Leyi Zhao | Computer Science | Best Researcher Award

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Dr. Leyi Zhao | Computer Science | Best Researcher Award

Doctor, Beijing University of Chinese Medicine, China

Dr. Leyi Zhao is a dedicated clinical doctoral researcher in Integrative Medicine at the prestigious Beijing University of Chinese Medicine. With a keen interest in digestive tract diseases, Dr. Zhao specializes in studying precancerous lesions, tumors, and the intricate relationship between the immune environment and disease progression. Passionate about blending traditional medicine with modern computational techniques, Dr. Zhao integrates computer language and data analysis to establish innovative prognostic models, enhancing clinical applications. With multiple completed and ongoing research projects, Dr. Zhao’s contributions to the field of immunotherapy and colorectal cancer prognosis are highly impactful.

Publication Profile

ORCID

🎓 Education

Dr. Zhao is currently pursuing a doctorate in Integrative Medicine at Beijing University of Chinese Medicine, a renowned institution for traditional and modern medical research. This academic journey has equipped Dr. Zhao with a strong foundation in both traditional Chinese medical practices and cutting-edge clinical research methodologies.

💼 Experience

With extensive research experience, Dr. Zhao has led and contributed to multiple research projects focusing on colorectal cancer, immune microenvironments, and predictive modeling in oncology. Through a blend of experimental studies and computational approaches, Dr. Zhao has contributed significantly to understanding the impact of tertiary lymphoid structures (TLS) on tumor prognosis and immune response. In addition to academic research, Dr. Zhao has been involved in consultancy and industry-based projects, furthering the practical application of scientific findings.

🏆 Awards and Honors

Dr. Zhao’s research excellence has been recognized through publications in high-impact journals indexed in SCI and Scopus. The innovative work in colorectal cancer prognosis and immunotherapy has garnered citations and recognition within the scientific community. As an active contributor to the field, Dr. Zhao has been nominated for the prestigious Best Researcher Award at the Cryogenicist Global Awards.

🔬 Research Focus

Dr. Zhao’s primary research focus lies in immunotherapy for tumors, particularly in colorectal cancer. The groundbreaking research involves developing a TLS-based prognostic model that explores immune cell interactions within tumors. This model holds potential for predicting patient prognosis and treatment responsiveness, offering valuable insights into personalized medicine. Furthermore, Dr. Zhao’s interdisciplinary approach integrates network pharmacology, computational modeling, and traditional Chinese medicine, enhancing the precision and effectiveness of cancer treatments.

🔗 Publications

The Impact of Tertiary Lymphoid Structures on Tumor Prognosis and the Immune Microenvironment in Colorectal Cancer. Biomedicines, 2025; 13(3):539
🔗 DOI: 10.3390/biomedicines13030539

 Limonin ameliorates indomethacin-induced intestinal damage and ulcers through Nrf2/ARE pathway. Immun Inflamm Dis, 2023; 11(2):e787
🔗 DOI: 10.1002/iid3.787

Chinese patent herbal medicine (Shufeng Jiedu capsule) for acute upper respiratory tract infections: A systematic review and meta-analysis. Integr Med Res, 2021; 10(3):100726
🔗 DOI: 10.1016/j.imr.2021.100726

Deciphering the Mechanism of Siwu Decoction Inhibiting Liver Metastasis by Integrating Network Pharmacology and In Vivo Experimental Validation. Integr Cancer Ther, 2024; 23:15347354241236205
🔗 DOI: 10.1177/15347354241236205

🔚 Conclusion

Dr. Leyi Zhao’s research contributions are shaping the future of colorectal cancer treatment and immune microenvironment analysis. With a strong foundation in integrative medicine and a passion for computational research, Dr. Zhao continues to push the boundaries of medical science, making a profound impact on oncology and personalized medicine. As a nominee for the Best Researcher Award, Dr. Zhao’s work exemplifies innovation, dedication, and a commitment to improving patient outcomes worldwide. 🌍

Mr. André Guimarães | Computer Science | Best Researcher Award

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Mr. André Guimarães | Computer Science | Best Researcher Award

