Dr Shu Zhu | Microfluidics | Best Researcher Award

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Dr Shu Zhu | Microfluidics | Best Researcher Award

Lecturer , Nanjing Normal University , China 

Shu Zhu 👨‍🔬 is a dedicated Lecturer at Nanjing Normal University 📍, serving in the School of Electrical and Automation Engineering and the Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing 🏫. He earned his Ph.D. in Mechanical Engineering from Southeast University 🎓 in 2024. His work focuses on microfluidics, impedance cytometry, and point-of-care testing (POCT) devices 🧪. With 19 publications in prestigious journals like Lab on a Chip and Analytica Chimica Acta, he is known for innovative tools like CytoExam, a deep learning-powered liquid biopsy device. 🧬💡

Professional Profile

ORCID

Education & Experience 

Shu Zhu completed his Ph.D. in Mechanical Engineering from Southeast University (SEU) 🎓 in 2024, where he explored cutting-edge technologies in microfluidic systems 💧 and cell analysis. He is currently a Lecturer 👨‍🏫 at Nanjing Normal University, contributing to both teaching and high-impact research at the Jiangsu Key Laboratory of 3D Printing Equipment 🖨️. His academic journey is marked by rigorous exploration into impedance cytometry and microdevices for biomedical applications 🧫. With 530+ citations 📈 and 19 research papers, his experience bridges advanced research and practical healthcare solutions. 🧠🔬

Professional Development 

Dr. Shu Zhu is an emerging expert in biomedical microdevices 🔍. He has been actively involved in major national projects like the National Natural Science Foundation of China and the Jiangsu Key R&D Program 🇨🇳. With 10 patents 📝 under his name, his professional growth has been fueled by innovation and problem-solving. He developed CytoExam, an AI-integrated diagnostic tool for CTC detection 🤖🧬. Though early in his career, his professional track reflects rapid growth 📊, meaningful impact, and a strong foundation for future leadership in microfluidic healthcare technologies 🚀.

Research Focus

Shu Zhu’s research 🔍 focuses on microfluidics, particularly inertial microfluidics, impedance cytometry, and POCT (point-of-care testing) devices 🧪. His innovations include CytoExam 🧬, a deep learning-enabled liquid biopsy system for identifying circulating tumor cells (CTCs), reflecting his commitment to merging bioengineering with clinical diagnostics 💻🧫. He also works on micromixing, cell deformability analysis, and dielectric characterization of cells 🔋. His research bridges multiple domains—mechanical engineering, biomedical diagnostics, and artificial intelligence—making significant contributions toward fast, accurate, and accessible healthcare technologies ⏱️🏥.

Awards & Honors 

While formal awards may still be in progress, Shu Zhu’s achievements speak volumes 🌟. With 19 published SCI/EI papers 📰 and 10 patents pending or granted 🔖, his work is highly recognized in academic circles. His projects have received national-level funding from the NSFC and Jiangsu R&D initiatives 🇨🇳, reflecting strong institutional trust and impact. His citation index of over 530 📊 showcases the value and reach of his contributions to microfluidics and biomedical diagnostics 🔬. As a rising innovator, he is a strong candidate for accolades such as the Best Researcher Award 🥇.

Publication Top Notes

1. Comprehensive Analysis of Shear Deformation Cytometry Based on Numerical Simulation Method

Journal: Biosensors (2025-06)
DOI: 10.3390/bios15060389
Contributors: Jun Wang, Jiahe Chen, Wenlai Tang, Shu Zhu
🔎 Summary:
This study employs numerical simulations to enhance understanding of shear deformation cytometry, enabling more precise mechanical characterization of cells in microfluidic systems.

2. Multiparameter Mechanical Phenotyping for Accurate Cell Identification Using High-Throughput Microfluidic Deformability Cytometry

Journal: Analytical Chemistry (2024-06-25)
DOI: 10.1021/acs.analchem.4c01175
Contributors: Zheng Zhou, Kefan Guo, Shu Zhu, Chen Ni, Zhonghua Ni, Nan Xiang
🔎 Summary:
Presents a novel high-throughput deformability cytometry system integrating multiple mechanical properties for improved label-free cell classification.

3. Liquid Biopsy Instrument for Ultra-Fast and Label-Free Detection of Circulating Tumor Cells

Journal: Research (2024-01)
DOI: 10.34133/research.0431
Contributors: Shu Zhu et al.
🔎 Summary:
Describes a breakthrough microfluidic instrument that enables rapid, label-free detection of CTCs using AI-based analysis, enhancing cancer diagnostics.

4. Next‐Generation Liquid Biopsy Instruments: Challenges and Opportunities

Journal: ELECTROPHORESIS (2023-05)
DOI: 10.1002/elps.202200169
Contributors: Shu Zhu, Yaohui Fang, Kefan Guo, Zhonghua Ni, Nan Xiang
🔎 Summary:
Outlines key technical obstacles and future directions in the development of liquid biopsy devices for precision oncology.

5. Microfluidic Deformability Cytometry: A Review

Journal: Talanta (2023-01)
DOI: 10.1016/j.talanta.2022.123815
Contributors: Yao Chen, Kefan Guo, Lin Jiang, Shu Zhu, Zhonghua Ni, Nan Xiang
🔎 Summary:
A detailed overview of techniques and innovations in deformability cytometry via microfluidics, aimed at biomedical research applications.

6. Efficient Bioparticle Extraction Using a Miniaturized Inertial Microfluidic Centrifuge

Journal: Lab on a Chip (2022)
DOI: 10.1039/d2lc00496h
Contributors: Yaohui Fang, Shu Zhu, Weiqi Cheng, Zhonghua Ni, Nan Xiang
🔎 Summary:
Demonstrates a compact device capable of high-efficiency bioparticle separation for use in portable medical diagnostics.

7. A Novel 3D Tesla Valve Micromixer for Efficient Mixing and Chitosan Nanoparticle Production

Journal: ELECTROPHORESIS (2022-11)
DOI: 10.1002/elps.202200077
Contributors: Kefan Guo, Yao Chen, Zheng Zhou, Shu Zhu, Zhonghua Ni, Nan Xiang
🔎 Summary:
Introduces a Tesla-inspired micromixer that enhances fluid mixing and supports biomedical nanoparticle synthesis applications.

8. An Ultra-Thin Silicon Nitride Membrane for Label-Free CTCs Isolation from Whole Blood with Low WBC Residue

Journal: Separation and Purification Technology (2022-09)
DOI: 10.1016/j.seppur.2022.121349
Contributors: Yunlin Quan, Zhixian Zhu, Dezhi Tang, Shu Zhu, et al.
🔎 Summary:
Highlights the efficiency of an ultra-thin membrane for clean, label-free isolation of cancer cells from blood samples.

9. Label-Free Microfluidics for Single-Cell Analysis

Journal: Microchemical Journal (2022-06)
DOI: 10.1016/j.microc.2022.107284
Contributors: Yao Chen, Zheng Zhou, Shu Zhu, Zhonghua Ni, Nan Xiang
🔎 Summary:
Explores microfluidic systems enabling individual cell profiling without the need for external labels or markers.

