgani, S.

Journal: Journal of Materials Research and Technology, 2021, 11, pp. 1112–1122

Description: This comparative study explores how different cation valencies affect chalcopyrite and pyrite flotation, contributing to better separation techniques in mineral processing.

Conclusion

Xiaolin Yang is a compelling candidate for the Best Researcher Award. His strengths in applying AI and image analysis to mineral processing reflect a unique skill set that is highly relevant for advancing research and industry practices. With further interdisciplinary work and expanded research visibility, Xiaolin is well-positioned to make impactful contributions and earn recognition in his field.

Jianzhi Li | Fiber sensing | Best Researcher Award

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Prof. Jianzhi Li | Fiber sensing | Best Researcher Award

 professor at Shijiazhuang Tiedao University,  china

Jianzhi Li is a Professor at the Key Laboratory of Structural Health Monitoring and Control, Shijiazhuang Tiedao University, specializing in fiber sensing technology and structural health monitoring. 🌉 She earned her Ph.D. from Beijing Jiaotong University and later held an academic post at Osaka University, Japan. 🚄 Her work focuses on enhancing railway infrastructure safety through innovative sensing techniques. 📚 Jianzhi has published numerous SCI papers and authored several books. 🚀 Her groundbreaking contributions in the field have earned her multiple awards, cementing her status as a leading researcher in fiber optics and structural health.

Publication Profile

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Education 🎓

Jianzhi Li earned her Ph.D. in Structural Diagnosis and Optimization from Beijing Jiaotong University in 2009. 📚 Her doctoral studies focused on identifying and solving complex structural challenges in engineering. 🌏 She further broadened her academic horizons by serving as an Associate Professor at Osaka University in Japan between 2014 and 2015. 🏛️ This role allowed her to collaborate internationally and enhance her expertise in fiber optic sensing technology. ✨ Throughout her education, she gained deep insights into the intersections of structural health and smart material technologies, which now form the cornerstone of her research endeavors.

Experience 🏢 

Jianzhi Li currently serves as a Professor at Shijiazhuang Tiedao University’s Key Laboratory of Structural Health Monitoring and Control. 🚇 She has led several high-impact projects, particularly in fiber optic sensing and structural health monitoring for railways and bridges. 🌉 During 2014–2015, she was an Associate Professor at Osaka University, contributing to international collaborations. 📊 With over 20 patents to her name and numerous published works in prestigious journals, her experience spans industry-relevant research and cutting-edge academic advancements. 💼 She also leads the China National Key Research and Development Program, contributing to the enhancement of railway infrastructure safety.

Awards and Honors  🏆

Jianzhi Li has received numerous awards, including the First Prize for Technological Invention in Hebei Province. 🌟 She was recognized with the “Best Paper” award at the 6th International Conference on Optoelectronic Sensing. 🎖️ Her outstanding research contributions have earned her prestigious honors such as the Hebei Outstanding Youth Talent Award and a place in the Hebei 333 Talent Program. 📜 She has authored three books, including an internationally recognized English-language textbook, and her innovative work in fiber sensing and structural health has placed her among the top researchers in China. 🌍 Her membership in the Chinese Optical Society and other professional groups reflects her impact on the scientific community.

Research Focus🔬

Jianzhi Li’s research is centered on fiber optic sensing technologies and structural health monitoring. 🚇 Her work addresses critical infrastructure challenges, including heavy-duty railway bridges and roadbeds. 🔧 She has been instrumental in advancing fiber-based sensing systems for monitoring railway hazards and enhancing safety through predictive detection. 🛰️ Her research extends to smart materials and their applications in dynamic environments, focusing on the early detection of structural anomalies. 🚀 Jianzhi’s contributions are practical and forward-looking, pushing the boundaries of electromagnetic and optical sensing in engineering, leading to the development of more robust and resilient civil structures.

Publication  Top Notes

Evaluation of Concrete Carbonation Based on a Fiber Bragg Grating Sensor
📅 Published: December 2023
📰 Journal: Micromachines
🌐 DOI: 10.3390/mi15010029
Contributors: Jianzhi Li, Haiqun Yang, Handong Wu

This paper introduces a novel approach for monitoring concrete carbonation using Fiber Bragg Grating (FBG) sensors, a crucial method for assessing structural durability.

A Long-Term Monitoring Method of Corrosion Damage of Prestressed Anchor Cable
📅 Published: March 2023
📰 Journal: Micromachines
🌐 DOI: 10.3390/mi14040799
Contributors: Jianzhi Li, Chen Wang, Yiyao Zhao

This research presents a long-term monitoring technique for detecting corrosion in prestressed anchor cables, improving infrastructure safety and longevity.