Researcher, University of Beira Interior, Portugal

Andre Guimarães is a dedicated researcher and educator in the fields of Engineering Sciences, Industrial Engineering, and Management. With a strong academic background, he has contributed significantly to various research projects related to Industry 4.0 and digital transformation. He currently holds research positions at the University of Beira Interior and the Polytechnic Institute of Viseu, Portugal. Alongside his academic work, Andre has accumulated practical experience in industrial environments, particularly in production management and technical consulting, where he focuses on quality management, lean methodologies, and engineering innovations. He is also a passionate educator, teaching engineering and management-related courses at the higher education level. 📚🔬

Publication Profile

ORCID

Education:

Andre’s educational journey includes a Master’s degree in Mechanical Engineering and Industrial Management from the Polytechnic Institute of Viseu. He is currently pursuing a PhD in Industrial Engineering and Management at the University of Beira Interior. Additionally, Andre holds several postgraduate qualifications, including a specialization in Industry 4.0 and Digital Transformation from the Polytechnic Institute of Porto. His training also includes certifications in quality management, Six Sigma, lean manufacturing, and other engineering disciplines. 🎓📖

Experience:

Andre’s professional career spans both academia and industry. He has worked as a researcher at the University of Beira Interior and the Polytechnic Institute of Viseu, contributing to cutting-edge research in mechanical and industrial engineering. Additionally, Andre has extensive industrial experience, having served as the Production Manager at IPROM – Products Industry Metallics Ltd, where he oversaw production processes and managed technical operations. As a consultant and facilitator at the Welding and Quality Institute, Andre applies his expertise in quality management systems and continuous improvement. 🏭⚙️

Awards and Honors:

Andre Guimarães has been recognized for his contributions to both research and industry. He is a full member of the Order of Engineers in Portugal and a fellow at FCT Research. His work has been acknowledged through various academic and industry accolades, cementing his reputation as a skilled professional and educator in his field. 🏅🌟

Research Focus:

Andre’s research interests are deeply rooted in Industry 4.0 technologies, digital transformation, lean management, and quality systems in industrial engineering. His research aims to bridge the gap between theoretical frameworks and practical applications in engineering, with a focus on improving production efficiency, implementing digital technologies, and optimizing management processes in industrial environments. His recent projects explore advanced methodologies in electromechatronics and systems research. 🔍📊

Conclusion:

With a rich academic background and a wealth of practical experience, Andre Guimarães stands at the intersection of research and industry, contributing to the evolution of engineering practices. His work, driven by a passion for innovation and education, continues to shape the future of industrial engineering and management in Portugal and beyond. Andre’s ongoing commitment to advancing the field through both research and practical applications makes him a valuable asset to the academic and industrial communities. 🚀🌍

Publications:

The influence of consumer, manager, and investor sentiment on US stock market returnsInvestment Management and Financial Innovations

Effects of Lean Tools and Industry 4.0 technology on productivity: An empirical studyJournal of Industrial Information Integration

Método Delphi modificado para abordar a transformação digital na gestão de ativosRevista de Ativos de Engenharia

Lean philosophy and Value Engineering methodologies. Their relations and synergy using Bert a natural language processing modelCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Modificação do Método Delphi para Aplicação num Questionário sobre a Transformação Digital na Gestão de AtivosCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Overview of the use of data assets in the context of Portuguese companies: Comparison between SMEs and large companiesCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Comparative analysis of welding processes using different thermoplasticsInternational Journal of Integrated Engineering

Yunhyung LEE | Computer science| Best Researcher Award

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Prof. Dr. Yunhyung LEE | Computer Science | Best Researcher Award

Professor, Korea Institute of Maritime and Fisheries Technology, South Korea

Dr. Yunhyung Lee is a distinguished professor at the Korea Institute of Maritime and Fisheries Technology and an adjunct professor at Korea Maritime and Ocean University. With an academic journey spanning nearly two decades, Dr. Lee has made significant contributions to marine systems engineering, control systems, and maritime research. A prolific researcher and academician, he is known for his innovative approaches in marine electric systems, fuzzy control, and genetic algorithms. His commitment to fostering maritime education and cutting-edge research has earned him several accolades and a global reputation in his field. 🌐✨

Publication Profile

ORCID

Education 🎓

Dr. Lee graduated summa cum laude with a Bachelor’s degree in Marine System Engineering from Korea Maritime and Ocean University in 2002. He further earned his Master’s degree in 2004 and completed his Ph.D. in Mechatronics Engineering in 2007. His academic excellence is reflected in multiple awards, including the President’s Award for graduating with the highest honors. 🏆📚

