Ms. Zaib Unnisa | Brain Tumor Diagnosis | Best Researcher Award

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Ms. Zaib Unnisa | Brain Tumor Diagnosis | Best Researcher Award

Ms. Zaib Unnisa | Brain Tumor Diagnosis – PhD Scholar at Superior University Lahore, Pakistan

Zaib Unnisa is a dynamic academic and researcher in the domain of Computer Science and Information Technology, known for her innovative research in artificial intelligence, biomedical data analysis, and intelligent user interfaces. Her academic profile reflects a strong commitment to applying computational tools to real-world problems, particularly within the healthcare and education sectors. Through years of dedicated teaching and impactful publications, she has emerged as a promising figure in the scientific community. Her work bridges theory and practice, focusing on how AI can be ethically and efficiently applied to enhance everyday human experiences and institutional systems.

Profile Verified:

ORCID

Scopus

Google Scholar

Education:

Zaib’s academic foundation is marked by rigorous and progressive learning. She first completed her Master of Computer Science (MCS) from the International Islamic University in Islamabad, where she gained core competencies in software development, algorithm design, and systems architecture. Her passion for advancing technological solutions led her to pursue a Master of Science in Computer Science (MSCS) at The University of Lahore (Gujrat Campus), where she engaged with cutting-edge topics like neural networks and machine learning. Currently, she is enrolled in a Ph.D. program at Superior University, Lahore, focusing on intelligent computing systems, data mining, and medical diagnostics powered by AI.

Experience:

Zaib Unnisa brings over a decade of academic teaching experience. Most recently, she served as a Lecturer in CS & IT at the University of Gujrat (2021–2022), where she taught undergraduate courses and supervised final-year projects in AI and system design. Prior to this, she was a Visiting Lecturer at Superior College, Gujrat (2020–2022), where she led specialized lectures in computer vision and operating systems. She began her academic career as a Lecturer at The Chenab College (2008–2011), delivering foundational computer science education. Across these roles, she emphasized active learning, project-based evaluation, and skill-oriented pedagogy.

Research Interest:

Her research interests are multi-disciplinary, integrating artificial intelligence, machine learning, and data-driven analytics. Zaib is particularly drawn to medical imaging and health diagnostics, exploring how AI models can detect brain and lung tumors with higher certainty. She also investigates EEG-based biometric systems for secure authentication, aiming to enhance digital security through neuroscience. In parallel, she examines AI-powered usability engineering and human-computer interaction, as well as the role of technology in educational transformation. Her recent projects also address challenges in model interpretability and fairness in automated decision-making systems.

Award:

Zaib has received multiple honors for her academic contributions. In 2023, she was recognized with the Online Peer Review Excellence Graduate Award by IOP Publishing Ltd for her thorough and constructive scientific evaluations. The same year, she earned the Outstanding Reviewer Award from IOP, marking her reputation as a diligent academic peer. In 2021, she was awarded a Gold Medal from The University of Lahore for academic distinction in Computer Science and IT. These accolades speak to her dedication, precision, and deep engagement with the academic research process.

Publication:

  • 📘 Beyond Accuracy: Evaluating Certainty of AI Models for Brain Tumour Detection (2025, Computers in Biology and Medicine) — Cited by 11 articles.
  • 🧠 Impact of Fine-Tuning Parameters of a Convolutional Neural Network for Skin Cancer Detection (2025, Scientific Reports) — Cited by 9 articles.
  • 🧬 Threats and Mitigation Strategies for EEG-Based Person Authentication (2025, International Journal of Telemedicine and Applications) — Cited by 6 articles.
  • 💡 Predicting the Usability of Mobile Applications Using AI Tools: The Rise of Large User Interface Models (2024, Procedia Computer Science) — Cited by 7 articles.
  • 🫁 Lung Cancer Detection Using Segmented 3D Tensors and Support Vector Machines (2023, International Journal of Advanced Computer Science and Applications) — Cited by 5 articles.
  • 🧑‍🏫 Interactive Learning Interfaces to Enhance Student Engagement and Performance in Government Education (2023, Journal of Public Policy Practitioners) — Cited by 4 articles.
  • ✍️ A Deep Insight into Signature Verification Using Deep Neural Networks (2021, Advances in Intelligent Systems and Computing) — Cited by 8 articles.

Conclusion:

In summary, Zaib Unnisa’s career reflects a deep-rooted commitment to advancing knowledge, fostering innovation, and applying computing solutions to societal challenges. Her teaching and research are guided by a sense of ethical responsibility, technical expertise, and interdisciplinary collaboration. Her growing citation record and international recognition for peer review work illustrate her emerging influence in the field of computer science. With a forward-looking vision and an adaptable research profile, she continues to contribute meaningfully to both academic and applied technological domains. Zaib stands out as a promising leader and a deserving candidate for recognition through this prestigious award.

 

 

 

Lucas Carvalho Cordeiro | Formal methods | Best Researcher Award

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Prof. Dr. Lucas Carvalho Cordeiro | Formal methods | Best Researcher Award

Prof. Dr. Lucas Carvalho Cordeiro | Formal methods – Professor at University of Manchester, United Kingdom

Dr. Lucas Carvalho Cordeiro is a globally recognized expert in the fields of formal methods, software verification, and cyber-physical systems. Holding a Full Professorship at the University of Manchester, he has established himself as a key figure in advancing automated reasoning and ensuring the security and reliability of modern software systems. His leadership extends across several research centers, where he guides innovative projects that address critical challenges in software engineering and embedded systems. Dr. Cordeiro’s work is distinguished by a rare combination of rigorous academic research and practical impact, as he actively collaborates with industry partners to bring cutting-edge verification technologies into real-world applications. Over the past two decades, his contributions have influenced both foundational theory and applied solutions, enabling more secure and dependable digital infrastructures worldwide.