A Combined Positioning Method Used for Identification of Concrete Cracks
📅 Published: November 2021
📰 Journal: Micromachines
🌐 DOI: 10.3390/mi12121479
Contributors: Jianzhi Li, Bohao Shen, Junjie Wang

This paper discusses a hybrid method for accurately identifying concrete cracks, advancing structural health monitoring.

A Spiral Distributed Monitoring Method for Steel Rebar Corrosion
📅 Published: November 2021
📰 Journal: Micromachines
🌐 DOI: 10.3390/mi12121451
Contributors: Jianzhi Li, Yiyao Zhao, Junjie Wang

Conclusion

Professor Jianzhi Li stands out as a strong candidate for the Best Researcher Award due to her exemplary research contributions, innovative spirit, and recognized leadership in the field of fiber sensing and structural health monitoring. Her achievements reflect not only her commitment to advancing science and technology but also her potential to further influence the field. With targeted improvements in professional engagement and industry collaboration, she could amplify her impact even more.

Nicola D’souza | home dialysis and self-efficacy | Best Researcher Award

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Ms.Nicola D’souza | home dialysis and self-efficacy | Best Researcher Award

Ms Nicola D’souza Edith Cowan University Australia

As a Level Two Registered Nurse, I focus on improving patient outcomes and care quality through clinical projects and research. My skills include developing protocols, conducting literature reviews, and analyzing data. Currently, at ForHealth Group, I manage chronic disease care and team coordination. Previously, I’ve worked in clinical research and dialysis settings, contributing to studies on respiratory health and caregiver experiences. My educational background includes a Master of Nursing by Research and a Bachelor of Nursing, complemented by various certifications and a robust track record of publications and presentations.

 

Professional Profiles:

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🎓 Education

Master of Nursing (By Research)Edith Cowan University 02/2021 – 07/2023.Bachelor of Nursing,University of Calgary in Qatar 09/2012 – 06/2016.Achieved: Distinction; Cumulative GPA 3.82.

🔑 Key Skills

🩺 Competence in critical assessment, reviewing policies, and patient education.📈 Data analysis, documenting, and reporting events.🖥️ Proficiency with MS Office, Endnote, and JBI SUMARI.

📜 Licenses & Certifications

Registered Nurse Division 1, Nursing and Midwifery Board AHPRA (Credential ID Registration number: NMW0002606370).Good Clinical Practice (GCP) in Australia.Research Education and Training Program, WAHTN.Registered General Nurse, Qatar Council for Health Care Practitioners

🏆 Awards

Outstanding Research Project, 11th Annual Undergraduate Research Experience Program Competition, 2019.International Exchange Award of 20,000 QAT for clinical placement and study in Canada, Fall 2016.Dean’s List, University of Calgary in Qatar, 2013-2016.

 

✍️Publications :

D’Souza, N.A., Abu‐Qamar, M.Z. & Whitehead, L. (2024) Self‐efficacy and home dialysis: An integrative review. Journal of Renal Care, 1–18

Conclusion

With a strong foundation in both clinical practice and research, I bring a comprehensive approach to nursing that enhances patient care and supports healthcare teams. My experience spans chronic disease management, clinical trials, and research, demonstrating my commitment to advancing healthcare quality and patient outcomes.

Aljowhara Honain | Numerical Methods| Best Researcher Award

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Ms Aljowhara Honain King Fahd University of Petroleum and Minerals Saudi Arabia

Aljowhara Hasan Honain is a dedicated mathematician currently pursuing a Ph.D. in Mathematics at King Fahd University of Petroleum and Minerals, Saudi Arabia. She holds an M.Sc. in Mathematics from Middle Tennessee State University and a B.Sc. from King Abdul-Aziz University. Her research focuses on advanced topics in fractional calculus, including rational approximations and exponential time differencing schemes for fractional oscillation models. Notable publications include work presented at the International Conference on Fractional Differentiation and Its Applications (ICFDA) and contributions to the journal Fractal and Fractional. She has actively participated in various teaching roles and conferences, presenting her work on fractional derivatives and oscillatory functions. Her achievements have been recognized with the Grünwald-Letnikov Award for Best Student Paper in March 2023.

 

Professional Profiles:

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📚 EDUCATION

Ph.D. in Mathematics,King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia2020 – Present.M.Sc. in Mathematics,Middle Tennessee State University, Murfreesboro, TN, USA,2016.B.Sc. in Mathematics,King Abdul-Aziz University, Jeddah, Saudi Arabia.2009.

👩‍🏫 TEACHING ACTIVITIES

Recitation Instructor, King Fahd University of Petroleum and Minerals (KFUPM)June 2023 – August 2023. Teaching Assistant, KFUPM.January 2023 – May 2023.Math Lecturer, Motlow State Community College, Smyrna, TN, USAJanuary 2019 – December 2019.Math Teacher, ICM Academy, Murfreesboro, TN, USAJanuary 2018 – June 2019.Math and ESL Teacher, Read to Succeed Organization of Murfreesboro, TN, USA,2017 – 2018.

