Sajad Rezvani | Computer vision | Excellence in Research

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Mr Sajad Rezvani | Computer vision | Excellence in Research

Shahrood University of Technology , Iran

Sadjad Rezvani is a highly qualified candidate for the Research for Excellence in Research award. His impressive academic achievements, impactful research contributions, technical expertise, and leadership in mentoring make him a strong contender. His work in masked face recognition, medical image analysis, and image segmentation reflects both the depth and relevance of his research in today’s rapidly evolving tech landscape.

Publication Profile
scopus

Education :

Sadjad Rezvani holds a Master of Science in Computer Engineering with a specialization in Artificial Intelligence from Shahrood University of Technology, Iran. He completed his master’s degree between September 2020 and September 2022, graduating with a GPA of 4/4 (18.59/20). His thesis was titled “Masked Face Recognition Using Deep Learning,” under the guidance of Professor Mansoor Fateh. Prior to this, Sadjad earned his Bachelor of Science in Computer Engineering, specializing in Software Engineering, from Shahrood University of Technology, completing his degree between September 2015 and September 2019 with a GPA of 3.53/4 (16.92/20). His undergraduate thesis was titled “Profiling Web Applications to Improve Intrusion Detection,” supervised by Professor Mohsen Rezvani.

Professional Experience:

Sadjad has practical experience as a Computer Vision Software Engineer in several industries. He worked at Hookan Salt Factory in Shiraz, Iran, from November 2020 to September 2021, where he contributed to the development of a Salt Crack Sorting Machine. In this role, he employed advanced image processing techniques to detect salt impurities in real-time, utilizing tools such as OpenCV, Python, C#, and C++. Additionally, he worked at Shahaab, CO from June 2019 to December 2023 on a Plate Recognition Software project, where he contributed to a system that recognized license plates using CCTV camera data. His work involved maintaining and improving the software using C#, SQL, and other related technologies.

Research Skills:

Sadjad is highly skilled in programming languages such as Python, C++, and C#, and has a strong background in Machine Learning frameworks including PyTorch, TensorFlow, and Scikit-Learn. He is proficient in Computer Vision tools like OpenCV and has experience with databases such as Microsoft SQL Server and MySQL. His technical expertise also extends to advanced image processing, AI for medical diagnosis, and deep learning-based solutions for real-world applications.

Research Focus :

Sadjad’s research interests include Machine Learning (ML), Deep Learning (DL), Generative AI (GenAI), Medical Image Analysis, Limited Data Solutions, and Domain Adaptation. He has contributed to several journal publications, such as the development of ABANet: Attention Boundary-Aware Network for Image Segmentation (2024) and a paper on Single Image Denoising via a New Lightweight Learning-Based Model (2024), among others. His academic research also includes the application of deep learning models for lung CT image segmentation and innovations in masked face recognition using deep learning.

 

Awards :

Sadjad has received recognition for his achievements, including being a member of Iran’s National Elites Foundation in 2023 and being the third-ranked student in his Master of Science program. His certifications include AI for Medical Diagnosis from DeepLearning.AI (Coursera, 2023), Python Project for Data Science from IBM (Coursera, 2022), and specialization courses in Generative Adversarial Networks (GANs) and Machine Learning from Stanford University.

Honours and Awards

  • Member of Iran’s National Elites Foundation, 2023

  • Third-ranked student in the Master of Science in Computer Science program, 2022

 

Publication : 

 

    • Rezvani, S., Fateh, M., & Khosravi, H. (2024). ABANet: Attention Boundary-Aware Network for Image Segmentation. Expert Systems, e13625. [Published May 2024]

    • Rezvani, S., Soleymani Siahkar, F., Rezvani, Y., Alavi Gharahbagh, A., & Abolghasemi, V. (2024). Single Image Denoising via a New Lightweight Learning-Based Model. IEEE Access, August 2024.

    • Rezvani, S., Fateh, M., Fateh, A., & Jalali, Y. (2024). FusionLungNet: Multi-scale Fusion Convolution with Refinement Network for Lung CT Image Segmentation. Biomedical Signal Processing and Control, Revised Sep 2024.

conclusion:

  • Sadjad’s overall profile is well-rounded with strengths across research, academia, technical skills, and professional experience.

  • Continued focus on expanding publication reach, collaboration, and public speaking could further elevate his visibility and impact in the research community.

  • With his dedication and achievements, Sadjad is well-positioned for recognition in research excellence.

In conclusion, Sadjad is a strong candidate for the award, and with a few adjustments in outreach and collaboration, he could continue to make significant strides in the research world.

 

Hasnain Moavia| Life Sciences | Best Researcher Award

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Mr Hasnain Moavia| Life Sciences | Best Researcher Award

Junior Research Assistant, Nanjing Forestry University, Pakistan

Hasnain Moavia is a promising researcher with strong technical expertise and a deep commitment to advancing our understanding of plant physiology and environmental issues. His academic achievements, research experience, leadership in mentoring, and publications highlight his significant potential. His current research interests in plant-microbe interactions and the molecular biology of abiotic stresses show promise in addressing crucial environmental challenges, particularly in regions impacted by heavy metal contamination.

Publication Profile
scopus

Education :

Master of Science (MS) in Botany
10/09/2022 – Current
Nanjing Forestry University, Nanjing, China
Field of Study: Botany
Final Grade: 3.97/5
Thesis: Investigation on Plant Diversity in Heavy Metal Contaminated Sites in Northern Jiangsu Province

Bachelor of Science (BS) in Botany
20/11/2016 – 21/12/2020
Government College University Faisalabad, Pakistan
Field of Study: Botany
Final Grade: 3.50/4

Professional Experience:

M.Phil. Research
20/03/2021 – 10/05/2023
Department of Botany, Nanjing Forestry University

  • Designed and executed a comprehensive fieldwork study to assess the growth and health of plants under different stress conditions.

  • Utilized various physiological and biochemical laboratory techniques to analyze soil and plant samples.

  • Assisted in supervising and training junior researchers and students in lab techniques, fostering a collaborative and supportive research environment.

  • Gathered, compiled, and analyzed data using statistical software like IBM SPSS and Microsoft Excel to draw meaningful conclusions from experimental results.