Professional Experience 💼

Dr. Lee began his academic career as a part-time lecturer at Korea Maritime and Ocean University and Youngsan University. From 2008 to 2014, he served as a professor at the Korea Port Training Institute before joining the Korea Institute of Maritime and Fisheries Technology in 2014. Simultaneously, he has been an adjunct professor at Korea Maritime and Ocean University since 2015. His practical experience includes spearheading innovative research projects and consulting for industry collaborations. ⚙️🛳️

Awards and Honors 🏅

Dr. Lee’s outstanding achievements have been recognized through numerous awards, including the Albert Nelson Marquis Lifetime Achievement Award (2018) and the Young Researcher Award from the Korean Society of Marine Engineering (2015). He has also been honored for his contributions to education and research with awards such as the Best Paper Award by the Korean Federation of Science and Technology Societies (2006) and the Citation for Excellence in Lecturing by Korea Maritime and Ocean University (2008). 🌟🎖️

Research Focus 🔬

Dr. Lee’s research encompasses control engineering, marine electric systems, genetic algorithms, fuzzy control, and PID control. His studies aim to enhance the safety, efficiency, and reliability of marine propulsion systems and other maritime technologies. Through numerous research projects and innovative solutions, he has significantly advanced the field of marine and fisheries technology. 🌊⚡

Conclusion 🌟

Dr. Yunhyung Lee’s exceptional career reflects his dedication to advancing marine and maritime technology through research, education, and industry collaboration. His passion for innovation and his unwavering commitment to excellence make him a leading figure in his field. 🌏✨

Publications 📚

Application of Real-Coded Genetic Algorithm–PID Cascade Speed Controller to Marine Gas Turbine Engine Based on Sensitivity Function Analysis
Mathematics, 2025 – Cited by: 5

Development of Hull Care for Warships Based on a Manned-Unmanned Hybrid System: Focusing on the Underwater Hull Plate
Journal of the KNST, 2024 – Cited by: 3

Modeling and Parameter Estimation of a 2DOF Ball Balancer System
Journal of the Korea Academia-Industrial Cooperation Society, 2024 – Cited by: 4

Ground-Fault Recognition in Low-Voltage Ships Based on Variation Analysis of Phase-to-Ground Voltage and Neutral-Point Voltage
IEEE Access, 2024 – Cited by: 8

Speed Control for Low Voltage Propulsion Electric Motor of Green Ship through DTC Application
Journal of the Korea Academia-Industrial Cooperation Society, 2023 – Cited by: 6

RCGA-PID Controller Based on ITAE for Gas Turbine Engine in the Marine Field
The Journal of Fisheries and Marine Sciences Education, 2023 – Cited by: 3

PID Controller Design Based on Direct Synthesis for Set Point Speed Control of Gas Turbine Engine in Warships
Journal of the Korean Society of Fisheries Technology, 2023 – Cited by: 2

Study on Speed Control of LM-2500 Engine Using IMC-LPID Controller
Journal of the Korea Academia-Industrial Cooperation Society, 2022 – Cited by: 7

A Study on the Training Contents of AC DRIVE of the HV Electrical Propulsion Ships
Journal of Fisheries and Marine Sciences Education, 2021 – Cited by: 4

Nasser Mozayani | software | Best Researcher Award

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Dr. Nasser Mozayani | software | Best Researcher Award

Associate Professor, Iran University of Science and technology, Iran

🎓 Dr. Nasser Mozayani is an Associate Professor at the School of Computer Engineering at Iran University of Science and Technology (IUST) in Tehran, Iran. With a distinguished career in computer engineering, he has contributed significantly to research, teaching, and administration in his field. Dr. Mozayani specializes in machine learning, multi-agent systems, and the metaverse, bringing innovative insights into these cutting-edge areas. He has held several prominent positions at IUST, including Dean of the Computer Engineering Department, and has been actively involved in national research and technological projects.

Publication Profile

ORCID

Education

📘 Dr. Mozayani completed his Ph.D. in Informatics at the University of Rennes I in France (1998), where he conducted groundbreaking research on spatio-temporal coding in neural networks. His educational journey also includes an M.Sc. in Telematics & Information Systems from SUPELEC, France (1994), and a B.Sc. in Electrical Engineering (Computer Hardware) from Sharif University of Technology in Tehran, Iran (1990).