🎤 PRESENTATIONS

“Rational Approximation for Oscillatory Mittag-Leffler Function”,March 14-16, 2023, International Conference on Fractional Differentiation and Its Applications (ICFDA’23), Ajman, UAE.“Exponential Time Differencing Scheme for Fractional Plasma Oscillations”,July 09-12, 2024, International Conference on Fractional Differentiation and Its Applications (ICFDA’24), Bordeaux, France.“Numerical Approximations of Fractional Derivatives”,December 12, 2021, Female Research Day, KFUPM Institute for Knowledge Exchange.

🌐 WORKSHOPS AND CONFERENCES ATTENDED

International Conference on Fractional Differentiation and Its Applications (ICFDA’24),July 09-12, 2024, Bordeaux, France,WebAssign Webinar Series,July 11-13, 2023.International Conference on Fractional Differentiation and Its Applications (ICFDA’23).March 14-16, 2023, Ajman University, UAE. The 6th Annual MTSU Literacy Research Conference
2018, Murfreesboro, TN, USA. Reading Tutor Workshop Training, Read to Succeed Organization2017, Murfreesboro, TN, USA.

🏆 AWARDS

Grünwald-Letnikov Award: Best Student Paper (Theory).First Place for “Rational Approximation for Oscillatory Mittag-Leffler Function”,March 2023, ICFDA’23.

 

✍️Publications :

Rational Approximation for Oscillatory Mittag-Leffler Function
Authors: A.H. Honain, K.M. Furati
Year: 2023

Rational Approximations for the Oscillatory Two-Parameter Mittag–Leffler Function
Authors: A.H. Honain, K.M. Furati, I.O. Sarumi, A.Q.M. Khaliq
Year: 2024

Exponential Time Differencing Scheme for Fractional Plasma Oscillations
Authors: A.H. Honain, K.M. Furati
Year: 2024

Conclusion

Aljowhara Hasan Honain is a dedicated mathematician currently pursuing a Ph.D. in Mathematics at King Fahd University of Petroleum and Minerals, Saudi Arabia. She holds an M.Sc. in Mathematics from Middle Tennessee State University and a B.Sc. from King Abdul-Aziz University. Her research focuses on advanced topics in fractional calculus, including rational approximations and exponential time differencing schemes for fractional oscillation models. Notable publications include work presented at the International Conference on Fractional Differentiation and Its Applications (ICFDA) and contributions to the journal Fractal and Fractional. She has actively participated in various teaching roles and conferences, presenting her work on fractional derivatives and oscillatory functions. Her achievements have been recognized with the Grünwald-Letnikov Award for Best Student Paper in March 2023.

Dr. Yong Wang | computational Award | Best Researcher Award

Published on by Mechanics Awards

Dr. Yong Wang | computational Award | Best Researcher Award

Dr. Yong Wang, Zhejiang University, China

Dr. Yong Wang is academic and researcher in the field of renewable energy, holds a PhD in Bio systems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

Professional Profiles:

Google scholar

orcid

🎓 Teaching and Tutoring

Jury for International Biosensor Competition: SensUs 2023 (2023)Supervisor for TruSense, Zhejiang University (2021-)Teacher for Ingenious Synthetic Biology, Zhejiang University (2022-)Teaching Assistant for Advanced Protein Science 2 – Protein Structure Determination (graduate course), University of Copenhagen (2020, 2019)Teaching Assistant for Advanced Protein Science (graduate course), University of Copenhagen (2015)Tutor for Postdoc, PhD, MSc, and BSc students.

📝 Editorial Roles

Academic Editor for PLoS One (2023-)Associate Editor for Frontiers in Molecular Biosciences (2021-)Editorial Board Member of Peer J (2023-)Ad Hoc Young Editorial Board Member of Journal of Molecular Cell Biology (JMCB) (2020-)Second Youth Editorial Board Member of Asian Journal of Pharmaceutical Sciences (2023-)

🔍 Reviewer

Journal Reviewer for prestigious journals.Grant Reviewer for the Dutch Research Council (NWO) Computational Grants.