🌐 Academic Profile

ORCID | SCOPUS

🎓 Education

Dr. Cordeiro’s educational journey laid a strong foundation for his interdisciplinary expertise. He earned his Ph.D. in Computer Science from the University of Southampton, one of the UK’s premier research institutions, where his dissertation focused on SMT (Satisfiability Modulo Theories)-based bounded model checking techniques tailored for embedded systems. This early work positioned him at the forefront of formal verification methods that can detect subtle errors in safety-critical software. Prior to his doctoral studies, he completed a Master’s degree in Informatics at the Federal University of Amazonas in Brazil, where he developed a keen interest in computer science fundamentals, programming languages, and system verification. His undergraduate education in Electrical Engineering at the same university provided a solid grounding in hardware design and embedded systems. Notably, Dr. Cordeiro enriched his academic training through international experience as a CAPES/DAAD scholar in Germany, gaining exposure to different research cultures and advancing his skills in formal methods and software verification. This blend of education across countries and disciplines has enabled him to adopt a holistic and innovative approach to complex engineering problems.

💼 Experience

Dr. Cordeiro’s professional experience spans nearly two decades, bridging academia, research institutes, and industry. At the University of Manchester, he currently leads major initiatives that promote business engagement and research innovation, managing teams that develop state-of-the-art verification tools. His responsibilities include spearheading collaborations with global technology companies, securing funding for groundbreaking projects, and mentoring the next generation of software engineers and researchers. Before his current role, he contributed as a Research Engineer at the University of Oxford, working on advanced software analysis techniques that enhance the reliability of critical systems. Dr. Cordeiro’s industrial experience includes significant software development roles at BenQ-Siemens and NXP, where he applied his theoretical knowledge to real products, tackling challenges related to embedded firmware and hardware-software integration. This blend of academia and industry experience has equipped him with a deep understanding of both the theoretical underpinnings and practical constraints of software verification, enabling him to create tools and methodologies that are robust, scalable, and industry-relevant.

🔬 Research Interest

Dr. Cordeiro’s research focuses on the intersection of formal methods, software engineering, and cybersecurity, with an emphasis on automated verification and validation of complex systems. His primary interests include developing innovative bounded model checking techniques, symbolic execution, and static and dynamic program analysis methods to uncover defects and security vulnerabilities in embedded software and cyber-physical systems. He is the lead developer of several influential verification tools, such as ESBMC (Efficient SMT-Based Context-Bounded Model Checker), JBMC (Java Bounded Model Checker), DSSynth, and FuSeBMC-AI, which integrate AI techniques with formal verification to enhance coverage and accuracy. His research also addresses the security implications of AI-generated code, neural network verification, and trustworthy software development, aiming to establish rigorous foundations for the next generation of intelligent and connected systems. Dr. Cordeiro’s work has a strong interdisciplinary dimension, drawing from computer science, electrical engineering, and artificial intelligence, reflecting the evolving landscape of software verification in the era of AI and IoT (Internet of Things).

🏆 Awards

Dr. Cordeiro has been widely recognized for his excellence in research and leadership. He has received multiple Best Paper Awards, including at prestigious conferences such as SBESC (Symposium on Software Testing, Analysis and Verification) in 2015 and SAC (Symposium on Applied Computing) in 2008, showcasing his ability to produce high-impact research. His papers have also been honored with Distinguished Paper Awards at leading venues like ICSE (International Conference on Software Engineering) in 2011 and ASE (Automated Software Engineering) in 2024. Perhaps most notably, he received the Most Influential Paper Award at ASE 2023, reflecting the long-term significance of his contributions to software verification. Beyond individual papers, Dr. Cordeiro has led teams to 46 first-place wins at international competitions such as SV-COMP (Software Verification Competition) and Test-Comp, underscoring the practical effectiveness of his verification tools in rigorous, competitive settings. His outstanding research achievements have attracted substantial funding exceeding USD 13 million, secured from leading agencies including UKRI, EPSRC, and industrial giants like Intel and ARM, demonstrating trust and recognition from both academic and industrial stakeholders.

📚 Publications

  • 📘 “How secure is AI-generated code: a large-scale comparison of large language models” (2025), published in Empirical Software Engineering, cited by 14 articles. This paper critically evaluates the security risks and robustness of AI-generated code, an emerging and vital area of research.
  • 🧠 “Counterexample Guided Neural Network Quantization Refinement” (2024), appearing in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, cited by 10 articles. It introduces novel methods to improve neural network quantization, enhancing reliability in resource-constrained environments.
  • 🔐 “FuSeBMC v4: Improving Code Coverage with Smart Seeds via BMC, Fuzzing and Static Analysis” (2024), featured in Formal Aspects of Computing, cited by 6 articles. This work advances automated test case generation by combining multiple analysis techniques, improving software testing effectiveness.
  • 🌐 “Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey” (2023), published in IEEE Communications Surveys and Tutorials, cited by 85 articles. A thorough survey exploring emerging edge learning techniques critical for future wireless networks and IoT systems.
  • 🧪 “Towards Global Neural Network Abstractions with Locally-exact Reconstruction” (2023), in Neural Networks, cited by 12 articles. This paper presents abstraction methods that facilitate scalable neural network verification.
  • 📺 “A Fuzzing-Based Test-Creation Approach for Digital TV Receivers” (2023), in Software Testing, Verification and Reliability, cited by 8 articles. It proposes novel fuzz testing approaches tailored to embedded digital TV systems.
  • ⚙️ “ESBMC 6.1: Automated Test Case Generation using Bounded Model Checking” (2021), published in the International Journal on Software Tools for Technology Transfer, cited by 20 articles. This article details the latest advances in ESBMC, a flagship tool for software verification.

✍️ Conclusion

In summary, Dr. Lucas Carvalho Cordeiro exemplifies the highest standards of scholarly excellence and practical impact in software verification and formal methods. His interdisciplinary research has yielded pioneering verification tools that are widely adopted in academia and industry, significantly enhancing the reliability and security of embedded and cyber-physical systems. His leadership in securing large-scale funding, mentoring future researchers, and consistently producing influential publications underscores his status as a visionary in the field. This award nomination recognizes not only Dr. Cordeiro’s exceptional past achievements but also his ongoing commitment to advancing the frontiers of trustworthy computing in an increasingly digital world. His work continues to shape the future of software engineering and cybersecurity, making him a deserving candidate for this prestigious recognition.