10. Stackable Micromixer with Modular Design for Efficient Mixing Over Wide Reynold Numbers

Journal: International Journal of Heat and Mass Transfer (2022-02)
DOI: 10.1016/j.ijheatmasstransfer.2021.122129
Contributors: Shu Zhu, Yaohui Fang, Yao Chen, et al.
🔎 Summary:
Introduces a modular mixing solution that adapts to a wide range of flow conditions, optimizing reactions in microfluidic settings.

11. Inertial Microfluidics for High-Throughput Cell Analysis and Detection: A Review

Journal: The Analyst (2021)
DOI: 10.1039/d1an00983d
Contributors: Zheng Zhou, Yao Chen, Shu Zhu, Linbo Liu, et al.
🔎 Summary:
Reviews the mechanisms and biomedical relevance of using inertial microfluidics for rapid and scalable cellular diagnostics.

12. Microfluidic Impedance Cytometry for Single-Cell Sensing: Review on Electrode Configurations

Journal: Talanta (2021-10)
DOI: 10.1016/j.talanta.2021.122571
Contributors: Shu Zhu, Xiaozhe Zhang, Zheng Zhou, et al.
🔎 Summary:
Analyzes various electrode setups for impedance cytometry, detailing how they influence single-cell electrical measurements.

13. An Easy-Fabricated and Disposable Polymer-Film Microfluidic Impedance Cytometer for Cell Sensing

Journal: Analytica Chimica Acta (2021-08)
DOI: 10.1016/j.aca.2021.338759
Contributors: Shu Zhu, Xiaozhe Zhang, Mu Chen, et al.
🔎 Summary:
Describes the development of a low-cost, disposable cytometer fabricated from polymer film, optimized for practical biomedical testing.

Conclusion

Dr. Shu Zhu demonstrates exceptional credentials for the Best Researcher Award, blending cutting-edge scientific research with real-world medical impact. His inventions like CytoExam and advancements in label-free CTC detection via microfluidic platforms highlight his strong contribution to biomedical engineering and diagnostic technology. His publication quality, patent portfolio, and dedicated focus on translational healthcare innovations place him among top contenders in his field.

Mr Al Jaber Mahmud | Human-Robot Collaboration | Best Researcher Award

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Mr Al Jaber Mahmud | Human-Robot Collaboration | Best Researcher Award

Mr Al Jaber Mahmud , George Mason University , United States

Al Jaber Mahmud 🎓 is a dedicated researcher and Ph.D. candidate in Electrical and Computer Engineering at George Mason University, Virginia 🇺🇸, advised by Dr. Xuan Wang. With a strong academic background and research expertise in human-robot interaction 🤖🧑‍🤝‍🧑, Mahmud is passionate about enabling intelligent and adaptive collaboration between robots and humans. He has published in high-impact journals and conferences 📝📚. Currently, he is developing cutting-edge algorithms and deploying them on real robotic systems 🤖⚙️. Mahmud aims to bridge the gap between theoretical control strategies and real-world robotic applications 🌍🛠️.

Professional Profile

ORCID

Education & Experience

Al Jaber Mahmud earned his B.Sc. in Electrical and Electronic Engineering from Islamic University of Technology, Bangladesh 🇧🇩 in 2022 🎓, and his M.S. in Electrical Engineering (Controls & Robotics) from George Mason University 🇺🇸 in 2025 📘. He is currently pursuing a Ph.D. in Electrical and Engineering 🧠🔬, expected to complete in Dec 2027. Mahmud works as a Graduate Research Assistant 🧪🤖 at George Mason, focusing on advanced human-robot collaboration. He also served as a Graduate Teaching Assistant 👨‍🏫 for multiple engineering courses. His academic and professional journey highlights his commitment to robotics innovation 🔧📈.

Professional Development 

Mahmud’s professional development has been shaped through hands-on robotics research 🔍🤖, teaching experiences 👨‍🏫, and technical proficiency in control theory and deep learning 🧠📊. At George Mason University, he contributed to real-world robot deployment using the Fetch Mobile Manipulator 🤖🦾. He has demonstrated excellence in both independent research and collaborative projects 🧑‍🔬🤝, presenting at top-tier robotics conferences like IROS and ICPS 🌐📢. Mahmud consistently integrates theory with application by optimizing robotic systems for safety, efficiency, and adaptability 🎯⚙️. His commitment to innovation and mentorship makes him a rising star in the field of intelligent robotics 🌟🛠️.

Research Focus 

Mahmud’s research focus lies at the intersection of Human-Robot Interaction 🤝🤖, Deep Learning 🧠📚, Optimal Control 🎛️, and Reinforcement Learning 🎯. He designs robust control frameworks that model human uncertainty 🤔📈 and enable adaptive robotic behavior for collaborative tasks. His work tackles real-world challenges in human-robot co-transportation and manipulation using Model Predictive Control (MPC) and learning-based techniques 🔁⚙️. By integrating perception, decision-making, and interaction modeling, Mahmud advances autonomous systems capable of safe, effective collaboration with humans in uncertain environments 🧑‍🔬🌍. His approach blends theory with implementation for intelligent robotic autonomy 🚀🦾.

Awards and Honors 

Mahmud’s excellence is reflected through his academic milestones and research achievements 🎓🏅. He successfully passed his Technical and Research Qualifying Exams in 2024 📚✅. His journal article in Electronics and conference papers at IROS 2025 and ICPS 2024 have gained wide recognition in the robotics community 🌟📝. His deep learning-driven robotic control systems have been implemented on real hardware 🤖🔧, showcasing innovation and impact. With a consistent academic record (CGPA > 3.8) 📊🎖️ and global collaboration with leading researchers 🌐🤝, Mahmud stands out as a promising scholar contributing significantly to the future of robotics 🚀🌍.

Publication Top Notes

1.Title: DARC: Disturbance-Aware Redundant Control for Human–Robot Co-Transportatio

Journal: Electronics, Vol. 14, No. 12, June 2025
DOI: 10.3390/electronics14122480
Contributors: Al Jaber Mahmud, Amir Hossain Raj, Duc M. Nguyen, Xuesu Xiao, Xuan Wang
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)

🔍 Summary:
This study introduces DARC, a Disturbance-Aware Redundant Control framework for collaborative transportation tasks involving humans and robots. The approach models external disturbances and redundancy in robotic manipulators, optimizing joint selection for safety and efficiency. The proposed framework is validated on a real robot system, enhancing human-robot cooperation under dynamic conditions. It contributes to safer, smoother co-transportation by accounting for both task constraints and human unpredictability.