Experience

👨‍🏫 Dr. Mozayani has been an Associate Professor at IUST since 1999, teaching undergraduate courses in electronic and electric circuits, and advanced graduate courses in fields like artificial neural networks, digital circuits synthesis, and distributed AI. He has also held visiting professor roles at Allameh Tabatabaee University and Tarbiat Modarres University, where he specialized in educational games and simulations for doctoral students. In administrative capacities, he has led multiple departments and centers at IUST, contributing to the growth of e-learning and technology innovation.

Research Focus

🔬 Dr. Mozayani’s research is centered on machine learning, multi-agent systems, and smart grid applications. He has led numerous projects on smart grid communication protocols, reinforcement learning, and the application of AI in predictive modeling and decision-making for health and energy sectors. His innovative work in hierarchical reinforcement learning has advanced the integration of machine learning in smart grid management and infrastructure.

Awards and Honors

🏆 Dr. Mozayani has supervised the IUST RoboCup team, which achieved notable successes, including a first-place win in the Rescue Virtual Robots competition at the Khwarizmi Young Award (2010) and a top-four ranking in the World RoboCup 2D football simulation (2013). He has also mentored award-winning student projects in digital library development, recognized by the Khwarizmi Young Award.

Publications – Top Notes

“Deployment of a Flexible Communication Protocol for Advanced Metering in Smart Grid” (IUST, 2023), cited by 5 articles Journal: Smart Grid Technologies.

“Algorithmic Trading on Financial Time Series Using Deep Reinforcement Learning” (IUST, 2022), cited by 10 articles Journal: Financial Technology & AI.

“Using Machine Learning Methods to Determine Factors Affecting COVID-19 Mortality Rates” (IUST, 2021), cited by 8 articles Journal: Health Informatics.

 

Zhizhen Chen | Computer Science | Best Researcher Award

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Dr. Zhizhen Chen | Computer Science | Best Researcher Award

Senior Lecturer, University of Greenwich, United Kingdom

🎓 Dr. Zhizhen Chen is a dedicated academic professional serving as a Senior Lecturer in Finance at the University of Greenwich since 2017. With a rich background in finance and economics, Dr. Chen brings extensive experience from both academia and industry. His research interests encompass financial markets, risk management, and financial engineering, contributing significantly to several top-tier finance journals. Dr. Chen is also an active peer reviewer and passionate educator, sharing his expertise through innovative courses like Fintech Banking and Financial Engineering and Machine Learning. 🌍📊

Publication Profile

Scopus

Strengths for the Award:

  1. Research Excellence: Dr. Chen has a strong publication record, with multiple articles published in high-impact journals such as “Journal of International Money and Finance” and “Research in International Business and Finance,” both rated 4* in SJR. This demonstrates his capability in producing high-quality research in the field of finance.
  2. Peer Review Activities: He has been a peer reviewer for several prestigious journals since 2016, which showcases his recognition in the academic community and his commitment to advancing knowledge in finance.
  3. Academic and Professional Credentials: Dr. Chen holds a PhD in Finance, is a Fellow of the Higher Education Academy, and has passed CFA Level 1. This combination of academic qualifications and professional certification adds to his credibility and expertise in the field.
  4. Diverse Teaching Portfolio: His teaching experience spans various finance and economics-related courses, demonstrating versatility and a solid understanding of different areas within the field.
  5. Industry Experience: Dr. Chen’s experience as an Investment Analyst and his work with financial institutions provide him with practical insights, enhancing his academic work’s relevance and applicability.
  6. Continuous Professional Development: His commitment to continuous learning and development is evident through his successful completion of the CFA Level 1 exam and his role in ongoing staff development activities.

Areas for Improvement:

  1. Broader Research Impact: While Dr. Chen has a strong record in finance-specific publications, expanding his research impact across other interdisciplinary areas, such as sustainable finance or fintech, could further enhance his profile.
  2. Leadership Roles in Research: Taking on more leadership roles in research projects or academic committees could strengthen his candidacy by demonstrating his influence beyond his individual contributions.
  3. Grants and Funding: Securing research grants or funding is a notable achievement in academia that is not highlighted in the current profile. Pursuing funding opportunities could bolster his research credentials further.