Dr. Ru Zhang | Electronics | Best Researcher Award

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Dr. Ru Zhang | Electronics | Best Researcher Award

Dr. Ru Zhang | Wearable Electronics – Research Associate at Shanghai Jiao Tong University, China

Dr. Ru Zhang is an accomplished biomedical engineering researcher currently serving as an assistant researcher at Shanghai Jiao Tong University. With a focus on innovative biosensor technologies and molecular diagnostics, Dr. Zhang’s work integrates cutting-edge materials science with clinical applications to address pressing health challenges such as Alzheimer’s disease, lung cancer, and traumatic brain injury. His multidisciplinary approach combines expertise in organic electrochemical transistors, micro/nanofluidic devices, and advanced data analysis techniques, positioning him at the forefront of translational biomedical research.

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Education:

Dr. Zhang’s academic journey began with a Bachelor of Engineering in Biomedical Engineering from Central South University, where he laid a solid foundation in engineering principles applied to biological systems. He advanced his studies at Shanghai Jiao Tong University, completing a direct-track Ph.D. in Biomedical Engineering. This rigorous training equipped him with deep knowledge and skills in sensor development, bio-interface engineering, and clinical diagnostic tools, preparing him to tackle complex biomedical problems through innovative research.

Experience:

Dr. Zhang’s professional career has evolved through progressively responsible roles reflecting both industrial and academic excellence. After his doctoral studies, he contributed as a Diagnostic Reagent R&D Engineer in the biotechnology sector, gaining valuable practical insights into product development and translational research. Following this, his postdoctoral fellowship at Tongji University School of Medicine allowed him to deepen his clinical research expertise and interdisciplinary collaboration. Currently, as an assistant researcher at Shanghai Jiao Tong University, Dr. Zhang leads multiple projects focusing on biosensor innovation for early disease detection and real-time health monitoring, reflecting his growth as an independent investigator and leader in biomedical engineering.

Research Interests:

Dr. Zhang’s research interests center on the design and application of organic electrochemical transistors and micro/nanofluidic biosensors for molecular diagnostics. His work targets early and non-invasive screening methods for neurodegenerative diseases like Alzheimer’s and various cancers, leveraging engineered 2D materials and hybrid sensor arrays. By integrating advanced materials science with clinical biomarker detection, his research aims to provide precise, rapid, and cost-effective diagnostic tools. Moreover, Dr. Zhang applies computational methods including MATLAB and Python for data analysis, enhancing the sensitivity and specificity of biosensor platforms. His innovative exploration of nanomagnetic robots for targeted lesion navigation exemplifies his commitment to translating technology into real-world clinical solutions.

Awards:

Recognition of Dr. Zhang’s research excellence is reflected in multiple prestigious awards. He was honored with the Shanghai Super Postdoctoral Fellowship in 2022, acknowledging his outstanding postdoctoral contributions. Earlier, he received the Best Poster Award at the Wiley-Shanghai IVD Conference in 2019 and the Best Paper Award at the 3M-NANO 2016 International Conference, highlighting his sustained impact at both national and international levels. These accolades underscore his ability to produce high-quality research outputs and innovative solutions in biomedical engineering.

Publications:

  1. 🧪 Zhang R, Rana M S, Huang L, et al. Antibacterial, Sensitive, Conformable Electronics Device by Engineered Two-Dimensional-Material-Based Organic Electrochemical Transistor. Biosensors and Bioelectronics, 2025. (First Author & Co-Corresponding Author) — Highly cited for advancing wearable biosensor technology.
  2. 🧬 Zhang R, Duan R, Yang D, et al. Fluorinated Amino-acid-doped Microarray-based Biochemical Patches Deciphers in-situ Spatiotemporal Dynamics amidst Intricate Bio-Interfaces. Chemical Engineering Journal, 2025. (Co-First Author) — Influential in biochemical patch sensor development.
  3. 🌟 Zhang R, Rana M S, Huang L, et al. Antibacterial Sensitive Wearable Biosensor Enabled by Engineered-Metal-Boride-Based Organic Electrochemical Transistor and Hydrogel Microneedle. Journal of Materials Chemistry A, 2025. (First Author & Co-Corresponding Author) — Noted for integration of hydrogel microneedles with biosensors.
  4. 🔬 Li Z, Xu E, Zhang Y, Zhang R, et al. Deciphering Spatiotemporal Molecular Pattern of Traumatic Brain Injury by Resveratrol-Engineered Two-Dimensional-Material-based Field-Effect-Transistor Biopatch. Biosensors and Bioelectronics, 2025. (Co-Corresponding Author) — Cited for traumatic brain injury biosensing.
  5. 📉 Wu T, Shen C, Zhao Z, Zhang R, et al. Integrating Paper-Based Microfluidics and Lateral Flow Strip into Nucleic Acid Amplification Device toward Rapid, Low-Cost, and Visual Diagnosis of Multiple Mycobacteria. Small Methods, 2024. (Co-Corresponding Author) — Important contribution to rapid infectious disease diagnostics.
  6. 🧫 Zhang R, Rejeeth C, Xu W, et al. Label-Free Electrochemical Sensor for CD44 by Ligand-Protein Interaction. Analytical Chemistry, 2019. (First Author) — Well-cited for innovative cancer biomarker sensing.
  7. ✨ Zhang R, Zhang J, Tan F, et al. Multi-channel AgNWs-doped Interdigitated Organic Electrochemical Transistors Enable Sputum-based Device towards Noninvasive and Portable Diagnosis of Lung Cancer. Materials Today Bio, 2022. (Co-First Author) — Recognized for noninvasive lung cancer diagnostic device development.

Conclusion:

Dr. Ru Zhang exemplifies the qualities of an exceptional researcher whose innovative work bridges fundamental biomedical engineering and clinical application. His comprehensive education, diverse experience, and pioneering research in biosensor development have yielded impactful publications, significant funding, and multiple prestigious awards. While still advancing in his career, his leadership in high-impact projects and translational technologies marks him as a rising leader poised to make lasting contributions to healthcare diagnostics. Dr. Zhang’s dedication to scientific excellence, innovation, and societal benefit strongly supports his nomination for the Best Researcher Award.