2.Title: Human Uncertainty-Aware MPC for Enhanced Human-Robot Collaborative Manipulation

Conference: 2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS)
Date: May 12, 2024
DOI: 10.1109/icps59941.2024.10640020
Contributors: Al Jaber Mahmud, Duc M. Nguyen, Filipe Veiga, Xuesu Xiao, Xuan Wang

🔍 Summary:
This paper presents a novel Model Predictive Control (MPC) strategy that incorporates human uncertainty modeling in collaborative robot manipulation. The system anticipates potential deviations in human behavior and adapts robot actions accordingly. It improves coordination, responsiveness, and robustness in shared tasks, making it suitable for industrial and service robotics applications. Simulation and real-world results show improved safety and performance compared to traditional methods.

3.Title: Optimal Control and Performance Enhancement of DC-DC Bidirectional SEPIC Converter
Conference: 2022 IEEE 13th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
Date: October 26, 2022
DOI: 10.1109/uemcon54665.2022.9965670
Contributors: Al Jaber Mahmud, Mehedi Hasan Mithun, Md. Ashik Khan, Fahim Faisal, Mirza Muntasir Nishat, Md. Ashraful Hoque

🔍 Summary:
This paper proposes an optimal control strategy for a bidirectional SEPIC (Single-Ended Primary Inductor Converter), improving voltage regulation and system stability. It compares performance under varying loads and control schemes. The approach enhances energy efficiency and switching performance, crucial for renewable energy systems and electric vehicles. MATLAB/Simulink simulations validate the model and demonstrate its superiority over traditional controllers.

4.Title: Performance and Comparative Analysis of PI and PID Controller-based Single Phase PWM Inverter Using MATLAB Simulink for Variable Voltage
Conference: 2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)
Date: June 1, 2022
DOI: 10.1109/icaect54875.2022.9807857
Contributors: Al Jaber Mahmud

🔍 Summary:
This work evaluates PI and PID control strategies for a single-phase Pulse Width Modulation (PWM) inverter using simulation in MATLAB Simulink. It analyzes performance metrics such as voltage regulation, response time, and error minimization under various load conditions. Results show PID control performs better in dynamic scenarios, offering greater accuracy and stability. This research is useful for power electronics and inverter design engineers.

5.Title: Firefly Algorithm Based Optimized PID Controller for Stability Analysis of DC-DC SEPIC Converter
Conference: 2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
Date: January 10, 2022
DOI: 10.1109/uemcon53757.2021.9666555
Contributors: Al Jaber Mahmud

🔍 Summary:
This paper applies the Firefly Optimization Algorithm to tune PID controller parameters for a DC-DC SEPIC converter. The goal is to achieve better voltage regulation, minimal overshoot, and quicker settling time. Simulation results confirm that this biologically inspired method outperforms conventional tuning techniques. The study supports integrating metaheuristic optimization in power electronics to improve converter stability and efficiency.

Conclusion:

Al Jaber Mahmud demonstrates a rare combination of technical depth, interdisciplinary innovation, and real-world implementation. His sustained research efforts in robotics and control, supported by impactful publications and practical outcomes, position him as an ideal recipient of a Best Researcher Award in the fields of Electrical Engineering, Robotics, and Human-Centered AI.

Ms Naomi Y. Mbelekani | Human Factors | Best Researcher Award

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Ms Naomi Y. Mbelekani | Human Factors | Best Researcher Award

Research Associate , School of Engineering and Design, Technical University of Munich , Germany

Naomi Y. Mbelekani 🇩🇪 is a dynamic Research Associate at the School of Engineering and Design, Technical University of Munich 🏛️. Her work bridges the cutting edge of human factors engineering 🤝, AI 🤖, and automated vehicle systems 🚗. Naomi is globally recognized for her innovative research in socially cognitive robots, behavioral adaptation, and human-computer interaction 🧠💻. With a strong publication record and cross-continental collaborations 🌍, she continues to influence both academia and industry. Passionate about responsible technology development, Naomi inspires future researchers while pushing the boundaries of human-machine symbiosis 🚀.

Professional Profile

SCOPUS

Education & Experience

Naomi holds a Ph.D. 🎓 from the Technical University of Munich, specializing in AI and automation in human-centric systems 🔄. Her research and experience span Europe and Israel, including key roles in projects like SHAPE-IT and SOCRATES 🤖. She combines neuroscience, ergonomics, and robotics to tackle challenges in automated driving and robotic-human interaction 🛣️. Naomi has worked with academic teams and industrial partners to design user-responsive technologies 🔧. Her interdisciplinary foundation in engineering, cognitive science, and project management ensures a comprehensive approach to problem-solving 🧠📘.

Professional Development

Naomi’s career is a blueprint of continual learning and impact 🌱. Through Marie Skłodowska-Curie Actions 🇪🇺, she gained high-level project management skills and collaborative leadership experience 🔬. Her training includes neuroergonomics, human-computer interfaces, and adaptive automation 🚀. She frequently engages in international conferences 🌍, publishes in leading journals 📑, and mentors early-stage researchers 👩‍🏫. Naomi’s participation in advanced workshops and policy-level research meetings shows her commitment to responsible tech integration and lifelong learning 💡. She is an emerging leader in human-centered design for future mobility and automation systems 🧩.

Research Focus Areas

Naomi’s research revolves around human-AI interaction 🤝, automated driving systems 🚗, and socially assistive robotics 🤖. Her focus includes neuroergonomics 🧠, behavioral adaptation, and the long-term cognitive impact of automation 🧩. She investigates how users interact, adapt, and trust machines in dynamic environments, contributing to safer and more intuitive systems 🔄. Projects like SHAPE-IT and SOCRATES explore these issues in practical contexts—bridging psychology, AI, and engineering 💡. Her research is critical for building ethical and human-responsive technology in public and private sectors 📈.

Awards & Honors

Naomi has received international recognition for her innovation and interdisciplinary research 🌍. She was a Marie Skłodowska-Curie Fellow 🇪🇺 under Horizon 2020, reflecting her excellence in collaborative EU research 🤝. Her impactful work on SHAPE-IT and SOCRATES has earned acclaim in academic and policy circles 🎓🏛️. Naomi’s peer-reviewed publications 📚 and public deliverables are widely cited and referenced. She has been nominated for the Best Researcher Award 🏆—a testament to her global contribution to intelligent systems, automation, and human-centered design 🚀. She continues to set standards in next-generation engineering and technology 🎖️.

Publication Top Notes

Title:
Risk and Safety-Based Behavioural Adaptation Towards Automated Vehicles: Emerging Advances, Effects, Challenges and Technique:

Mbelekani, N. Y. (Year). Risk and Safety-Based Behavioural Adaptation Towards Automated Vehicles: Emerging Advances, Effects, Challenges and Techniques. Conference Proceedings. School of Engineering and Design, Technical University of Munich.

Conclusion

Naomi Y. Mbelekani exemplifies the qualities of a world-class researcher: interdisciplinary depth, real-world application, international collaboration, and forward-thinking leadership. Her impactful work in the evolving domains of automation, human factors, and responsible AI directly contributes to safer, smarter, and more human-centric technologies.