Education

🎓 Dr. Zhizhen Chen holds a PhD in Finance from the University of Glasgow (2018), demonstrating his strong foundation in financial research and education. He is also a Fellow of the Higher Education Academy (2017), a testament to his commitment to teaching excellence, and he earned an MSc in Economics from the University of Wuhan (2012). 📚✨

Experience

🌟 Dr. Chen’s career spans roles as a Senior Lecturer in Finance at the University of Greenwich since 2017, where he excels in teaching and research. His prior experience includes serving as a Research Assistant and Teaching Assistant at the University of Glasgow, and an Investment Analyst at ICBC Wuhan. This blend of academic and industry roles has equipped him with a unique perspective on finance education. 💼💹

Research Focus

🔍 Dr. Chen’s research is focused on financial markets, risk management, securitization, and financial engineering. He actively contributes as a peer reviewer for prestigious journals, including the Journal of International Financial Markets, Institutions & Money, and Finance Research Letters, ensuring rigorous academic standards in the field. 📑🔬

Awards and Honours

🏅 Dr. Chen was recognized as a Fellow of the Higher Education Academy in 2017, highlighting his dedication to teaching excellence. In addition, he passed the CFA Level 1 exam in 2020, demonstrating his commitment to continuous professional development in finance. 🎖️📈

Publication Top Notes

Lin, W., Yan, W., Chen, Z., Xiao, R. (2023). Research on product appearance patent spatial shape recognition for multi-image feature fusion. Multimedia Tools and Applications (SJR 3*).

Xiao, R., Li, G., Chen, Z. (2023). Research progress and prospect of evolutionary many-objective optimization. Control and Decision.

Chen, Z., Liu, H., Peng, J., Zhang, H., Zhou, M. (2022). Securitization and bank efficiency. In: Ferris, S.P., Kose, J., Makhija, A.K., (eds.) Empirical Research in Banking and Corporate Finance. Emerald Publishing Limited.

Conclusion:

Dr. Zhizhen Chen is a suitable candidate for the “Research for Best Researcher Award” due to his significant contributions to the field of finance through high-quality publications, peer-review activities, and professional development. While there is room for growth in interdisciplinary research and leadership roles, his current achievements and ongoing commitment to both academic and professional excellence make him a compelling contender for the award.

qianqian zhang | Computer application technology | Best Dissertation Award

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Dr. qianqian zhang | Computer application technology | Best Dissertation Award

Doctoral student, University of Chinese Academy of Sciences, China

Qianqian Zhang is a doctoral student at the University of Chinese Academy of Sciences, specializing in computer application technology within the School of Computer Science and Technology and the National Space Science Center. With notable achievements in electronic information technology for complex space systems, Qianqian has excelled in both academic and research arenas.

Profile

ORCID

🎓 Education:

  • Bachelor’s Degree: Hefei University of Technology, School of Computer Science and Information, Electronic Information Science and Technology, 2017-2021 (Graduated with the highest average score).
  • Master’s Degree: University of Chinese Academy of Sciences, School of Computer Science and Technology/National Space Science Center, Computer Application Technology, 2021-2024 (GPA: 3.7/4.0).
  • Ph.D. Candidate: Continuing at the University of Chinese Academy of Sciences, with significant contributions including 4 patents and several research publications.

🛠 Experience:

Qianqian Zhang has 3 years of experience in the field of computer application technology, with a focus on AI, deep learning, computer vision, and electronic design. She has been mentored by leading experts and has extensive practical experience with PyTorch, PaddlePaddle, TensorFlow, and multimodal data.

🔬 Research Interests:

Her research interests include multimodal data processing, small target detection, model lightweighting, video compression, and efficient deployment of models. She has made significant contributions to the fields of intelligent computing and system-on-chip design.

🏆 Awards:

Qianqian has received numerous national and regional awards, including top prizes in robotics control competitions. Her academic excellence is recognized through various awards and honors in advanced mathematics and electronic design.

📚 Publications:

“Real-time Recognition Algorithm of Small Target for UAV Infrared Detection” (SCI Journal, 2023) [Cited by 5 articles]

“Design of H.264 Video Compression System Based on Domestic CPU+GPU” (Conference Paper, 2023) [Cited by 2 articles]

“Multi-YOLO: Small Target Detection Algorithm Based on Visible and Infrared Multimodal Fusion” (Contributing Paper, 2024) [Cited by 3 articles]