 

 

 

Seung-Bok Choi | Magnetorheological fluid | Best Researcher Award

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Prof. Dr. Seung-Bok Choi | Magnetorheological fluid | Best Researcher Award

Prof. Dr. Seung-Bok Choi | Magnetorheological fluid – Leading Professor at The State University of New York- SUNY, South Korea

Prof. Dr. Seung-Bok Choi is a globally recognized authority in the field of smart materials and magnetorheological (MR) fluid systems. With a distinguished career that spans over four decades, Prof. Choi has been a pioneering force in mechanical engineering, particularly in adaptive structures, vibration control, and intelligent systems. His leadership in research, innovation, and education has not only advanced the field of mechanical systems engineering but also influenced emerging technologies in robotics, aerospace, automotive systems, and biomedical devices. Currently serving as a leading professor at the State University of New York (SUNY) Korea, he continues to contribute actively to academia and industry. His visionary contributions have earned him international respect and recognition, including prestigious editorial positions, keynote lectureships, and numerous scientific awards.

Academic Profile🧑‍🔬

ORCID  | SCOPUS

Education 🎓

Prof. Choi received his Ph.D. and M.S. in Mechanical Engineering from Michigan State University, USA, completing his doctorate in 1990. He began his academic journey with a Bachelor of Science in Mechanical Engineering from Inha University, Korea. His international academic background, combining American engineering principles with Korean innovation, has provided him with a unique edge in cross-disciplinary research and global collaboration. This robust educational foundation has underpinned his long-standing success in both research and teaching.

Experience 🛠️

Prof. Choi dedicated 30 years of his career to Inha University, mentoring a new generation of engineers and researchers. During that time, he supervised 156 Master’s theses, 45 Ph.D. dissertations, and 14 postdoctoral researchers. After his retirement from Inha University, he joined SUNY Korea as a leading professor, where he continues to guide students and conduct advanced research. Beyond teaching, he serves in editorial leadership roles for more than 20 international journals, including Smart Materials and Structures, Sensors, and Scientific Reports. His global influence extends through collaborations and service to professional societies, cementing his status as a leader in smart materials and system dynamics.

Research Interests 🔬

Prof. Choi’s research focuses on the design, modeling, and control of dynamic systems using smart materials such as magnetorheological fluids (MR), electrorheological fluids (ER), shape memory alloys (SMA), and piezoelectric materials. His groundbreaking work in semi-active vibration control systems has found practical applications in vehicle suspension systems, seismic protection, robotics, and biomedical devices. Known for integrating theoretical analysis with experimental validation, Prof. Choi has developed numerous innovative control algorithms and actuator systems, significantly contributing to the field’s technological advancement.

Awards 🏆

Prof. Choi’s exceptional career has been recognized through numerous national and international honors. He is a Fellow of both the National Academy of Engineering of Korea (NAEK) and the Korean Academy of Science and Technology (KAST). He has received multiple distinguished awards, including the 4th Korea Engineering Award (Young Engineer Award), the 8th Duckmyung Engineering Academy Award, and the 2022–2024 Research.com Mechanical and Aerospace Engineering Leader Award in South Korea. These accolades reflect not only the excellence of his work but also his consistent impact on the global scientific community.

Publications 📚

  • 🧲 “Vibration control of MR damper systems for vehicle suspension” – Smart Materials and Structures, 2000 – Cited by 1,200+ articles
  • ⚙️ “Modeling and control of MR seat suspensions for heavy vehicles” – Journal of Sound and Vibration, 2005 – Cited by 980+ articles
  • 🔄 “MR brake systems: Design, analysis, and control” – IEEE/ASME Transactions on Mechatronics, 2008 – Cited by 1,050+ articles
  • 🚗 “Semi-active suspension systems using MR dampers” – Vehicle System Dynamics, 2003 – Cited by 890+ articles
  • 🧪 “Magnetorheological actuators in haptic devices” – Sensors and Actuators A: Physical, 2010 – Cited by 770+ articles
  • 🏗️ “Application of MR fluid in seismic vibration control” – Engineering Structures, 2009 – Cited by 640+ articles
  • 🤖 “Piezoelectric and MR hybrid actuators for robotic arms” – Journal of Intelligent Material Systems and Structures, 2012 – Cited by 580+ articles

Conclusion ✅

Prof. Dr. Seung-Bok Choi stands as a luminary in the realm of smart materials and adaptive mechanical systems. His lifelong dedication to research, teaching, and academic service exemplifies the highest standards of scientific excellence. With transformative work in MR fluid-based control systems, extensive publications, prestigious awards, and a proven legacy of mentorship, Prof. Choi is eminently deserving of the Best Researcher Award. His contributions have not only advanced theoretical knowledge but also driven technological innovation that continues to benefit engineering applications around the world.

Prof. Dr. Zhixiang Xie | Organic Chemistry | Best Researcher Award

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Prof. Dr. Zhixiang Xie | Organic Chemistry | Best Researcher Award

Prof. Dr. Zhixiang Xie | Organic Chemistry – Lanzhou University, China

Professor Zhixiang Xie is a highly accomplished researcher in the field of synthetic organic chemistry, specializing in total synthesis, biomimetic strategies, and advanced reaction methodologies. He has built a reputation for designing and executing complex synthetic routes for bioactive natural products, significantly advancing the understanding of stereoselective and catalytic processes. Over the course of more than twenty years, he has established a prolific academic career marked by innovation, international collaboration, and impactful scholarship. His research not only contributes to fundamental chemistry but also holds broad potential for pharmaceutical and material science applications.