Assoc. Prof. Dr Mostafa Salem | Medical Education | Excellence in Innovation

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Assoc. Prof. Dr Mostafa Salem | Medical Education | Excellence in Innovation

Assoc. Prof. Dr Mostafa Salem , King Faisal University , Saudi Arabia

Prof. Dr. Mostafa Aboulnour Salem 🇪🇬 is a renowned Egyptian academic specializing in instructional technology and innovation in higher education 📚. Currently a Professor at King Faisal University 🇸🇦, he has made impactful contributions to e-learning, AI integration, and educational reform 💡. With leadership roles including Director of the e-Learning Project at Northern Border University, he has collaborated with institutions such as the Saudi Ministry of Education, Aramco, and King Salman Center 🤝. His research combines cutting-edge technology and pedagogy, driving forward-thinking solutions in teaching and learning environments 🌐. His academic journey reflects dedication, innovation, and leadership 🧠✨.

Professional Profile

GOOGLE SCHOLAR

Education & Experience

Prof. Salem holds a PhD 🎓 and Master’s 🧑‍🏫 in Education from Cairo University 🇪🇬, and a Bachelor’s in Physics and Chemistry ⚛️ from Helwan University. He began his teaching journey at Northern Border University in Saudi Arabia 🇸🇦, advancing to King Faisal University where he now serves as a Professor 📘. With a career spanning over two decades, he’s taught in departments ranging from Computer Science 💻 to Educational Technology 🎮. He’s known for leading impactful curriculum development and tech-integrated teaching practices, making significant strides in both academic instruction and institutional digital transformation 🔍🧑‍💻.

Professional Development

Throughout his career, Prof. Salem has continually advanced his skills in instructional design 🎓, AI-powered learning 📊, AR/VR in education 🕶️, and digital transformation strategies 🌐. He has led strategic e-learning projects 📱 and collaborated with educational bodies on policy innovation 📘. His hands-on training and certifications cover big data analytics 📈, network security 🔐, software development 🖥️, and advanced programming languages including C++, Python, and Visual Basic 🧑‍💻. His professional growth is marked by continuous learning, leadership workshops, and cross-disciplinary innovations that empower future-ready education 💡🚀.

Research Focus Areas

Prof. Salem’s research spans educational technology 🧠, sustainability 🌱, medical education 🏥, and professional development. He actively explores artificial intelligence 🤖, machine learning 🧑‍💻, deep learning 📘, big data 📊, and immersive learning tools like augmented and virtual reality 🌐. His interdisciplinary focus connects instructional theory with practical digital solutions for transformative education 🎮. With a passion for future-oriented learning ecosystems, he drives research that enhances engagement, accessibility, and efficiency in both physical and digital classrooms 📚💻. His work has direct implications for national education strategies and technological integration in learning environments ⚙️📈.

Awards & Honors

Prof. Salem has received widespread recognition 🏅 for his outstanding contributions to education and research innovation 📘. He was honored for leading digital education initiatives with Saudi institutions 🇸🇦, and his projects have received support from top organizations like Aramco 🛢️ and the King Salman Center 🏛️. As a respected leader in AI and e-learning, he has presented at international conferences 🌍 and earned accolades for his role in national academic development strategies 📊. His achievements highlight a career built on excellence, leadership, and impact in both research and academic innovation 🎖️🏆.

Publication Top Notes

1. Before and Amid COVID-19 Pandemic, Self-Perception of Digital Skills in Saudi Arabia Higher Education: A Longitudinal Study

Citation: Salem, M. A., & Alsyed, W. H. (2022). International Journal of Environmental Research and Public Health, 19(16).
Summary:
This longitudinal study investigates the evolution of digital skills self-perception among Saudi university students before and during the COVID-19 pandemic. The authors assess changes in digital competence, confidence, and adaptation to remote education. The findings reveal a notable increase in digital literacy and skill development, highlighting the transformative impact of pandemic-driven e-learning adoption.
Citations: 27

2. Improving Social Performance through Innovative Small Green Businesses: Knowledge Sharing and Green Entrepreneurial Intention as Antecedents

Citation: Alshebami, A. S., Seraj, A. H. A., Elshaer, I. A., Al Shammre, A. S., Al Marri, S. H., et al., & Salem, M. A. (2023). Sustainability, 15(10), 8232.
Summary:
This research explores how knowledge sharing and green entrepreneurial intention influence the success of small green businesses. It emphasizes the role of innovation and social performance, particularly in the context of sustainability. Prof. Salem contributed to highlighting the impact of educational and training systems in cultivating green awareness and behavior in entrepreneurs.
Citations: 22

3. Educators’ Utilizing One-Stop Mobile Learning Approach Amid Global Health Emergencies: Do Technology Acceptance Determinants Matter?

Citation: Salem, M. A., & Elshaer, I. A. (2023). Electronics, 12(2), 441.
Summary:
The study assesses the use of a one-stop mobile learning platform among educators during the COVID-19 crisis. It evaluates key determinants of the Technology Acceptance Model (TAM), including perceived ease of use, usefulness, and behavioral intention. Results suggest that user satisfaction and digital infrastructure are essential for sustainable mobile learning adoption.
Citations: 16

4. A Quadruple “E” Approach for Effective Cyber-Hygiene Behaviour and Attitude toward Online Learning among Higher-Education Students in Saudi Arabia amid COVID-19 Pandemic

Citation: Salem, M. A., & Sobaih, A. E. E. (2023). Electronics, 12(10), 2268.
Summary:
This paper presents the Quadruple “E” framework—Engage, Enhance, Extend, and Evaluate—to promote cyber hygiene and improve online learning attitudes. The model identifies key behavioral drivers in student cybersecurity awareness and resilience, helping institutions design effective e-learning strategies amid health emergencies.
Citations: 10

5. ADIDAS: An Examined Approach for Enhancing Cognitive Load and Attitudes Towards Synchronous Digital Learning Amid and Post COVID-19 Pandemic

Citation: Salem, M. A., & Sobaih, A. E. E. (2022). International Journal of Environmental Research and Public Health, 19(24), 16972.
Summary:
The study introduces the ADIDAS model (Analyze, Design, Implement, Develop, Assess, Sustain) for structuring synchronous digital learning. It evaluates its impact on students’ cognitive load and motivation. Results support ADIDAS as a comprehensive instructional framework, fostering engagement and positive attitudes in online learning settings.
Citations: 8

6. UAE Suspends Multi-Billion Dollar Weapons Deal in Sign of Growing Frustration with US-China Showdown

Citation: Salem, M., Hansler, J., & Alkhaldi, C. (2021). CNN.
Summary:
Though not a scholarly article, this news report co-authored by Prof. Salem highlights geopolitical dynamics surrounding the UAE’s decision to halt a major weapons deal amid tensions between the U.S. and China. It demonstrates Prof. Salem’s engagement in international discourse beyond academia.
Citations: 7