👥 Memberships

Member of the PLUMED ConsortiumMember of the American Society for Biochemistry and Molecular BiologyMember of Chinese Chemical Society

AWARDS & GRANTS🏆

Recognition for contributions:Zhejiang Provincial National Science Foundation (No. XXX) (300 K ¥) 2024-2026National Science Foundation of China (No. 32371300) (500 K ¥) 2024-2027Start-up funding of Zhejiang University (4.0 M ¥) 2021-2027National Key R & D Program of China (No. 2021YFF1200404) (4.55 M ¥) 2021-2024Fundamental Research Funds for the Central Universities of China (No. K20220228) (900 K ¥) 2022-2024HPC-Europa3 Transnational Access program for visiting Max Planck Institute for Biophysical Chemistry Spring of 2020EMBO Short-term Fellowship for visiting Prof. Michele Parrinello lab at ETH Zurich, Switzerland Spring of 2016The PhD Scholarship at the Department of Biology, University of Copenhagen (2013-2016)

Citations: 1547

h-index: 23

i10-index: 31

And if we consider the second set:

Citations: 1074

h-index: 21

i10-index: 30

📖 Publications  Top Note :

A Computational and Chemical Design Strategy for Manipulating Glycan-Protein Recognition

Q Zhu, D Geng, J Li, J Zhang, H Sun, Z Fan, J He, N Hao, Y Tian, L Wen, …

Advanced Science, 2024

Diverse roles of the metal binding domains and transport mechanism of copper transporting P-type ATPases

Z Guo, F Orädd, V Bågenholm, C Grønberg, JF Ma, P Ott, Y Wang, …

Nature Communications, 2609, 2024

Dissecting the mechanism of atlastin-mediated homotypic membrane fusion at the single-molecule level

L Shi, C Yang, M Zhang, K Li, K Wang, L Jiao, R Liu, Y Wang, M Li, …

Nature Communications, 2488, 2024

Euglena’s atypical respiratory chain adapts to the discoidal cristae and flexible metabolism

Z He, M Wu, H Tian, L Wang, Y Hu, F Han, J Zhou, Y Wang, L Zhou

Nature Communications, 1628, 2024

Structures and ion transport mechanisms of plant high-affinity potassium transporters

J Wang, Y Luo, F Ye, ZJ Ding, SJ Zheng, S Qiao, Y Wang, J Guo, W Yang, …

Molecular Plant, 2024

Structural basis for sugar perception by Drosophila gustatory receptors

D Ma, M Hu, X Yang, Q Liu, F Ye, W Cai, Y Wang, X Xu, S Chang, R Wang, …

Science, eadj2609, 2024

PAFAH2 suppresses synchronized ferroptosis to ameliorate acute kidney injury

Q Zhang, T Sun, F Yu, W Liu, J Gao, J Chen, H Zheng, J Liu, C Miao, …

Nature Chemical Biology, 1-12, 2024

Structure and mechanism of Zorya anti-phage defense system

H Hu, TCD Hughes, PF Popp, A Roa-Eguiara, FJO Martin, N Rutbeek, …

bioRxiv, 1, 2024

The effect of linker conformation on performance and stability of a two-domain lytic polysaccharide monooxygenase

Z Forsberg, AA Stepnov, G Tesei, Y Wang, E Buchinger, SK Kristiansen, …

Journal of Biological Chemistry, 299 (11), 2023

Ex vivo structures from spinach leaves

J Wang, NT Johansen, LF Gamon, Z Zhao, Z Guo, Y Wang, AT Fuglsang, …

biorxiv, 2023

Dr. Kim Robinson | molecular biology Award | Best Researcher Award

Published on by Mechanics Awards

Dr. Kim Robinson | molecular biology Award | Best Researcher Award

Dr. Kim Robinson, University of York, United Kingdom

Dr. Kim Robinson is academic and researcher in the field of renewable energy, holds a PhD in Bio systems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

 

Professional Profiles:

Google scholar

📚 Academic Qualifications

PhD, University of Dundee, UK (2010-2014), title: “Understanding the molecular basis for squamous cell carcinoma” supervised by Prof Andrew South and Prof Irene LeighMSc, University of Dundee, UK (2008-2010) (part-time), “investigating light activated drugs for cancer therapeutics” supervised by Dr Julie Woods and Prof James FergusonBSc (Hons), University of Dundee, UK (2004-2008), FYP “Obtaining an action spectrum for Carprofen induced photosensitivity” supervised by Dr Julie Woods and Prof James Ferguson

🔬 Post-Doctoral Positions Held

Senior Research Fellow, Singapore Research Institute Singapore & ASTAR Skin Research Laboratories, ASTAR, Singapore, (November 2017- August 2023)

🔖 List of Patents

Co-inventor on technology patent (International Publication No. WO 2021/188052 A1, Mar 2021)Co-inventor on technology patent (Provisional Conversion, SG Patent Application No. 10202101805W, 23 February 2021)

📊 Citation Metrics (Google Scholar):

Citations by: All – 2198, Since 2018 –1626

h-index: All – 18, Since 2018 – 16

i10 index: All – 19, Since 2018 –17

📖 Publications  Top Note :

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