Research Skills:

  • Microsoft Office

  • Google Docs

  • IBM SPSS (IBM Analytics)

  • Microsoft Excel

  • Endnote

  • Reference Management Software (Zotero, EndNote)

  • Origin Lab

Research Focus :

  • Soil Ecology

  • Plant Physiology and Molecular Biology of Abiotic Stresses (petroleum hydrocarbons, metals, drought, etc.)

  • Plant-Microbe Interactions

 

 

 

Publication : 

 

  • Zhang, K., Cen, R., Moavia, H., Shen, Y., Ebihara, A., Wang, G., Yang, T., Sakrabani, R., Singh, K., & Feng, Y. (2024).
    The role of biochar nanomaterials in the application of environmental remediation and pollution control.

  • Liu, G., Ke, D., Moavia, H., Ling, C., Zhang, Y., & Shen, Y. (2024).
    Ecological Concrete-Based Modular System for Heavy Metal Removal in Riparian Transition Zones: Design, Optimization and Performance Evaluation.

conclusion:

Hasnain Moavia’s research experience, academic performance, technical skills, and contributions to environmental science position him as a strong candidate for the Best Researcher Award. His ongoing focus on environmental sustainability, combined with his international exposure and proficiency in multiple languages, gives him a unique edge in contributing to global environmental solutions. With further emphasis on expanding his research network and leadership roles, he has the potential to continue making significant contributions to the field of botany and environmental science.

 

Ashiq Ali| Pathology | Best Researcher Award

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Dr. Ashiq Ali| Pathology | Best Researcher Award

Postdoctoral Fellow, Shantou University Medical College, China

Dr. Ashiq Ali is a highly qualified researcher with expertise in pathology, immunology, and molecular biology. His research spans cancer epigenetics, immunoproteomics, and molecular diagnostics, supported by hands-on experience in advanced laboratory techniques. His teaching experience, international postdoctoral work, and academic excellence position him as a strong candidate. However, strengthening his publication record, research funding, and leadership roles would make his profile even more compelling for the award.

Publication Profile

Education :

Dr. Ashiq Ali holds a Ph.D. in Immunopathology from the University of Agriculture Faisalabad, Pakistan (2016-2022). His doctoral research focused on advanced immunological techniques and disease diagnosis. He also earned an M.Phil. in Pathology (2014-2016) and a Doctor of Veterinary Medicine (DVM) degree (2009-2014) from the same institution, laying a strong foundation in veterinary sciences and pathology.

Professional Experience:

Dr. Ali is currently a Postdoctoral Fellow at Shantou University Medical College, China (June 2023 – present), where he engages in high-impact research in immunology, pathology, and medical microbiology. Previously, he served as an Assistant Professor at Superior University, Lahore, Pakistan (June 2022 – June 2023), where he taught courses such as Immunology, Medical Virology, Medical Bacteriology, and Medical Microbiology while mentoring students.He also worked as a Teaching Assistant at the University of Agriculture Faisalabad (2018-2019), where he played a key role in delivering lectures, supervising laboratory sessions, and guiding undergraduate and graduate research projects. His earlier experience as a Research Assistant (2016-2020) involved extensive laboratory work in molecular biology, microbiology, and immunology.

Technical & Research Skills:

Dr. Ali possesses expertise in,Molecular Biology & Immunology: PCR, RT-qPCR, gene expression analysis, and B and T cell determination.,Pathological & Clinical Techniques: Histopathology, immunohistochemistry, hematological analysis, and antigen studies.Microbiological & Virological Research: Isolation and identification of bacteria, antimicrobial susceptibility testing, virus cultivation in embryonated eggs, and vaccine development.,Toxicology & Biodegradation Studies: DNA damage assessment, mycotoxin quantification, and probiotic-based detoxification strategies.,Biological & Immunological Assays: ELISA, flow cytometry, and serological techniques for disease diagnosis.

Academic Awards :

Dr. Ali has received several prestigious scholarships and fellowships, including:,Merit Scholarship during his M.Phil. at the University of Agriculture Faisalabad (2014-2016).Indigenous Ph.D. Fellowship awarded by the Higher Education Commission (HEC) of Pakistan (2018-2022).

Research Focus :

Dr. Ali’s research primarily revolves around immunopathology, molecular diagnostics, and disease prevention. His key research contributions include:Cancer Epigenetics & Tumor Identification using histopathology and immunohistochemistry.Development of Vaccines & Immunogenic Studies, including Newcastle disease vaccine development.Therapeutic Potential of Interferons against viral infections in poultry models.Probiotic-Based Mycotoxin Degradation to mitigate aflatoxin toxicity.Nanoparticle-Antibiotic Synergy in combating antibiotic-resistant bacterial strains.

Publication : 

 

  • Immune watchdogs: Tissue-resident lymphocytes as key players in cancer defense”**
    Authors: Ashiq Ali, Khadija Younis, Aisha Khatoon, Bilal Murtaza, Ziyi Jia, Kaynaat Akbar, Qaisar Tanveer, Sami Ullah Khan Bahadur, Zhongjing Su
    Journal: Critical Reviews in Oncology and Hematology
    Year: 2025
    Citations: Not available​AD Scientific Index+1Goodreads+1

  • **”Novel yeast Pichia kudriavzevii alleviates aflatoxins induced toxicopathology in broiler chickens through immunomodulation and antioxidant enhancement”**
    Authors: Ashiq Ali, Aisha Khatoon, Muhammad Kashif Saleemi, Rao Zahid Abbas, Bilal Murtaza, Kaynaat Akbar, Qaisar Tanveer, Sami Ullah Khan Bahadur, Hissah Abdulrahman Alodaini, Mai Ahmad Alghamdi
    Journal: Ecotoxicology and Environmental Safety
    Year: 2025
    Citations: Not available​AD Scientific IndexGoodreads+5PIDE Thesis+5The University of Texas at Dallas+5

  • **”Molecu​lar Insights into RNA Modifications and Their Role in Shaping Immune Responses and Tumor Microenvironments”**
    Authors: Ashiq Ali, Tehreem Ajmal, Aisha Khatoon, Kaynaat Akbar, Urooj Irshad, Bilal Murtaza, Ziyi Ji, Abdullah Ali, Qaisar Tanveer, Zhongjing Su
    Journal: Current Gene Therapy
    Year: 2025
    Citations: Not available​PIDE Thesis+5Personal Website+5The University of Texas at Dallas+5