Profile Verified:

ORCID

Education:

Professor Xie’s academic path began with rigorous training in chemical sciences, where he earned both his master’s and doctoral degrees in organic chemistry from a leading Chinese institution. During his early studies, he developed a deep understanding of organic synthesis, chemical reactivity, and mechanistic analysis. These formative years were crucial in shaping his research mindset, enabling him to approach synthetic challenges with a combination of creativity and precision. His formal education laid the foundation for what would become a deeply impactful career in the chemical sciences.

Experience:

Following his doctoral studies, Professor Xie undertook postdoctoral research at one of China’s premier research universities, collaborating with prominent figures in synthetic chemistry. His postdoctoral work further refined his skills in stereoselective synthesis and natural product construction. In the years that followed, he rapidly progressed through academic positions, achieving full professorship. His appointment as a senior visiting fellow at Stanford University allowed him to engage in high-level collaborative research and integrate cutting-edge synthetic strategies from one of the world’s leading laboratories. Throughout his academic tenure, he has supervised numerous graduate students and postdocs, fostering a culture of research excellence.

Research Interest:

Professor Xie’s research interests center around the total synthesis of structurally complex natural products, particularly those with antiviral, anticancer, and neuroprotective activity. He is especially drawn to biomimetic synthesis, where he emulates nature’s strategies to construct intricate molecular frameworks. His work often integrates asymmetric catalysis, C–H activation, photoredox systems, and cascade reactions to achieve highly efficient and selective syntheses. Additionally, he explores the design of new synthetic methodologies for building functional organic molecules, contributing to the fields of medicinal chemistry, sustainable chemistry, and molecular innovation.

Award:

Professor Xie’s exceptional research contributions have been recognized with several national and institutional honors. He was selected for the Program for New Century Excellent Talents in University by the Ministry of Education, a prestigious award recognizing academic leadership and innovation. In recognition of his synthetic achievements, he received the NHU-CJC Innovation Award, honoring his creative breakthroughs in organic synthesis. Furthermore, he has been designated as a Science and Technology Expert in Gansu Province and named a Senior Member of the Chinese Chemical Society, reflecting the broad impact of his scientific contributions across China.

Publication:

📘 Asymmetric total synthesis of benzenoid cephalotane-type diterpenoids (2025), Nature Communications, cited by 25 articles.
🔬 Total Synthesis of Berkeleyone A and Preaustinoid A through Epoxypolyene Cyclization (2025), Angewandte Chemie International Edition, cited by 17 articles.
🧪 Cocrystal of Configurational/Conformational Isomers in Energetic Materials (2025), Journal of Organic Chemistry, cited by 10 articles.
🌿 Scalable Total Synthesis of (+)- and (–)-Codonopiloneolignanin A (2021), Organic Letters, cited by 43 articles.
🔍 Biomimetic Synthesis of Psiguajdianone (2019), Organic Letters, cited by 58 articles.
⚗️ Visible-Light-Induced Charge Transfer Enables Csp³–H Functionalization (2020), Organic Letters, cited by 61 articles.
🧬 Enantioselective aerobic oxidative coupling of glycine derivatives (2020), Chemical Science, cited by 48 articles.

Conclusion:

Professor Zhixiang Xie is a leading researcher whose career exemplifies excellence in innovation, scholarship, and academic leadership. His groundbreaking work in synthetic organic chemistry continues to expand the frontiers of the discipline, offering new tools, frameworks, and insights that have applications far beyond the laboratory. With a strong record of publications, respected awards, and a commitment to training the next generation of scientists, Professor Xie is an ideal candidate for the Best Researcher Award. His work not only contributes to the advancement of chemistry but also resonates with the mission of fostering impactful and transformative scientific research.

 

 

 

Prof. Dr. Claudia Soar | Nutrition Science | Women Researcher Award

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Prof. Dr. Claudia Soar | Nutrition Science | Women Researcher Award

Prof. Dr. Claudia Soar | Nutrition Science – Professor at Universidade Federal de Santa Catarina, Brazil

Dr. Claudia Soar is a distinguished researcher in the field of Public Health Nutrition, currently affiliated with the Universidade Federal de Santa Catarina (UFSC), Brazil. Over the span of her academic career, she has consistently contributed to advancing knowledge in food and nutrition security, obesity prevention, and health education. With an h-index of 12, an i10-index of 15, and over 630 citations, her work has had significant scholarly and social impact, particularly in shaping nutrition policies and interventions for vulnerable populations in Brazil. Her integrated approach combines epidemiological analysis, public policy evaluation, and community-based studies, making her a notable figure in the Latin American research community.

Profile Verified:

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Scopus

Google Scholar

Education:

Dr. Soar holds advanced academic credentials in Nutrition and Public Health, having undergone rigorous training in both theoretical and applied aspects of the discipline. Her educational journey is marked by a strong foundation in the biological sciences, followed by specialized study in nutritional epidemiology and food security governance. Through continued academic development and collaboration with leading researchers, she has cultivated expertise in both academic research and public health implementation.

Experience:

Throughout her career, Dr. Soar has served in various academic and research capacities, including teaching, mentoring, and conducting extensive fieldwork across Brazilian public health institutions. She has worked closely with government and educational sectors to develop, implement, and evaluate policies related to nutrition education and food access. Her role often bridges academia and practice, notably in studies addressing childhood obesity, elderly health, and the functioning of public food programs. Her involvement in multi-institutional research initiatives and congress proceedings, such as the IPLeiria International Health Congress, further illustrates her engagement with both national and international scientific communities.

Research Interest:

Dr. Soar’s primary research interests lie in Food and Nutrition Security (FNS), nutritional epidemiology, public policy evaluation, and school-based health interventions. She focuses on the social determinants of health, investigating how nutrition intersects with inequality, education, and governmental frameworks. Her work also explores the effectiveness of intersectoral approaches to nutrition, such as the role of government-subsidized restaurants and food programs in promoting health equity. She has contributed significantly to developing evaluative models for nutrition programs and policies, placing her research at the intersection of science, society, and governance.

Award:

While formal awards are not listed in her profile, Dr. Soar’s scholarly contributions, citation impact, and sustained commitment to public health nutrition indicate recognition within her field. Her leadership in multi-authored publications, citation strength of key works, and collaborations with policy-makers exemplify the merit and societal value her work holds. These qualities render her highly deserving of the Women Researcher Award.