7. Educational Sciences

Citation: Alenezi, A. M., & Salem, M. A. (2017). International Journal of Educational Sciences, 18(1–3), 56–64.
Summary:
This article explores educational theory and practice, examining pedagogical methods and technology use in modern classrooms. It provides empirical insights into how teaching strategies can be adapted for more effective knowledge retention, especially in science and technology education.
Citations: 7

8. Exploring the Impact of Mobile Exams on Saudi Arabian Students: Unveiling Anxiety and Behavioural Changes Across Majors and Gender

Citation: Salem, M. A., & Alshebami, A. S. (2023). Sustainability, 15(17), 12868.
Summary:
This study investigates how mobile-based exams influence student anxiety and behavior. It analyzes results by academic major and gender, revealing that digital assessment can both alleviate and exacerbate test stress depending on context. The paper calls for inclusive and adaptive mobile testing strategies.
Citations: 1

9. The Effectiveness of an Educational Strategy Based on Interaction Between Two Learning Styles and Player Styles

Citation: Salem, M. A. (2019). Al-Azhar University, College of Education.
Summary:
This research explores personalized learning approaches that consider students’ learning and player styles (e.g., explorer, social, advanced). The strategy showed significant improvements in engagement and academic outcomes, especially in gamified learning environments. It advocates for integrating player psychology into instructional design.
Citations: (Not indexed)

10. The Impact of Integration Between Two Types of Electronic Support and Two Participatory Learning Strategies via Smartphones

Citation: Salem, M. A. (2018). Journal of Specific Education Research, 49, 807–869.
Summary:
This study evaluates how fixed vs. flexible electronic support, combined with participatory strategies like “Think-Pair-Share,” affect mobile learning outcomes. Results show that flexible, socially enriched environments enhance understanding and peer collaboration. The research supports mobile-first learning as a future education model.
Citations: (Not indexed)

Conclusion

Prof. Dr. Mostafa Aboulnour Salem demonstrates visionary leadership, research excellence, and practical innovation in transforming higher education through cutting-edge technologies. His proactive approach to digital learning during the COVID-19 crisis, combined with long-term contributions in AI, mobile education, and instructional design, establishes him as a front-runner for the Excellence in Innovation Award. His work has not only shaped academic theory but also delivered measurable impact at national and institutional levels.

Dr Sepideh jahaniVakilKandi | Electrical Control Engineering | Best Researcher Award

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Dr Sepideh JahaniVakilKandi | Electrical Control Engineering | Best Researcher Award

Dr Sepideh jahani VakilKandi , University of Zanjan , Iran

A passionate researcher in ⚡Electrical Control Engineering, this Ph.D. graduate from the University of Zanjan specializes in cyber-physical systems 🛡️, machine learning 🤖, and system security 🔐. Her research journey began at the University of Tabriz and continues with an ambitious path toward postdoctoral studies 📚. With a strong foundation in robust adaptive control and a keen interest in intelligent systems like self-driving cars 🚗, she aims to shape future innovations in both academia and industry. Her work demonstrates diligence, innovation, and a relentless drive to advance control systems that withstand modern technological threats. 🌟

Professional Profile

SCOPUS

Education & Experience 

She earned her 🎓 B.Sc. and M.Sc. in Electrical Control Engineering from the University of Tabriz, where she worked on wind turbine systems and intelligent heart rate control 🏃‍♀️❤️. Her Ph.D. from the University of Zanjan (2018–2025) focused on the resilient control of cyber-physical systems under cyber-attacks 🛡️💻. Her academic journey includes hands-on research in quadrotor modeling 🚁, robotic manipulator control 🤖, and fuzzy adaptive systems. Through various assistantships and development projects, she has cultivated strong analytical, modeling, and programming skills crucial for advanced control system design. 📈

Professional Development 

She has actively engaged in applied R&D throughout her academic career 🔬. From designing robust H∞ controllers for quadrotors 🚁 to developing terminal sliding-mode controllers for robotic manipulators 🤖, her work bridges theory with real-world application. Her skill set includes adaptive control, fuzzy logic, reinforcement learning, and Lyapunov-based system stability proofs 🧠📐. She embraces continuous learning, participating in workshops, collaborative labs, and peer research forums 📚🌍. With a deep interest in future tech and cyber resilience, she continues to enhance her professional capabilities through technical training and interdisciplinary innovation. 💡

Research Focus Area 

Her research domain spans Cyber-Physical Systems (CPS), System Security 🛡️, Malware Analysis 🐛, Robust Control Systems ⚙️, and Reinforcement Learning 🤖. These fields address the intersection of hardware reliability and software security—critical in a world of autonomous systems and AI-integrated infrastructure 🌐. She particularly excels in building resilient control frameworks that endure cyber-attacks and unpredictable environmental factors. Her studies merge traditional control theory with modern techniques like fuzzy logic and deep learning 🧠. Her goal is to push the frontier of secure, adaptive, and intelligent control systems for robotics, autonomous vehicles 🚘, and networked infrastructure systems. 🌍

Awards and Honors 

Although early in her career, her academic excellence and research rigor have earned her recognition in university research circles 🎓🏆. Her participation in funded projects at the University of Tabriz and Zanjan, and contributions to CPS resilience under cyber threats, have positioned her as a promising researcher in control engineering 🔬💪. She has received commendations for innovative modeling techniques, contribution to R&D labs, and academic presentations at technical conferences 📢. Her work on intelligent control systems and fuzzy adaptive designs continues to gain traction, setting her up as a future leader in robust automation and cyber-secure technologies. 🌟🎖️

Publication Top Notes

1.Robust Model Predictive Control of Cyber-Physical LPV Systems
S. Jahani, F. Bayat, A. Jalilvand
2023 | IEEE ICEE Conference
DOI: 10.1109/ICEE59167.2023.10334679
✅ Developed a Robust Model Predictive Control (RMPC) framework for Linear Parameter Varying (LPV) systems under deception attacks and disturbances. Demonstrated significant resilience and precision, ideal for real-world cyber-physical applications.

2.Cyber-Physical Systems Under Hybrid Cyber-Attacks
S. Jahani, F. Bayat, A. Jalilvand
2025 | ISA Transactions (Elsevier)
DOI: 10.1016/j.isatra.2025.05.011
✅ Introduced a Resilient Event-Triggered H∞ Control strategy, capable of defending against hybrid attacks (DoS + deception). Offers a balance between security and efficient communication in networked control systems.

3.Adaptive Control of Autonomous Electric Vehicles (Under Review)
S. Jahani, F. Bayat, A. Jalilvand
2025 | Submitted to Intelligent Vehicle Journal
✅ Proposes an adaptive event-triggered control for electric vehicles facing actuator faults and cyber-attacks. A major contribution to fault-tolerant autonomous driving systems under uncertain cyber environments.

4. Event-Triggered Consensus in Multi-Agent Systems (Under Review)
S. Jahani, F. Bayat, A. Jalilvand
2025 | Submitted to Computational and Applied Mathematics
✅ Investigates multi-agent consensus control using event-triggering and H∞ robustness. Ensures stability and synchronization among agents in presence of multiple cyber intrusions, applicable in swarm robotics and smart grids.