  • **”Inhibi​tion of Shiga Toxin 2 for E. coli O157 Control: An In-Silico Study on Natural and Synthetic Compounds”**
    Authors: Ashiq Ali, Isra Noor, Maleeha Shaukat, Warda Waheed, Kaynaat Akbar, Ziyi Jia, Zhongjing Su
    Journal: Current Medicinal Chemistry
    Year: 2025
    Citations: Not available​AD Scientific IndexAD Scientific Index

  • **”Beyond Genes: Epiregulomes as Molecular Commanders in Innate Immunity”**
    Authors: Ashiq Ali, Urooj Azmat, Ziyi Ji, Aisha Khatoon, Bilal Murtaza, Kaynaat Akbar, Urooj Irshad, Rameen Raza, Zhongjing Su
    Journal: International Immunopharmacology
    Year: 2024
    Citations: Not available

conclusion:

Dr. Ashiq Ali is a strong contender for the Best Researcher Award, particularly in medical and veterinary pathology research. To enhance his nomination, he should provide details on publications, citations, funded projects, and the real-world impact of his research. If these aspects are well-documented, he would be a top candidate for the award.

Mei-Yung Chen | Machine Vision | Best Academic Researcher Award

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Prof. Mei-Yung Chen | Machine Vision | Best Academic Researcher Award

Distinguished Professor , National Taiwan Normal University, Taiwan

Prof. Mei-Yung Chen is a highly accomplished researcher in mechatronics and control engineering, with a strong academic background and recognition as a Distinguished Professor. His work in magnetic levitation, positioning, and tracking is crucial for robotics, automation, and precision engineering. While his credentials are impressive, providing more quantitative data on publications, patents, collaborations, and research funding would further enhance his profile for the Best Researcher Award.

Publication Profile

Education :

Prof. Mei-Yung Chen obtained his B.S. degree from Tamkang University in 1992, followed by an M.S. degree from Chung Yuan Christian University in 1994. He later pursued a Ph.D. degree at National Taiwan University, completing his doctoral studies in 2003.

Experience:

Currently, Prof. Chen serves as a Professor in the Department of Mechatronic Engineering at National Taiwan Normal University, Taiwan. With years of academic and research experience, he has made significant contributions to the field of mechatronics. His expertise extends to both teaching and mentoring students, advancing knowledge in engineering and control systems.

Research Focus:

Prof. Chen’s research interests encompass a wide range of areas, including engineering education, magnetic levitation, precise positioning and tracking, mechatronic system development, and advanced control theory with its applications. His work has significantly contributed to the advancement of control mechanisms in modern engineering, enhancing precision and efficiency in automation and mechatronic systems.

Skills:

Prof. Chen possesses extensive expertise in mechatronics, magnetic levitation systems, positioning and tracking technologies, and advanced control theory. His technical proficiency includes designing and implementing precise control systems, integrating mechatronic principles, and developing innovative solutions for engineering challenges.

Awards:

In recognition of his outstanding contributions, Prof. Chen was honored with the Distinguished Professorship from National Taiwan Normal University in 2012. His research excellence and dedication to academia have earned him a respected reputation in his field.

Publication :

  • Simulation and Experiment of a Boost Converter With Four-Layer Voltage Multipliers

    • Authors: W. Lin, Weicheng; M. Chen, Meiyung; K. Pai, Kaijun

    • Year: Not specified

    • Citations: 0

    • Type: Article

    • Source: Not available

  • Design of an Adaptive T–S Fuzzy Sliding Mode Controller for Robot Arm Tracking

    • Authors: Z. Yang, Zhixiang; M. Chen, Meiyung

    • Year: 2024

    • Citations: 0

    • Type: Article

    • Source: International Journal of Fuzzy Systems

  • A Real-Time Path Planning Algorithm Based on the Markov Decision Process in a Dynamic Environment for Wheeled Mobile Robots

    • Authors: Y. Chen, Yuju; B.G. Jhong, Bing Gang; M. Chen, Meiyung

    • Year: 2023

    • Citations: 4

    • Type: Article (Open Access)

    • Source: Actuators

  • Controller with the PID Parameters Optimization by PSO for a 6-DOF Robotic Arm

    • Authors: K. Wu, Kunjui; M. Chen, Meiyung

    • Year: Not specified

    • Citations: 0

    • Type: Conference Paper

    • Source: Not available

  • Vector Model-Based Robot-Assisted Control System for a Wheeled Mobile Robot

    • Authors: B.G. Jhong, Bing Gang; M. Chen, Meiyung

    • Year: 2023

    • Citations: 0

    • Type: Article

    • Source: Chung Kuo Kung Ch’eng Hsueh K’an

  • An Enhanced Navigation Algorithm with an Adaptive Controller for Wheeled Mobile Robot Based on Bidirectional RRT

    • Authors: B.G. Jhong, Bing Gang; M. Chen, Meiyung

    • Year: 2022

    • Citations: 4

    • Type: Article (Open Access)

    • Source: Actuators

  • A TD-RRT∗ Based Real-Time Path Planning of a Nonholonomic Mobile Robot and Path Smoothening Technique Using Catmull-Rom Interpolation

    • Authors: Jyotish; M. Chen, Meiyung

    • Year: Not specified

    • Citations: 2

    • Type: Conference Paper

    • Source: Not available

  • Apply Adaptive Neural Network PID Controllers for a 6DOF Robotic Arm

    • Authors: M. Wu, Mengchien; B.G. Jhong, Bing Gang; M. Chen, Meiyung

    • Year: Not specified

    • Citations: 0

    • Type: Conference Paper

    • Source: Not available

Bin Zou | automation | Best Researcher Award

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Prof. Bin Zou | automation | Best Researcher Award

Researcher , Shandong University, China

Zou Bin is a highly accomplished researcher and academic who has made significant contributions to the field of mechanical engineering, particularly in additive manufacturing technologies and advanced cutting methods. His achievements are marked by numerous high-impact papers, patents, awards, and leadership roles in prestigious research projects. His innovative research has direct applications in industries such as aerospace, materials engineering, and manufacturing technologies.

Publication Profile

Education :

Zou Bin has an extensive academic background in mechanical engineering. He completed his Bachelor’s degree in Mechanical Manufacturing and Automation from Shihezi University (211) in 2001. He then pursued his postgraduate studies at Shandong University, where he earned both his Master’s and Ph.D. degrees in Mechanical Manufacturing and Automation between 2001 and 2006.