Publication:

  • 📘 Prevalência de sobrepeso e obesidade em escolares de uma escola pública de Florianópolis (2004) — Revista Brasileira de Saúde Materno Infantil — Cited by 115
  • 📗 A relação cintura quadril e o perímetro da cintura associados ao índice de massa corporal em estudo com escolares (2004) — Cadernos de Saúde Pública — Cited by 94
  • 📙 Prevalência de fatores de risco cardiovascular em idosos não institucionalizados (2015) — Revista Brasileira de Geriatria e Gerontologia — Cited by 36
  • 📕 Adequação normativa dos planos estaduais de segurança alimentar e nutricional no Brasil (2018) — Cadernos de Saúde Pública — Cited by 33
  • 📝 Government-subsidized restaurants as promoters of the realization of the human right to adequate food: proposal of an evaluation model (2019) — Revista de Nutrição — Cited by 12
  • 📒 Meal and snack patterns of 7–13-year-old schoolchildren in southern Brazil (2021) — Public Health Nutrition — Cited by 25
  • 📓 Analysis of the implementation of Food and Nutrition Education actions in public schools in a capital city in southern Brazil (2023) — Revista de Nutrição — Cited by 7

Conclusion:

Dr. Claudia Soar represents a powerful voice in the field of food and nutrition security, having combined academic rigor with meaningful societal contributions. Her research has influenced public health strategies for over two decades, particularly in child and elderly nutrition, educational programming, and public policy evaluation. Though much of her work has focused on Brazil, the methods and insights she offers have broader applicability across global contexts. With a proven record of impact, a clear vision for equitable food systems, and an ongoing commitment to academic excellence, Dr. Soar is a fitting nominee for the Women Researcher Award. Her career exemplifies the integration of research with policy and practice, setting a high standard for future women leaders in the field of public health nutrition.

 

 

 

Prof. Dr. Hui Li | Economics | Best Researcher Award

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Prof. Dr. Hui Li | Economics | Best Researcher Award

Prof. Dr. Hui Li | Economics – Dean at Kaifeng University, China

Dr. Hui Li is a dedicated researcher at Kaifeng University, China, whose academic journey and scientific contributions focus on the development of sustainable energy solutions through advanced nanotechnology. With an h-index of 7, over 350 citations across 9 peer-reviewed articles, and growing recognition in the field of triboelectric nanogenerators, Dr. Li is emerging as a promising figure in energy research. His interdisciplinary expertise spans nanomaterials, mechanical systems, and energy harvesting technologies, making his work both impactful and timely within the global transition toward renewable energy.

Profile Verified:

Scopus

Education:

Dr. Li has built a strong academic foundation in the field of energy and materials science through rigorous training and research-oriented education. Though specific degree information is not publicly detailed, his scholarly work reflects a well-rounded understanding of physics, electrical engineering, and applied materials science. His research contributions, particularly in high-level journals, indicate a research-intensive educational background that has equipped him with the tools to pursue cutting-edge innovation in energy conversion and storage technologies.

Experience:

Currently serving at Kaifeng University, Dr. Li has accumulated practical experience in collaborative, cross-functional research environments. He has worked alongside multidisciplinary teams to design, fabricate, and evaluate systems based on triboelectric nanogenerators, a novel energy-harvesting technology. His professional activities have included contributing to experimental design, data analysis, and writing for high-impact publications. Through his academic role, he also likely mentors students and participates in university-level scientific activities that reinforce the broader dissemination of knowledge and the promotion of renewable energy research.

Research Interest:

Dr. Li’s primary research interests center around sustainable energy systems, particularly through the use of triboelectric nanogenerators (TENGs). He is fascinated by the ability of these devices to harvest ambient mechanical energy—such as waves, vibrations, or human motion—and convert it into usable electricity. His work explores frequency upconversion, system networking, and material optimization, all aimed at increasing the efficiency and scalability of nanogenerator systems. Additionally, he is interested in interdisciplinary methods that link materials science, nanotechnology, and electronics to develop smarter, greener technologies for the future.

Award:

Although there is currently no record of formal grants or major awards listed under Dr. Li’s Scopus profile, his steadily increasing citations, high-impact publications, and continued research productivity represent a strong trajectory toward future academic and institutional recognition. His contributions are beginning to receive attention in the academic community, which positions him well for research awards that honor innovation, collaboration, and sustainability in science.

Publication 📚:

 📘 Design of an efficient blue energy harvesting system based on triboelectric nanogenerators with frequency upconversion and networking strategies

Conclusion:

Dr. Hui Li exemplifies the qualities of an emerging leader in energy science, with a focused research agenda, growing citation impact, and a clear commitment to innovation in renewable technologies. While still in the early-to-mid phase of his research career, his contributions to triboelectric nanogenerators are technically sound, forward-looking, and socially relevant. His potential for future impact is substantial, especially as he continues to publish in high-impact journals and collaborates with diverse scientific teams. Dr. Li’s profile aligns well with the goals of the Best Researcher Award, making him a strong and deserving nominee for recognition based on his scientific dedication, interdisciplinary innovation, and research promise.

 

 

 

 

Ms. Soree Hwang | Biomedical Engineering | Best Researcher Award

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Ms. Soree Hwang | Biomedical Engineering | Best Researcher Award

Ms. Soree Hwang | Biomedical Engineering – Researcher at KIST | Korea Institute of Science and Technology, South Korea

So Ree Hwang is an emerging biomedical engineering researcher whose multidisciplinary expertise in mechanical engineering, design, and biomedical systems positions her at the forefront of AI-integrated healthcare innovation. Currently pursuing her Ph.D. in Biomedical Engineering at Korea University and conducting research at the Korea Institute of Science and Technology (KIST), she brings a unique fusion of engineering principles and data-driven health solutions. Her work centers on wearable sensor technologies, machine learning, and neurorehabilitation platforms, with a clear commitment to transforming clinical care through personalized, non-invasive, and remote monitoring systems. As a student researcher, her contributions are both technically rigorous and socially impactful, targeting populations with urgent healthcare needs such as stroke patients and frontline workers.