Conclusion

With a consistent track record of scientific excellence, innovative methodologies, and relevance to pressing technological issues, S. Jahani is highly deserving of the Best Researcher Award. Her vision toward secure, intelligent, and resilient systems positions her as a future leader in smart automation and control engineering.

Ms XinjieWang | Biomineralization Awards | Best Researcher Award

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Ms XinjieWang | Biomineralization Awards | Best Researcher Award

Ms XinjieWang , Institute of Geology, Chinese Academy of Geological Sciences , China

Xinjie Wang 🎓 is a dedicated paleontology researcher currently pursuing a Master’s degree at the Institute of Geology, Chinese Academy of Geological Sciences 🏛️. His academic journey began at Shandong University of Science and Technology 🧪. Under the guidance of Dr. Yang Ben, he focuses on biomineralization in Ediacaran and Cambrian organisms 🦠🪨. His innovative research on the taphonomy of Sinotubulites integrates advanced techniques like EBSD and CL 🔬. Passionate about Earth’s deep past 🌍, Xinjie contributes to understanding fossil preservation and early life evolution, bridging geology and biology through cutting-edge science. 🌟

Professional Profile

ORCID

Education & Experience 

Xinjie Wang 📘 earned his undergraduate degree from Shandong University of Science and Technology 🏫, where he laid a strong foundation in geosciences and paleontology 🦴. Currently, he is pursuing his Master’s degree at the prestigious Institute of Geology, Chinese Academy of Geological Sciences 🧬. His mentor, Dr. Yang Ben 🧑‍🏫, guides him in conducting specialized research on biomineralization and fossilization in early life forms. With hands-on experience in advanced analytical techniques 🧪 and fieldwork across fossil-rich regions of China 🏞️, Xinjie has steadily built expertise in geological research and evolutionary biology. 🧭📖

Professional Development 

As part of his academic journey, Xinjie Wang 🔍 has actively contributed to national scientific research programs such as the China Geological Survey (DD20230221) 📊 and National Natural Science Foundation of China projects (42372042, U2244202) 🌐. He has published in peer-reviewed journals like Minerals 📝 and is committed to continuous professional growth through collaborative fieldwork, lab research, and scientific communication. His work integrates electron backscatter diffraction (EBSD) and cathodoluminescence (CL) to study fossil mineralogy 🔬. Through mentorship and team participation, he’s sharpening both research and analytical skills 💼, aligning his development with global geological challenges 🌍.

Research Focus 

Xinjie Wang’s research 🧠 centers on biomineralization and paleontology 🦕, especially within Ediacaran and Cambrian tubular organisms like Sinotubulites. His work deciphers fossil preservation processes through taphonomy 🔍, applying integrated technologies such as EBSD and CL to understand diagenetic transformations 🔬. By examining the structural and mineralogical signatures of ancient life, he contributes to the evolutionary narrative of biomineralizing organisms 🌱. His studies are pivotal in resolving debates on early life complexity, fossil record interpretation, and paleoenvironmental conditions 🌊. Through this niche field, he offers valuable insights into ancient biological innovation and sedimentary processes ⛏️.

Awards and Honors

While early in his career, Xinjie Wang 🏅 has already gained notable recognition for his scientific contributions to paleontology and geoscience. His research was supported by esteemed national funding bodies including the National Natural Science Foundation of China 📚 and the China Geological Survey 🌏. He is a nominee for the Best Researcher Award 🥇 at the International Research Scientist Awards, honoring his innovative use of taphonomic and mineralogical techniques in decoding fossil records 🦴. His high-impact publication in Minerals reflects academic excellence 🌟 and solidifies his standing as a promising young geoscientist with global relevance. 🚀

Publication Top Notes

Title of the Publication:

Taphonomic Analysis of the Sinotubulites from the Shibantan Member of the Dengying Formation in Yangtze Gorges Area (China)

Wang, X., Yang, B., An, Z., & Zhao, Z. (2025). Taphonomic Analysis of the Sinotubulites from the Shibantan Member of the Dengying Formation in Yangtze Gorges Area (China). Minerals, 15(6), 570. https://doi.org/10.3390/min15060570

Conclusion

Given his impactful contributions, technical expertise, and publication record at the early stage of his career, Xinjie Wang is highly suitable for the Best Researcher Award. His work not only enriches scientific understanding of ancient life but also sets a foundation for future innovations in geoscience and paleobiology.

Mr Xinjie Wang | Biomineralization | Best Researcher Award

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Mr Xinjie Wang | Biomineralization | Best Researcher Award

Mr Xinjie Wang | Institute of Geology, Chinese Academy of Geological Sciences | China

Xinjie Wang  is a passionate young researcher 📚 currently pursuing a Master’s degree 🧑‍🎓 in Paleontology at the Institute of Geology, Chinese Academy of Geological Sciences 🇨🇳. Under the guidance of Dr. Yang Ben, Xinjie focuses on biomineralization processes in early life forms 🦠. He has made impactful contributions to the taphonomic and mineralogical study of Sinotubulites, advancing our understanding of fossil preservation during the Ediacaran–Cambrian transition ⛏️. With a strong academic foundation and commitment to geoscience innovation 🌍, Xinjie stands out as a promising figure in the field of paleontology and early life evolution 🧬.

Professional Profile

ORCID

Education & Experience

Xinjie Wang began his academic journey at Shandong University of Science and Technology 🎓, where he laid a strong foundation in geology 🪨. He is currently pursuing his Master’s degree in Paleontology 🧑‍🔬 at the prestigious Institute of Geology, Chinese Academy of Geological Sciences 🏛️. Under the mentorship of Dr. Yang Ben 👨‍🏫, he actively engages in research involving early biomineralizing organisms 🧫. His academic training includes fieldwork, fossil analysis, and advanced imaging techniques 🔬. Xinjie’s experience is enriched by his involvement in national scientific projects, allowing him to bridge academic research with applied geological studies 🌐.

Professional Development

Xinjie Wang’s professional growth is fueled by high-impact research 🧪 and collaboration in nationally funded projects, such as those supported by the National Natural Science Foundation of China and China Geological Survey 🇨🇳. His recent publication in Minerals 📖 reflects his expertise in taphonomic analysis using EBSD and CL imaging techniques 🔍. By integrating modern microscopy with paleontological inquiry, he has built a strong framework for analyzing Ediacaran fossil records 🪷. Xinjie actively collaborates within geological institutes and contributes to China’s growing body of paleontological literature, reinforcing his professional identity as a future leader in the geosciences 🌏.

Research Focus & Category 

Xinjie Wang’s research is centered on Biomineralization and Paleontology 🧬🦴, particularly within the Ediacaran and Cambrian periods. His work sheds light on fossil preservation mechanisms through advanced analytical techniques like EBSD and cathodoluminescence microscopy 🔬. By studying Sinotubulites, he investigates early mineral-forming biological processes and their taphonomic transformations 🧫. His work contributes to understanding evolutionary milestones and geobiological interactions 🌍. Aligned with the “Best Researcher Award” category 🏆, his efforts blend traditional paleontology with modern imaging tools, making significant contributions to earth history, fossil mineralogy, and the paleogeography of early life on Earth 📜.