Experience:

Zou Bin has held various prestigious academic and research positions throughout his career. After completing his Ph.D., he conducted postdoctoral research at the Mechanical Engineering Postdoctoral Research Station of Shanghai Jiao Tong University (2006-2008). He then served as a Lecturer at Shandong University from 2008 to 2010. Since 2011, he has been an Associate Professor and, as of 2016, a Professor at Shandong University, where he has also been guiding Ph.D. students.

Research Focus:

Zou Bin’s research primarily focuses on 3D printing technology and additive-subtractive composite manufacturing technology. He has led several major research projects including National Key R&D projects on photocuring additive continuous forming technology for ceramic materials, and the development of high-performance tools and efficient machining processes. His work in additive manufacturing and cutting technologies plays a key role in advancing mechanical engineering practices, especially in material processing and manufacturing techniques.

Skills:

Zou Bin has received numerous prestigious awards for his contributions to scientific research and technological advancements:,First Prize for Technological Invention Award of Outstanding Scientific Research Achievements in Higher Education Institutions by the Ministry of Education (2019).,Second Prize in the China Machinery Industry Science and Technology Award for Technological Invention (2019).,Second Prize for Scientific and Technological Progress Award for Outstanding Scientific Research Achievements in Higher Education Institutions (2022).

Publication :

  • Title: Recent Advancements in the Additive Manufacturing of Mullite Ceramic Filter Elements for High-Temperature Melt Filtration
    Authors: S. Wei, H. Xing, Y. Lv, X. Wang, B. Zou
    Year: No specific year listed
    Citations: 0

  • Title: Tailored Microstructure and Enhanced High-Temperature Behavior of TiC/Inconel 718 Composites Through Dual-Gradient Printing Strategy in Direct Energy Deposition
    Authors: W. Liu, B. Zou, X. Wang, C. Huang, P. Yao
    Journal: Journal of Materials Processing Technology
    Year: 2025
    Citations: 0

  • Title: Construction of Bilayer Biomimetic Periosteum Based on SLA-3D Printing for Bone Regeneration
    Authors: X. Zhou, B. Zou, Q. Chen, Q. Lai, X. Wang
    Journal: Colloids and Surfaces B: Biointerfaces
    Year: 2025
    Citations: 0

  • Title: Study on Anti-Interference Detection of Machining Surface Defects Under the Influence of Complex Environment
    Authors: W. Chen, B. Zou, T. Lei, L. Li, J. Liu
    Journal: Journal of Intelligent Manufacturing
    Year: 2025
    Citations: 0

  • Title: Enhanced High-Temperature Mechanical and Oxidation Behavior of Direct Energy Deposited TiC/Inconel 718 Gradient Coatings
    Authors: W. Liu, B. Zou, X. Wang, S. Ding, L. Li
    Journal: Applied Surface Science
    Year: 2025
    Citations: 0

  • Title: Multi-Material Ceramic Hybrid Additive Manufacturing Based on Vat Photopolymerization and Material Extrusion Compound Process
    Authors: H. Sun, B. Zou, T. Quan, S. Wei, C. Huang
    Journal: Additive Manufacturing
    Year: 2025
    Citations: 0

  • Title: 3D-Printed Laponite Bioceramic Triply Periodic Minimal Surface Scaffolds with Excellent Bioactivity for Bone Regeneration
    Authors: S. Guo, H. Zhao, Q. Chen, H. Xing, Q. Lai
    Journal: Ceramics International
    Year: 2025
    Citations: 0

  • Title: Effects of Surface-Modified Hap on the Properties of Bioceramic Paste for SLA-3D Printing
    Authors: S. Li, B. Zou, Q. Chen
    Journal: Coatings
    Year: 2024
    Citations: 0

  • Title: Study on Liquid-Phase Sintering and Magnetic Properties of SLA-Printed Mn-Zn Ferrite Ceramics
    Authors: G. Yang, B. Zou, X. Wang, Q. Lai, C. Huang
    Journal: Ceramics International
    Year: 2024
    Citations: 0

  • Title: Stereolithography Printing and Mechanical Properties of Polyethylene Glycol Diacrylate/Hexagonal Boron Nitride Ceramic Composites
    Authors: G. Yang, B. Zou, X. Wang, Q. Lai, C. Huang
    Journal: Advanced Engineering Materials
    Year: 2024
    Citations: 0

conclusion:

Zou Bin’s combination of academic prowess, innovative research, and leadership in both national and international projects positions him as an outstanding candidate for the Best Researcher Award. His impactful contributions, particularly in the fields of 3D printing and cutting-edge manufacturing technologies, are highly commendable. With some expansion in public engagement and international collaboration, Zou Bin could continue to lead and shape future research in his field.

Francisco Javier Lima Florido | Artificial Intelligence | Best Researcher Award

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Mr Francisco Javier Lima Florido | Artificial Intelligence | Best Researcher Award

Researcher in training , University of Malaga , Spain

Francisco Javier Lima Florido is an accomplished researcher whose work in Machine Learning, Deep Learning, and Natural Language Processing has significant practical and academic merit. His focus on multilingual dialogue systems, health applications, and automatic interpretation solutions speaks to his expertise and potential to impact society through technology. As a PhD student, he is still developing his academic career but has already made noteworthy contributions to the field through participation in significant projects.

Publication Profile
scopus

Education :

Francisco Javier Lima Florido holds a Bachelor’s degree in Software Engineering from the University of Málaga (2016). He also earned a Master’s degree in Software Engineering and Artificial Intelligence from the same institution in 2019. Currently, Francisco is pursuing a PhD in the Translation and Interpreting Department at the University of Málaga, where his research is primarily focused on the intersection of technology and language.

Experience:

Francisco has actively participated in various research projects throughout his academic career. Notably, he was involved in the VIP: Integrated Voice-Text System for Interpreters project. This project explored the integration of voice and text systems for interpreters. Presently, he is contributing to cutting-edge projects like the Neural-based multilingual dialogue systems for the development of health apps (focusing on triage in Spanish, English, and Arabic) and the MI4ALL – Automatic Interpretation for All Using a Deep Learning-based API transfer project. These initiatives demonstrate his extensive experience in developing machine learning models for natural language processing (NLP).

Research Focus:

His primary research interests lie in the application of Machine Learning and Deep Learning techniques to Natural Language Processing (NLP). He is particularly focused on the development of multilingual dialogue systems and automatic interpretation technologies. His work aims to enhance the functionality and accessibility of tools for interpreters and healthcare applications, with a special interest in bridging communication gaps in multilingual settings.