Profile Verified:

Scopus | Google Scholar

Education:

Hwang’s educational journey reflects a strong foundation in engineering disciplines, which has evolved into highly specialized research in healthcare technologies. She holds a Bachelor’s degree in Mechanical Engineering, followed by a Master’s in Design and Engineering. These programs equipped her with deep technical knowledge and problem-solving capabilities, allowing her to apply advanced engineering concepts to human health systems. Currently pursuing a Ph.D. in Biomedical Engineering at Korea University, she is now applying data-driven methodologies to solve real-world clinical challenges. Her academic path shows a consistent upward progression from foundational mechanics to AI-assisted medical technology.

Experience:

Professionally, Hwang has gained extensive research experience through her role at KIST, a premier research institute known for advanced technological development. She has contributed to over 16 research projects, covering domains such as gait analysis, fatigue detection, and motor function evaluation. Her collaborative initiatives include working with Korea University Hospital and the Korea Institute of Machinery & Materials (KIMM) on technologies that promote neuroplasticity in stroke rehabilitation. She also collaborated on the development of an AI-powered stress monitoring system tailored for police officers. These projects illustrate her ability to engage in high-level, cross-disciplinary research that directly translates into real-world healthcare improvements.

Research Interest:

Hwang’s research interests include AI-based health monitoring, smart wearable technologies, neurorehabilitation, and digital healthcare applications for special populations. She is especially focused on developing systems that use inertial measurement units (IMUs), electromyography (sEMG), and machine learning algorithms to detect fatigue, classify abnormal gait, and assess stroke severity. Her goal is to enable remote, continuous health monitoring systems that assist clinicians in delivering customized rehabilitation and stress management therapies. By combining physiological signal analysis with deep learning architectures, she aims to improve both diagnostic accuracy and patient autonomy in the recovery process.

Award:

Though she is still in the early stages of her career, So Ree Hwang has demonstrated excellence in academic and applied research that makes her a strong candidate for the Best Researcher Award. She is actively involved in two patent applications and is a member of recognized professional bodies such as the Korean Society for Precision Engineering and the Korean Society of Medical & Biological Engineering. These affiliations, coupled with her multidisciplinary achievements and collaborative projects, establish her as a rising talent whose work is already contributing meaningfully to the biomedical field.

Publications:

  • 🧠📶 “A Multimodal Fatigue Detection System Using sEMG and IMU Signals with a Hybrid CNN-LSTM-Attention Model”, Sensors, 2025 – Main Author, Vol. 25, Article 3309.
  • 🦿📊 “Machine Learning-Based Abnormal Gait Classification with IMU Considering Joint Impairment”, Sensors, 2024 – Main Author, Vol. 24, Article 5571.
  • 🧬🚶 “Classification of Gait Phases Based on a Machine Learning Approach Using Muscle Synergy”, Frontiers in Human Neuroscience, 2023 – Co-Author, Vol. 17, Article 1201935.
  • 🔁🧠 “Classification of Stroke Severity Using Clinically Relevant Symmetric Gait Features Based on Recursive Feature Elimination with Cross-Validation”, IEEE Access, 2022 – Co-Author, Vol. 10, pp. 119437–119447.
  • ⛹️📐 “Prediction of Lower Extremity Multi-Joint Angles During Overground Walking Using a Single IMU with a Low Frequency Based on an LSTM Recurrent Neural Network”, Sensors, 2021 – Co-Author, Vol. 22, Article 53.
  • 🖨️🧪 “Property Analysis of Photo-Polymerization-Type 3D-Printed Structures Based on Multi-Composite Materials”, Applied Sciences, 2021 – Main Author, Vol. 11, Article 8545.

Conclusion:

So Ree Hwang stands out as a highly motivated and innovative researcher who is already making meaningful contributions to AI-driven healthcare systems. Her integration of engineering principles with clinical insights allows her to design impactful solutions for rehabilitation and stress monitoring. With a solid academic background, multiple high-quality publications, and successful collaborative research efforts, she exemplifies the qualities of a future leader in biomedical research. Recognizing her with the Best Researcher Award would not only validate her significant accomplishments but also inspire further innovations in digital health and neurorehabilitation technologies.

 

 

Ms. mengjiao lu | Biosensors | Best Researcher Award

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Ms. Mengjiao lu | Biosensors | Best Researcher Award

Ms. Mengjiao lu | Biosensors – Guizhou University, China

Dr. Mengjiao Lu is an emerging researcher at Guizhou University, China, known for her innovative contributions to nanomaterials and biosensor development. Her research centers on photoelectrochemical (PEC) immunoassays enhanced by advanced hybrid materials, particularly ZnIn₂S₄/TiO₂ nanorod heterojunctions integrated with multifunctional hydrogels. With a strong foundation in interdisciplinary science, she has quickly built a reputation for her scientific rigor and commitment to addressing biomedical challenges through material innovation. Her work bridges chemistry, materials science, and medical diagnostics, aiming to create ultrasensitive, reliable biosensing platforms for clinical applications.

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ORCID

Scopus

Education:

Dr. Lu pursued her higher education in the field of materials science and nanotechnology, where she developed a deep understanding of semiconductor materials, surface modification techniques, and biosensor systems. During her academic training, she specialized in photoelectrochemical systems and hydrogel-based composite materials. Her graduate and postgraduate studies equipped her with the theoretical knowledge and practical skills essential for high-impact research, particularly in the synthesis and characterization of functional materials for biomedical detection. This educational background has formed the basis of her research focus on smart analytical technologies.

Experience:

Dr. Lu currently serves as a researcher at Guizhou University, where she has collaborated on interdisciplinary projects related to PEC biosensing and material interface engineering. She has worked with a diverse team of scholars and co-authors across various institutions, contributing to both theoretical and experimental aspects of research. Her experience includes material synthesis, device fabrication, sensor validation, and application testing. In addition to publishing peer-reviewed articles, she has contributed to collaborative reviews and played an active role in laboratory-based innovation, establishing herself as a technically skilled and research-oriented professional.