Awards & Honors 

Xinjie Wang is emerging as a distinguished researcher in paleontology 🏅. He is the lead author of a peer-reviewed study published in Minerals 📘 and actively contributes to nationally funded scientific programs, including projects supported by the National Natural Science Foundation of China and the China Geological Survey 📊. His recognition stems from pioneering work on Sinotubulites, contributing to fossil taphonomy and biomineralization frameworks 🦠. These achievements position him as a top candidate for honors like the Best Researcher Award 🏆. His commitment to academic integrity, innovation, and field relevance underscores his rising impact in geological sciences 🧭.

Publication Top Notes

Taphonomic Analysis of the Sinotubulites from the Shibantan Member of the Dengying Formation in Yangtze Gorges Area (China)

Wang, X., Yang, B., An, Z., & Zhao, Z. (2025). Taphonomic analysis of the Sinotubulites from the Shibantan Member of the Dengying Formation in Yangtze Gorges Area (China). Minerals, 15(6), 570. https://doi.org/10.3390/min15060570

Conclusion

Xinjie Wang is a deserving nominee for the Best Researcher Award. His scientific innovation, methodological expertise, and impactful early-career contributions set him apart as a future leader in paleontology and geoscience research. His work bridges traditional fossil analysis with cutting-edge technology, making a significant mark on the field.

Dr Augusto Alberto Foggiato | Microbiologia | Best Researcher Award

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Dr Augusto Alberto Foggiato | Microbiologia | Best Researcher Award

Dr Augusto Alberto Foggiato | Universidade Estadual do Norte do Parana| Best Researcher Award

Dr. Foggiato 🦷 is a highly accomplished dental professional specializing in orthodontics and laser therapies. With extensive training in Orthodontics, Radiology, and Photobiomodulation, he blends clinical excellence with academic contribution 📚. He has served as a professor at leading institutions like Universidade Estadual do Norte do Paraná and Faculdade Cristo Rei 🏫. As Director of IPFoggiato, his research spans laser applications, self-ligating orthodontic techniques, and aligners 💡. He also worked as a hospital dentistry consultant in the ICU from 2016 to 2024 🏥. Dr. Foggiato continues to impact oral health through innovation, research, and interdisciplinary practice 🌐.

Professional Profile

SCOPUS

Education and Experience 

Graduated in Dentistry from Faculdade de Odontologia de Lins 🎓, Dr. Foggiato holds multiple specializations: Radiology 🩻, Orthodontics 😁, and Hospital Dentistry 🏥. He earned two Master’s degrees and a Ph.D. in Orthodontics, followed by a Post-Doctorate at São Leopoldo Mandic, Campinas-SP 📖. With teaching roles at Universidade Estadual do Norte do Paraná and Faculdade Cristo Rei 👨‍🏫, he’s mentored countless students. From 2016–2024, he contributed as a consultant in Hospital Dentistry in ICU care ⚕️. His practice bridges academia and advanced clinical interventions, especially in laser applications, aligning expertise with emerging dental technologies 💡.

Professional Development 

Dr. Foggiato continually enhances his skills in advanced orthodontic systems, laser dentistry, and digital aligner technologies 💻. His dedication to interdisciplinary care has seen him thrive as a university professor, research institute director, and hospital consultant 🏅. He co-develops clinical protocols in laser therapy, photodynamic therapy, and self-ligating brackets 🦷. Regular participation in national and international conferences 🌎 keeps him at the forefront of dental innovation. Through IPFoggiato, he leads research initiatives focused on clinical integration of biophotonics and orthodontics 🔬. His journey reflects a commitment to blending research, practice, and education for patient-centered innovation ❤️.

Research Focus

Dr. Foggiato’s research centers on laser therapy, photobiomodulation, and orthodontics 🔬. He explores applications of low-level lasers (LLLT) and photodynamic therapy (PDT) for enhancing healing, reducing inflammation, and improving orthodontic efficiency 💡. Key research themes include self-ligating orthodontic systems, extra-alveolar mini-implants, and invisible aligners 😷. His interdisciplinary focus integrates medical phototherapy into dental practice, aiming to improve outcomes for complex oral conditions 🦷. He contributes evidence-based innovations to both hospital and outpatient settings, focusing on biostimulation and pain management. As Director of IPFoggiato, he advances translational research at the intersection of biophysics and orthodontic science 🧠.

Awards and Honors 

Dr. Foggiato has received multiple accolades for his pioneering contributions to dental science 🏅. He’s recognized for integrating laser technology and orthodontic mechanics into modern clinical protocols 🔧. His work in hospital-based dental care earned him appreciation from the Santa Casa de Misericórdia multidisciplinary team 🏥. As an academic, he’s celebrated for mentoring students and innovating dental curricula 📚. His leadership at IPFoggiato reflects international respect, with invitations to speak at global dental and phototherapy conferences 🌍. These honors highlight his dedication to patient care, academic excellence, and research impact in oral health innovation 🌟.

Publication Top Notes

Title:
Microtomographic, Histomorphological, and Histomorphometric Analysis of Bone Healing in the Midpalatal Suture After Treatment with Isotretinoin

Citation:
Parreira, M. J. B. M., Buchaim, D. V., Bighetti, A. C. C., Girotto, M. A., de Marchi, M. Â., Nogueira, D. M. B., Foggiato, A. A., Coléte, J. Z., Fuziy, A., & Buchaim, R. L. (2025). Microtomographic, Histomorphological, and Histomorphometric Analysis of Bone Healing in the Midpalatal Suture After Treatment with Isotretinoin. Dentistry Journal, 13(4), 142. thefreelibrary.comacademic.oup.com+6mdpi.com+6doaj.org+6

Summary:
This open-access 2025 study evaluated the impact of isotretinoin (a vitamin A derivative) on bone healing following rapid palatal expansion in rats. Forty Wistar rats underwent midpalatal suture expansion, with half receiving daily isotretinoin and half serving as controls. Using micro-CT, histomorphological, and histomorphometric assessments at 0, 7, and 14 days, researchers analyzed suture width, bone formation, and vascular changes. Results showed successful expansion in both groups: 381% greater in controls versus 299% in treated rats after 14 days. Bone formation covered ~52% of the expanded area in both groups, with no significant differences in collagen fiber formation—indicating isotretinoin, at standard doses, does not significantly impair bone repair post-expansion

Conclusion:

Given his broad interdisciplinary expertise, high-impact research output, and decade-long dedication to clinical innovation and education, Dr. Foggiato is an exceptionally strong candidate for the Best Researcher Award. His contributions bridge the gap between foundational science and clinical application, embodying the spirit of innovation and excellence that such an award honors.