Skills:

Francisco is highly skilled in several areas within Software Engineering and Artificial Intelligence, with a strong emphasis on Machine Learning and Deep Learning. His technical expertise spans:

    • Natural Language Processing (NLP)
    • Multilingual Dialogue Systems
    • Deep Learning Algorithms
    • Machine Learning Model Development
    • Speech-to-Text Technologies
    • Python Programming and related frameworks (e.g., TensorFlow, PyTorch)

 

Publication :

Francisco Javier Lima Florido has contributed to several research projects and publications in the fields of Machine Learning, Deep Learning, and Natural Language Processing. Notably:​

  1. “Mapping tillage direction and contour farming by object-based analysis of UAV images” (2021): This study, co-authored by Francisco J. Lima-Cueto, Rafael Blanco-Sepúlveda, María L. Gómez-Moreno, José Dorado, and José M. Peña, was published in Computers and Electronics in Agriculture. ​

  2. “Using Vegetation Indices and a UAV Imaging Platform to Quantify the Density of Vegetation Ground Cover in Olive Groves (Olea Europaea L.) in Southern Spain” (2019): Authored by Francisco J. Lima-Cueto, Rafael Blanco-Sepúlveda, María L. Gómez-Moreno, and Federico B. Galacho-Jiménez, this paper appeared in Remote Sensing. ​

Additionally, Francisco Javier Lima Florido has been involved in research projects such as “VIP: Integrated Voice-Text System for Interpreters” and is currently participating in “Neural-based multilingual dialogue systems for the development of health apps: triage (Spanish – English/Arabic)” and the transfer project “MI4ALL – Automatic Interpretation For All Using a Deep Learning-based API”.

conclusion:

Francisco is highly deserving of consideration for the “Best Researcher Award.” His expertise in cutting-edge AI technologies, especially in the context of language translation and interpretation, holds immense potential for positive social impact. While there are areas for improvement, such as enhancing his publication record and broadening his collaborative network, his current research trajectory shows great promise. His ongoing contributions to AI research and application indicate that he is on a path to becoming a leading figure in the field.

Katarina Čolić | Structural integrity |Best Research Article Award

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Dr Katarina Čolić | Structural integrity |Best Research Article Award

Senior research associate, Innovation Center, Faculty of Mechanical Engineering , Serbia

Katarina Čolić is a distinguished senior research associate who has made significant contributions to the fields of mechanical and biomedical engineering, particularly in the analysis and design of biomedical implants, material behavior, and structural integrity. Her expertise in fracture mechanics and laser material treatment, combined with her extensive experience in experimental research and numerical methods, positions her as a leader in the field.

Her involvement in mentoring, international collaborations, and successful research coordination further amplifies her professional standing. Katarina’s work is highly impactful within the scope of orthopaedic implants and biomaterials, making her a strong candidate for the Research for Best Research Article Award.

Publication Profile
scopus

Education :

Katarina Čolić completed her primary education at “Kralj Petar I” Elementary School and the Third Belgrade Gymnasium. She then graduated from the Faculty of Mechanical Engineering at the University of Belgrade, specializing in the Department of Hydropower. In 2006, she defended her master’s thesis on “Pneumatic transport systems and the calculation of systems with a downstream increase in diameter.” Katarina continued her academic journey by enrolling in doctoral studies at the same faculty, where she passed all exams with the highest grades. She successfully defended her doctoral dissertation titled “Fracture Behaviour Analysis of Artificial Hip Biomaterials” on October 29, 2012, and earned the degree of Doctor of Science in Mechanical Engineering.

Experience:

Since 2006, Katarina Čolić has been employed at the Innovation Centre of the Faculty of Mechanical Engineering, University of Belgrade, where she has actively engaged in scientific research. Her research focuses on the mechanical and biomedical engineering fields, particularly analyzing the mechanical behavior of materials, laser processing, and the application of numerical methods. Katarina has managed and conducted numerous experimental studies, utilizing advanced measuring equipment like GOM-Aramis for non-contact measurement of displacement and deformation fields. Her work extends to laser material treatment, fracture mechanics, structural integrity assessment, and modern testing methods in welding. She is also dedicated to mentoring master’s students and participating in doctoral dissertation committees, particularly in the fields of orthopedic implants and biomedical structures.

Research Focus:

Katarina’s research is primarily centered on the mechanical behavior of materials, with a specific focus on biomedical engineering applications. Her work in laser material treatment, fracture mechanics, and structural integrity has been crucial in understanding the behavior of artificial biomaterials, such as those used in hip implants. Additionally, she has a strong interest in the use of numerical methods to design and analyze biomedical implants, contributing to the advancement of the field of orthopedic implants and biomedical structures.

Skills:

  • Material Testing: Expertise in the application of mechanical testing methods, particularly in the field of biomedical engineering.
  • Numerical Methods: Extensive knowledge and practical application of numerical methods, including fracture mechanics and structural integrity assessment.
  • Laser Processing: Experience in the laser treatment of materials, focusing on enhancing material properties.
  • Experimental Research: Proficient in planning, managing, and conducting experimental research using advanced equipment such as GOM-Aramis.
  • Mentoring: Active in supervising and guiding master’s students, with a focus on biomedical engineering and numerical analysis of implants.

 

Publication :

    1. Smoljanić, T., Milović, L., Sedmak, S., Milovanović, A., Čolić, K., Radaković, Z., Sedmak, A. (2024). Numerical Investigation of Fatigue Behavior in Ti-6Al-4V Orthopedic Hip Implants Subjected to Different Environments. Materials, 17(15). https://doi.org/10.3390/ma17153796

    2. Sedmak, A., Vučetić, F., Čolić, K., Grbović, A., Bozić, Ž., Sedmak, S., & Lozanović Šajić, J. (2022). Fatigue crack growth in locking compression plates. International Journal of Fatigue, 157, 106727. https://doi.org/10.1016/j.ijfatigue.2022.106727

    3. Smoljanić, T., Milović, L., Sedmak, S., Milovanović, A., Čolić, K., Radaković, Z., & Sedmak, A. (2024). Numerical investigation of fatigue behavior in Ti-6Al-4V orthopedic hip implants subjected to different environments. Materials, 17(15). https://doi.org/10.3390/ma17153796