Research Interest:

Dr. Lu’s core research interest lies in the development of PEC-based biosensors using nanostructured semiconductors and hydrogels. Her work focuses on creating hybrid materials that enhance signal output and detection sensitivity for clinical diagnostics. She is particularly interested in heterojunction systems like ZnIn₂S₄/TiO₂, which offer synergistic photoelectric properties, and in soft hydrogel matrices that improve biocompatibility and analyte interaction. Her studies aim to improve the performance and reliability of biosensors used for detecting disease biomarkers, environmental toxins, and small molecules, advancing the field of smart analytical devices.

Award:

Although Dr. Lu has not yet received major international awards, her scholarly reputation is rapidly growing. With more than 340 citations from 253 documents and an h-index of 8, her research has clearly gained academic recognition. Her work is frequently cited in high-impact publications, reflecting both relevance and innovation. Her potential for awards in the near future is evident through her publication record, interdisciplinary collaborations, and contributions to high-demand applications in biomedical technology.

Publications 📚:

🌟 “ZnIn₂S₄/TiO₂ NRs heterojunction-multifunctional hydrogel hybrid for ultrasensitive photoelectrochemical immunoassay” – Biosensors and Bioelectronics (2023), cited by 42 articles.
🔬 “Research Progress of Biosensor Based on Organic Photoelectrochemical Transistor” – Sensors and Actuators B: Chemical (2022), cited by 37 articles.

Conclusion:

In conclusion, Dr. Mengjiao Lu exemplifies the ideal candidate for the Best Researcher Award due to her pioneering work in nanostructured biosensors and PEC detection systems. Her innovative research, publication impact, and technical excellence place her at the forefront of interdisciplinary science. Although still early in her career, her contributions have already advanced the field of photoelectrochemical biosensing, with promising applications in medical diagnostics and environmental monitoring. Her continuous drive for innovation, strong academic background, and growing international recognition make her a compelling nominee for this prestigious honor.

 

 

 

Dr. peyman peyrovan | Numerical Analysis | Best Researcher Award

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Dr. peyman peyrovan | Numerical Analysis | Best Researcher Award

Dr. peyman peyrovan | Numerical Analysis – Independent Researcher at shahed university, Iran

Dr. Peyman Peyrovan is a dedicated researcher in applied mathematics with expertise in numerical analysis, particularly in delay differential and integro-differential equations. His academic and research journey reflects a strong focus on solving complex mathematical problems with direct applications in healthcare and cybersecurity. Known for integrating rigorous theory with practical computation, Dr. Peyrovan has made notable contributions to the fields of inverse problems, regularization, and computational modeling. His vision lies in leveraging mathematics to address real-world challenges through algorithmic development and intelligent modeling. With an early but impressive track record, he stands out as a rising scholar in scientific computing and applied analysis.

Profile Verified:

ORCID

Education:

Dr. Peyrovan obtained his Ph.D. in Applied Mathematics (Numerical Analysis) from Shahed University in Tehran, Iran. His doctoral thesis, supervised by Dr. A. Tari, focused on developing and analyzing collocation methods for solving delay Volterra integro-differential equations with weakly singular kernels using continuous piecewise polynomial functions. Before his doctoral studies, he earned his M.Sc. in Applied Mathematics from Kharazmi University, specializing in regularization and inverse problems—particularly the determination of optimal regularization parameters for discrete ill-posed problems. His academic foundation was built during his undergraduate studies in mathematics at Damghan University, where he developed a strong theoretical background and problem-solving skills.

Experience:

Throughout his academic career, Dr. Peyrovan has accumulated substantial research experience in both theory and application. He has designed adaptive numerical algorithms for solving delay integral equations relevant to cybersecurity threat detection and system vulnerability analysis. In the biomedical domain, he developed MATLAB-based simulation tools for modeling tumor growth and biological feedback using delay systems. His contributions to MRI image reconstruction through inverse problem techniques have led to improved accuracy and reduced computational noise. He is proficient in MATLAB and Maple for numerical computing, and LaTeX for technical documentation. Dr. Peyrovan’s work demonstrates his capacity to bridge abstract mathematics with technological applications in data-driven domains.

Research Interests:

Dr. Peyrovan’s primary research interests include numerical methods for solving integral and integro-differential equations with delays, regularization of inverse problems, and computational modeling for real-life systems. He is particularly interested in delay systems with weakly singular kernels and their applications in healthcare, such as modeling biological responses and image reconstruction, and in cybersecurity, including the prediction of cyberattack propagation. He is actively exploring the synergy between machine learning and numerical analysis, aiming to develop hybrid models that combine data-driven insights with analytical rigor for intelligent system modeling and anomaly detection.

Awards:

In recognition of his academic excellence, Dr. Peyrovan was awarded the Top Graduate Student Award at Shahed University in 2024. This honor reflects both his outstanding performance during his Ph.D. studies and his commitment to advancing the field of applied mathematics. His early achievements demonstrate his potential to contribute further as a leader in numerical research, algorithm development, and interdisciplinary problem solving.

Publications:

📘 “Convergence analysis of collocation solutions for delay Volterra integral equations with weakly singular kernels” – Applied Mathematics and Computation, 2025, frequently cited in delay equation research.

📗 “Collocation method for Volterra integro-differential equations with piecewise delays” – Journal of Computational and Applied Mathematics, 2026, referenced in adaptive modeling studies.

Conclusion:

Dr. Peyman Peyrovan exemplifies the qualities of a forward-thinking researcher whose work sits at the intersection of mathematics, computer science, and real-world problem-solving. His research contributions in numerical delay equations, inverse problems, and algorithm development have been both technically rigorous and societally relevant. With a growing body of publications, experience in cross-disciplinary applications, and a clear research vision, he demonstrates strong potential for long-term academic and practical impact. Dr. Peyrovan is a highly deserving nominee for the Best Researcher Award, and his trajectory suggests continued innovation and leadership in applied mathematical research.