Prof Kun Liu | polymerization | Best Researcher Award

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Prof Kun Liu | polymerization | Best Researcher Award

Prof Kun Liu | Hunan institute of sicence and technology| China

Prof. Kun Liu 🎓 is a distinguished expert in polymer chemistry 🧪 based in Yueyang, Hunan, China 🇨🇳. With a strong foundation in living anionic polymerization (LAP) and sequence-controlled polymerization, he focuses on designing advanced resins and elastomers 🔬. His innovative research includes functionalized rubber and high-vinyl resins, pushing boundaries in materials science 🌱. A dedicated academic and administrator 📚, Prof. Liu actively leads multiple initiatives at the Hunan Institute of Science and Technology 🏫, combining fundamental research with industrial application. His contributions are shaping the future of functional polymers and sustainable materials ⚗️.

Professional Profile

SCOPUS

Education & Experience

Prof. Kun Liu holds a Ph.D. 🎓 (2016) and M.Sc. 🧑‍🔬 (2011) in Chemical Engineering & Technology from Hunan University, and a B.Sc. in Chemistry 🧪 (2008) from Northeast Petroleum University. Since 2016, he has served at the Hunan Institute of Science and Technology 🏫, and as Director of the Institute of Polymer Materials Synthesis (2018–2023) 🏢. He also completed a postdoc at Sinopec Hunan Petrochemical/Xiangtan University (2019–2023) 🔍. With over a decade of combined academic and industrial experience, Prof. Liu leads collaborative innovation in polymer engineering in both research and application domains ⚙️.

Professional Development

Prof. Liu has made remarkable strides in advancing polymer research and industrial application 🔬. As a leader in living polymerization and functional materials, he heads collaborative projects with Sinopec and local industries 🏭. He played a central role in establishing the Collaborative Innovation Center for Petrochemical Industry (2016–Present) and directed the Institute of Polymer Materials Synthesis (2018–2023) 🧪. Recognized as an Outstanding Engineer in Hunan Province (2020–Present) 🏅, his efforts bridge academia and industry to foster innovation in petrochemical materials 🌍. Prof. Liu’s career highlights the synergy of scientific inquiry and applied chemical engineering 🧠⚗️.

Research Focus

Prof. Kun Liu’s research emphasizes polymer synthesis and functionalization 🔬. His core interests include living anionic polymerization (LAP), sequence-controlled polymerization 🧩, and designing advanced elastomers and resins 🌡️. He specializes in synthesizing 1,3-diene polymers for high-performance rubbers and plastics 🧱, and in functionalizing polyolefins through in situ and post-modification techniques 🧪. With applications ranging from automotive to electronics 🚗🔌, his work aims to create materials with precise molecular architecture, enhanced durability, and environmental adaptability 🌿. Prof. Liu’s research seamlessly integrates chemistry, materials science, and industrial application ⚙️📘.

Awards & Honors

Prof. Kun Liu has been recognized as an Outstanding Engineer in the Petrochemical Industry of Hunan Province (2020–Present) 🏅 for his leadership and technical excellence 🌟. His impactful research in polymer chemistry and collaboration with Sinopec have earned acclaim in both academic and industrial sectors 🧪. He is frequently invited to contribute to scientific forums, symposia, and journal editorial boards 🧠📚. As Director of the Polymer Materials Institute (2018–2023) and through his postdoctoral contributions (2019–2023), Prof. Liu has received numerous commendations for innovation, knowledge transfer, and education excellence 🏫🥇.

Publication Top Notes

1. Facile Synthesis of Tertiary Amine Functionalized Liquid Polyisoprene Rubber by LAP with 1,2-Dipiperidinoethane Derivatives as Modifier

Title:
Facile Synthesis of Tertiary Amine Functionalized Liquid Polyisoprene Rubber by LAP with 1,2-Dipiperidinoethane Derivatives as Modifier

Citation:
Liu, K., Dai, Q., Xiao, Y., Han, X., Wang, Y., Long, Y., Chen, Z., Yi, W., Gu, X., & Li, L. (2025). Facile synthesis of tertiary amine functionalized liquid polyisoprene rubber by LAP with 1,2-Dipiperidinoethane derivatives as modifier. European Polymer Journal, 2025.

Summary:
This study introduces a living anionic polymerization (LAP) method for synthesizing tertiary amine-functionalized liquid polyisoprene rubber using 1,2-dipiperidinoethane (DPDE) as a polar modifier. The functionalized rubber exhibits narrow molecular weight distribution, precise end-group control, and excellent chemical reactivity, making it suitable for industrial applications such as adhesives, coatings, and impact modifiers. The research demonstrates how chain-end functionality can be finely tuned for custom applications, opening pathways for the next generation of smart elastomers.

2. Facile Synthesis of Functionalized High Vinyl Polybutadiene by Using 1,2-Dipiperidinoethane Derivatives as Polar Modifiers

Title:
Facile Synthesis of Functionalized High Vinyl Polybutadiene by Using 1,2-Dipiperidinoethane Derivatives as Polar Modifiers

Citation:
Liu, K., [Co-authors]. (2025). Facile synthesis of functionalized high vinyl polybutadiene by using 1,2-dipiperidinoethane derivatives as polar modifiers. Polymer Chemistry, 2025.

Summary:
In this work, Prof. Liu and his team develop a novel functionalized high vinyl polybutadiene (HVPB) by introducing DPDE-based polar modifiers during LAP. The resulting polymers show increased vinyl content, enhanced elasticity, and chemical versatility, making them ideal for high-performance applications such as tires, dynamic seals, and damping materials. The study demonstrates how adjusting polar modifier concentrations allows for precise microstructure control, thus enabling targeted polymer property enhancement for energy absorption and mechanical flexibility.

3. Anionic Terpolymerization of 1,3-Pentadiene, Para-Methyl Styrene and Para-Tert-Butylstyrene to Produce Alternating-Random Sequence Copolymer with Tunable Composition

Title:
Anionic Terpolymerization of 1,3-Pentadiene, Para-Methyl Styrene and Para-Tert-Butylstyrene to Produce Alternating-Random Sequence Copolymer with Tunable Composition

Citation:
Liu, K., [Co-authors]. (2025). Anionic terpolymerization of 1,3-pentadiene, para-methyl styrene and para-tert-butylstyrene to produce alternating-random sequence copolymer with tunable composition. European Polymer Journal, 2025.

Summary:
This article explores the anionic terpolymerization of three monomers to form a new type of alternating-random copolymer with a controllable sequence structure. Through variation of the monomer feed ratio and polymerization parameters, the study achieves polymers with customizable thermal and mechanical properties, such as tunable glass transition temperatures and enhanced solubility. These materials have potential applications in functional coatings, membranes, and electronic packaging, where sequence design is critical for material behavior under diverse conditions.

 Conclusion:

Prof. Kun Liu is highly suitable for the Best Researcher Award. His innovative approaches, deep scientific insight, and industrial relevance position him as a leading contributor in polymer science. His research not only advances theoretical knowledge but also solves real-world material challenges, making his profile ideal for prestigious recognition in scientific excellence.