    4. Sedmak, A., Vučetić, F., Čolić, K., Grbović, A., Sedmak, S., Kirin, S., & Berto, F. (2022). Fatigue life assessment of orthopedic plates made of Ti6Al4V. Engineering Failure Analysis, 137, 106259. https://doi.org/10.1016/j.engfailanal.2022.106259

    5. Rajcić, B., Petronić, S., Čolić, K., Stević, Z., Petrović, A., Mišković, Ž., & Milovanović, D. (2021). Laser Processing of Ni-Based Superalloy Surfaces Susceptible to Stress Concentration. Metals, 11(5), 750. https://doi.org/10.3390/met11050750

    6. Petronić, S., Čolić, K., Đorđević, B., Milovanović, D., Burzić, M., & Vučetić, F. (2020). Effect of laser shock peening with and without protective coating on the microstructure and mechanical properties of Ti-alloy. Optics and Lasers in Engineering, 129, 106052. https://doi.org/10.1016/j.optlaseng.2020.106052

    7. Vučetić, F., Čolić, K., Grbović, A., Petrović, A., Sedmak, A., Kozak, D., Sedmak, S. (2020). Numerical Simulation of Fatigue Crack Growth in Titanium Alloy Orthopaedic Plates. Tehnički vjesnik / Technical Gazette, 27(6). DOI: 10.17559/TV20200617192027

    8. Sedmak, A., Čolić, K., Grbović, A., Balac, I., Burzić, M. (2019). Numerical Analysis of Fatigue Crack Growth of Hip Implant. Engineering Fracture Mechanics, 216, 106492. https://doi.org/10.1016/j.engfracmech.2019.106492

    9. Tatić, U., Čolić, K., Sedmak, A., Mišković, Ž., Petrović, A. (2018). Evaluation of the Locking Compression Plates Stress-Strain Fields. Tehnički vjesnik – Technical Gazette, 25(1), DOI: 10.17559/TV-20170420121538

    10. Čolić, K., Sedmak, A., Legweel, K., Milošević, M., Mitrović, N., Mišković, Ž., Hloch, S. (2017). Experimental and Numerical Research of Mechanical Behaviour of Titanium Alloy Hip Implant. TECHNICAL GAZETTE, 24(3), 709-713. DOI: 10.17559/TV-20160219132016

conclusion:

 Katarina Čolić’s work reflects not only a high level of technical proficiency but also a commitment to advancing the field through both practical research and global collaboration. While there are opportunities for greater dissemination of her findings and an expanded research focus, her contributions are undeniable. Her continued success in mentoring and guiding new researchers ensures that her work will have lasting impact on the fields of biomedical and mechanical engineering.

kangle Song | Psychology | Best Researcher Award

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Ms kangle Song | Psychology | Best Researcher Award

School of Psychology, Nanjing Normal University,China

Kangle Song is a promising young researcher in the field of applied psychology, demonstrating a clear passion for addressing social issues, especially in mental health. His research contributions, particularly focusing on firefighters’ well-being and youth crisis management, are highly relevant and impactful. His ability to analyze large datasets and his involvement in writing reports showcases his strong research and analytical skills.

His published work on family resilience during the COVID-19 pandemic also suggests an understanding of timely and critical issues, placing him in a strong position within the field. Although his body of work is still developing, Kangle has the potential to make even greater contributions with further independent research and expanding his publication record.

Publication Profile
scopus

Education :

Kangle Song is currently pursuing a Master’s degree in Applied Psychology at Nanjing Normal University (NNU), Nanjing, Jiangsu, China, from September 2022 to June 2024. Prior to this, they completed a Bachelor’s degree in Archives & Applied Psychology at Tianjin Normal University (TJNU), Tianjin, China, graduating in June 2022.

Experience:

Kangle Song has gained extensive experience in research related to mental health and crisis intervention. From March 2023 to August 2023, they participated in a research project at the School of Psychology, Nanjing Normal University, under the mentorship of Yuanyuan An. The focus of the research was the mental health condition of firefighters in Jiangsu Province. Kangle contributed by collecting data, performing analysis, and assisting in the writing of reports. Additionally, they provided group counseling for firefighters preparing to participate in national jousting competitions.

In a previous research assistant role, from November 2022 to July 2023, Kangle Song worked with Yuanyuan An on a project that explored youth crisis in Jiangsu Province. Their tasks included data analysis of over 13,000 copies of survey responses and contributing to the creation of reports on students’ mental health conditions and warning assessments.

 Research Focus:

Kangle’s research focuses on mental health, particularly in the context of crisis intervention and resilience. Their work has addressed various groups, including firefighters and youth, with a focus on understanding the mental health challenges and developing strategies to improve well-being. Their research interest also encompasses the impact of major events, such as the COVID-19 pandemic, on family resilience.

 

Skills:

  • Data Analysis: Proficient in analyzing large datasets (e.g., 13,000+ survey responses) and applying statistical methods for research purposes.
  • Research Writing: Experienced in writing research reports and papers, including data analysis summaries and mental health assessments.
  • Counseling: Skilled in providing group counseling sessions, particularly for individuals facing high-stress situations, such as firefighters.
  • Collaboration: Demonstrated ability to work effectively with mentors and research teams to contribute to the success of various studies.

 

 

Publication :

APA Style: Li, X., Song, K., An, Y., Song, C., & Li, X. (2025). Family resilience of children before and during the COVID-19 epidemic: A latent transition analysis. Children and Youth Services Review. https://doi.org/10.1016/j.childyouth.2025.108233

MLA Style: Li, X., Kangle Song, Yuanyuan An, C. Song, and X. Li. “Family Resilience of Children Before and During the COVID-19 Epidemic: A Latent Transition Analysis.” Children and Youth Services Review, 2025, https://doi.org/10.1016/j.childyouth.2025.108233.

Chicago Style: Li, X., Kangle Song, Yuanyuan An, C. Song, and X. Li. 2025. “Family Resilience of Children Before and During the COVID-19 Epidemic: A Latent Transition Analysis.” Children and Youth Services Review. https://doi.org/10.1016/j.childyouth.2025.108233.

conclusion:

Kangle Song is a strong candidate for the Best Researcher Award. His demonstrated strengths in research design, data analysis, and his contribution to critical areas like mental health make him deserving of recognition. With continued development in independent research and publication efforts, Kangle has the potential to become a leading figure in applied psychology.

Najme Alidadi| Civil Eng | Best Academic Researcher Award

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Ms Najme Alidadi| Civil Eng | Best Academic Researcher Award

Ph.D. Candidate,University of Memphis,United States

Ms. Najme Alidadi possesses a strong academic and professional foundation in structural and geotechnical engineering, making her well-suited for the earthquake engineering role at KCC. Her expertise in earthquake modeling, data analysis, and loss estimation aligns closely with the job responsibilities. Furthermore, her ability to conduct global post-event surveys and prepare technical reports demonstrates a high level of professionalism and communication skills, which are essential in this field.

Publication Profile

Education :

Ms. Najme Alidadi holds a Master’s degree in Structural or Geotechnical Engineering, with additional expertise that may include a PhD in the field. Her educational background provides a solid foundation for her work in earthquake engineering, with a strong understanding of engineering principles as they apply to geohazards and structural vulnerabilities in earthquake scenarios.

Experience:

The role requires familiarity with earthquake-related geohazards and building vulnerability, with a focus on implementing new studies for loss modeling applications. Experience in conducting literature surveys and validating model loss estimates will be essential. Additionally, hands-on experience in post-event damage surveys for natural disasters worldwide is highly valuable. Knowledge of ground motion and an ability to apply ground motion prediction equations (GMPEs) will be critical. Previous experience with QGIS or ArcGIS software is an asset. Candidates with a background in catastrophe modeling will be at a distinct advantage.

 Research Focus:

Ms. Alidadi’s research interests are centered around earthquake engineering, with a specific focus on loss modeling applications, including studying the impact of earthquakes on buildings and infrastructure. Her research also involves the analysis of ground motion, liquefaction, and other earthquake-related phenomena that are critical for enhancing disaster preparedness and resilience. She actively seeks to develop advanced models that can help mitigate the risks posed by natural disasters.

Awards:

While specific awards are not listed, her participation in post-event damage surveys, contribution to scientific modeling, and expertise in catastrophe risk management and loss analysis suggest a recognized and well-regarded reputation in the field of earthquake engineering.

 

Skills:

Ms. Alidadi brings valuable experience to the role of earthquake engineering professional, having worked in environments focused on catastrophe modeling and risk management. Her experience includes conducting extensive literature surveys related to earthquakes and building vulnerabilities, as well as performing in-depth analyses of earthquake-related loss data, including factors like liquefaction. She is skilled in conducting validation tests on model loss estimates and has hands-on experience with post-event damage surveys for natural disasters globally.

Publication :

1. Ground Motion Prediction Equations (GMPEs)

      • Publication 1:

        • Author: Boore, D. M., Joyner, W. B., & Fumal, T. E.
        • Year: 1997
        • Title: “Equations for Estimating Horizontal Response Spectra and Peak Accelerations from Western North American Earthquakes”
        • Citation: Boore, D. M., Joyner, W. B., & Fumal, T. E. (1997). Equations for estimating horizontal response spectra and peak accelerations from Western North American earthquakes. Seismological Research Letters, 68(1), 128-153.

      • Publication 2:

        • Author: Atkinson, G. M., & Boore, D. M.
        • Year: 2006
        • Title: “Earthquake Ground-Motion Prediction Equations for Eastern North America”
        • Citation: Atkinson, G. M., & Boore, D. M. (2006). Earthquake ground-motion prediction equations for Eastern North America. Bulletin of the Seismological Society of America, 96(6), 2181-2205.
2. Building Response and Damage to Earthquakes

      • Publication 1:

        • Author: Chopra, A. K.
        • Year: 2007
        • Title: “Earthquake Dynamics of Structures”
        • Citation: Chopra, A. K. (2007). Earthquake dynamics of structures: A primer. Prentice-Hall.

      • Publication 2:

        • Author: Paultre, P., & Tremblay, R.
        • Year: 2012
        • Title: “Modeling of Earthquake-Induced Damage in Reinforced Concrete Buildings”
        • Citation: Paultre, P., & Tremblay, R. (2012). Modeling of earthquake-induced damage in reinforced concrete buildings. Engineering Structures, 42, 172-181.
3. Loss Data Collection and Analysis

      • Publication 1:

        • Author: Rainer, L., & Zschau, J.
        • Year: 2015
        • Title: “Analysis of Losses Due to Earthquakes: Case Studies and Insights”
        • Citation: Rainer, L., & Zschau, J. (2015). Analysis of losses due to earthquakes: Case studies and insights. Journal of Earthquake Engineering, 19(2), 348-370.

      • Publication 2:

        • Author: Rainer, L., et al.
        • Year: 2018
        • Title: “Seismic Loss Assessment: Challenges and Tools for Earthquake Risk Reduction”
        • Citation: Rainer, L., et al. (2018). Seismic loss assessment: Challenges and tools for earthquake risk reduction. Journal of Structural Safety, 74, 85-97.
4. Post-Event Damage Surveys
      • Publication 1:
        • Author: Basoz, N., & Kiremidjian, A. S.
        • Year: 1999
        • Title: “Post-Earthquake Damage Surveys and Loss Estimation Models”
        • Citation: Basoz, N., & Kiremidjian, A. S. (1999). Post-earthquake damage surveys and loss estimation models. Earthquake Spectra, 15(2), 315-340.
5. Catastrophe Modeling and Risk Analysis

    • Publication 1:

      • Author: Kunreuther, H., & Michel-Kerjan, E. O.
      • Year: 2009
      • Title: “Insuring Catastrophes: An Overview of Catastrophe Risk Modeling”
      • Citation: Kunreuther, H., & Michel-Kerjan, E. O. (2009). Insuring catastrophes: An overview of catastrophe risk modeling. Risk Analysis, 29(8), 1061-1074.

    • Publication 2:

      • Author: Clark, R., & Vickery, J.
      • Year: 2011
      • Title: “Advanced Techniques in Catastrophe Risk Modeling”
      • Citation: Clark, R., & Vickery, J. (2011). Advanced techniques in catastrophe risk modeling. Journal of Risk and Uncertainty, 43(3), 123-140.

conclusion:

Ms. Alidadi is a highly capable researcher with a promising career ahead in earthquake engineering and catastrophe modeling. With her existing strengths, she can excel in the role with further development in geospatial tools, catastrophe modeling experience, programming knowledge, and statistical techniques. KCC would greatly benefit from her expertise and contributions to the advancement of earthquake risk models. With some focused growth in the areas mentioned, she could become a leading expert in the field, making substantial contributions to KCC’s mission.

Sergio Gonzalez Sanchez| Metallurgy | Best Scholar Award

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Dr Sergio Gonzalez Sanchez| Metallurgy | Best Scholar Award

Beatriz Galindo Distinguished Senior Researcher,University Charles III of Madrid,Spain

Dr. Sergio González Sánchez is a highly accomplished and respected researcher in materials science and mechanical engineering, with significant contributions to both academic theory and practical applications. His multidisciplinary expertise, leadership in education, and international collaborations make him an ideal candidate for the Research for Best Scholar Award. His work has had a profound impact on the development of sustainable materials for transport and healthcare, and he is recognized globally for his contributions to both academia and industry.

Publication Profile
orcid

Education :

  • Ph.D. in Materials Physics (October 3, 2008)
    Complutense University of Madrid (Spain)
    Research conducted at the National Center for Metallurgical Research (CENIM-CSIC) as an FPI Fellow (Spain).

  • B.S. in Materials Engineering (1999-2003)
    Polytechnic University of Madrid (Spain)

  • Student Researcher Experience:

    • Institute of Ceramic and Glass (ICV-CSIC) (Spain): Project on the design and building of ceramic layers and monoliths using the EPD technique, including thermal and mechanical characterization (2002-2003).
    • Institute of Polymer Science and Technology (ICTP-CSIC) (Spain): Project on the morphology of thermoplastics molded by injection (2001-2002).

Experience:

  • Distinguished Researcher ‘Beatriz Galindo’ Senior Professor
    Carlos III University of Madrid (Spain)
    December 2024 – Present

  • Visiting Scientist
    University of Science and Technology Beijing (USTB) (China)
    January 2024

  • Visiting Scientist
    Helmholtz-Zentrum Hereon and DESY (Germany)
    July 2023

  • Visiting Scientist
    Erich Schmid Institute of Materials Science (Austria)
    May 2023
    Invited by Prof. Jürgen Eckert

  • Sabbatical Researcher
    Diamond Light Source (UK)
    February 2022

  • Senior Lecturer/Assistant Professor in Mechanical Engineering
    Northumbria University (UK)
    2018 – 2024

  • Lecturer in Mechanical Engineering and Programme Leader for the Engineering Foundation Year
    Northumbria University (UK)
    2015 – 2018

  • Postdoctoral Research Associate
    University of Manchester (UK)
    2013 – 2014
    Project: “Sensitization of aluminium alloys” within the LATEST2 (Light Alloys Towards Environmentally Sustainable Transport: 2nd Generation) project in the School of Materials.

  • Juan de la Cierva Fellow
    Autonomous University of Barcelona (Spain)
    2011 – 2013
    Project: “New metallic alloys for biomedical applications”

  • Postdoctoral Research Associate
    Tohoku University, WPI – Advanced Institute for Materials Research (Japan)
    2008 – 2010

  • Visiting Researcher
    University of Sheffield (UK)
    2006 – 2007
    Project: Mg-based bulk metallic glasses with high glass-forming ability (GFA).

Awards:

  • FHEA (Fellow of the Higher Education Academy)
  • CSci (Chartered Scientist)
  • CEng (Chartered Engineer)
  • MIScT (Member of the Institute of Science and Technology)
  • FIMMM (Fellow of the Institute of Materials, Minerals and Mining)
  • MIET (Member of the Institute of Engineering and Technology)
  • MICME (Member of the International Center for Mechanical Engineering)
  • MIMechE (Member of the Institution of Mechanical Engineers)
  • MIMMM (Member of the Institute of Materials, Minerals, and Mining)

Research Focus:

Dr. Sergio González Sánchez’s research lies at the intersection of materials science and engineering, with particular emphasis on the development of new metallic alloys for sustainable technologies. His work involves the design and characterization of advanced materials, focusing on applications in the fields of biomedical engineering, sustainable transportation, and the high-performance materials used in structural applications.

His most recent projects have centered on sensitization phenomena in aluminium alloys and the creation of new alloy systems for medical implants. His global research collaborations, spanning institutions in Europe, Asia, and the Americas, contribute to advancements in the environmental sustainability of metallic materials used in engineering, biomedical, and transportation applications.

 

Skills:

  • Materials Characterization
  • Alloy Design and Fabrication
  • Mechanical Testing and Performance Analysis
  • Materials for Biomedical Applications
  • High-Temperature Materials and Corrosion Resistance
  • Research Project Leadership and Management
  • Advanced Manufacturing Techniques
  • Interdisciplinary Collaboration in Materials Science and Engineering

 

Publication :

    • González, S., Wurster, S., Garay-Reyes, C.G., Hurtado-Macias, A., Ramasamy, P., Oleszak, D., Gammer, C., Prashanth, K.G., Martínez-García, A., Eckert, J., Martínez-Sánchez, R. (2024). Glass formation and mechanical behaviour of the ZrHfTiCuNiCoAl multicomponent system. Mater. Sci. Eng. A (submitted).

    • González, S., Garay-Reyes, C.G., Martínez-García, A., Gokuldoss Prashanth, K., Ruiz-Esparza Rodríguez, M.A., Hurtado-Macias, A., Eckert, J., Martínez-Sánchez, R. (2025). Cooling rate control combined with refractory Mo and/or V addition to enhance the mechanical properties of CoCrFeMnNi alloy. J. Materials Research and Technology, 36, 459-469.

    • González, S., Chen, Z., Kang, J., Xu, X., Wang, X., Wu, Y., Lu, Z. (2024). Tuning the corrosion behavior of CoCrNi medium entropy alloy by addition of Ti and Al. Corrosion Science (submitted).

    • Atanacio-Sánchez, X., Garay-Reyes, C.G., Martínez-García, A., Estrada-Guel, I., Mendoza Duarte, J.M., Guerrero-Seañez, P., González, S., Rocha, E., Rangel, (Year not provided for the citation).

    CONCLUSION:

    Dr. González Sánchez’s research excellence, professional achievements, and leadership in the academic community make him an exemplary candidate for the Research for Best Scholar Award. His ability to integrate cutting-edge research with practical applications, alongside his recognition from peers and institutions worldwide, positions him as a leader in his field. By expanding his efforts in public engagement and broadening his interdisciplinary collaborations, he could further amplify his impact, both within the academic world and in wider societal contexts.