Assoc. Prof. Dr. Huseyin Erdal | Automation | Best Researcher Award

Posted on by Global Sensor Awards

Assoc. Prof. Dr. Huseyin Erdal | Automation | Best Researcher Award

Assoc. Prof. Dr. Huseyin Erdal | Automation | Aksaray University | Turkey

Hüseyin Erdal, Ph.D., is an Associate Professor in the Department of Medical Genetics at the Faculty of Medicine, Aksaray University, with a specialization in molecular biochemistry, genetics, and biomedical research. He earned his Ph.D. in Molecular Biochemistry and Genetics from Hatay Mustafa Kemal University in 2019, focusing on thiol-disulfide balance and thioredoxin reductase enzyme levels in chronic kidney disease and hemodialysis patients. In addition, he holds two bachelor’s degrees: one in Chemistry and another in Economics from Anadolu University, complementing his interdisciplinary expertise. Professor Erdal began his academic career as a Research Assistant at Mustafa Kemal University, conducting studies in analytical chemistry and molecular sciences, before joining Aksaray University as an Assistant Professor and later being promoted to Associate Professor in 2023. His professional work spans molecular biochemistry, genetics, biomaterials, and therapeutic applications, emphasizing translational research that bridges fundamental molecular mechanisms with clinical implementation.

Professional Profile

Scopus

Google Scholar

Suitability Summary 

Prof. Hüseyin Erdal is a distinguished scientist whose exceptional contributions in molecular biochemistry, genetics, and biomedical research make him highly suitable for the Best Researcher Award. With a Ph.D. in Molecular Biochemistry and Genetics from Hatay Mustafa Kemal University (2019), his work has focused on critical areas such as dynamic thiol-disulfide balance and thioredoxin reductase enzyme levels in chronic kidney disease, demonstrating a strong commitment to understanding and addressing complex molecular mechanisms relevant to human health.

Education

  • Ph.D. in Molecular Biochemistry and Genetics, Hatay Mustafa Kemal University, 2019
    Thesis: “Dynamic thiol-disulfide balance and thioredoxin reductase enzyme levels in chronic kidney disease and thiol balance in hemodialysis”

  • Research experience at University of Florida, 2013

  • Bachelor’s Degree in Chemistry, Anadolu University (Open Education), 2017

  • Bachelor’s Degree in Economics, Anadolu University (Open Education), 2017

Work Experience

  • Associate Professor, Department of Medical Genetics, Faculty of Medicine, Aksaray University, August 2023 – Present

  • Assistant Professor, Department of Medical Genetics, Faculty of Medicine, Aksaray University, 2020 – 2023

  • Research Assistant, Department of Chemistry, Mustafa Kemal University, 2014 – 2020

Achievements

  • Supervised graduate research projects, including innovative studies on collagen-based composite films for wound healing

  • Conducted research in molecular biochemistry, genetics, biomaterials, and therapeutic applications

  • Expertise in laboratory methodologies, enzymology, biochemical assays, and translational research bridging molecular insights with clinical applications

Awards and Honors

  • Recognized for contributions to biomedical research and translational science through awards and academic distinctions

Publication Top Notes

  • Title: Oxidative stress and its impacts on intracellular lipids, proteins and DNA
    Authors: O. Özcan, H. Erdal, G. Çakırca, Z. Yönden
    Year: 2015
    Citations: 158

  • Title: Oxidative stress and its effects on intracellular lipid, protein and DNA structures
    Authors: O. Özcan, H. Erdal, G. Çakırca, Z. Yönden
    Year: 2015
    Citations: 122

  • Title: Cancer cell sensing and therapy using affinity tag-conjugated gold nanorods
    Authors: E. Yasun, H. Kang, H. Erdal, S. Cansiz, I. Ocsoy, Y.F. Huang, W. Tan
    Year: 2013
    Citations: 67

  • Title: The Effect of Pneumatic Tube Systems on the Hemolysis of Biochemistry Blood Samples
    Authors: G. Çakırca, H. Erdal
    Year: 2017
    Citations: 41

  • Title: Biomedical applications of polyglycolic acid (PGA)
    Authors: E. Göktürk, H. Erdal
    Year: 2017
    Citations: 32

  • Title: Plasma ischemia-modified albumin levels and dynamic thiol/disulfide balance in sickle cell disease: a case-control study
    Authors: O. Özcan, H. Erdal, G. İlhan, D. Demir, A.B. Gürpınar, S. Neşelioğlu, Ö. Erel
    Year: 2018
    Citations: 28

  • Title: Evaluation of thiol-disulfide balance in adolescents with vitamin B12 deficiency
    Authors: M.S. Demirtaş, H. Erdal
    Year: 2023
    Citations: 19

  • Title: Thiol/disulfide Homeostasis as a New Oxidative Stress Marker in Patients with Fabry Disease
    Authors: H. Erdal, F. Turgut
    Year: 2023
    Citations: 18

Prof. Ivan Beloev | Power Transformer | Best Researcher Award

Posted on by Global Sensor Awards

Prof. Ivan Beloev | Power Transformer | Best Researcher Award

Prof. Ivan Beloev | Power Transformer | University of Russe “Angel Kanchev” | Bulgaria

Professor Ivan Beloev, is a distinguished academic and researcher in the field of transport technology and management. He currently serves as the Head of the Center for Continuing Education and Head of the Department of Transport at Angel Kanchev University of Ruse, where he also holds a professorship. His academic journey and professional career have been deeply rooted in the same esteemed institution, where he has steadily progressed from Assistant to Associate Professor and now to Full Professor. Throughout his tenure, Professor Beloev has made significant contributions to the advancement of transport systems, sustainable mobility, and energy-efficient technologies in transportation engineering.

Professional Profile

Google Scholar

Suitability Summary

Prof. Ivan Beloev is an outstanding and visionary Bulgarian researcher, academic, and innovator whose extensive contributions to transport technology, sustainable mobility, and environmental protection make him a highly suitable candidate for the Best Researcher Award. With over a decade of academic and research experience at the University of Ruse “Angel Kanchev”, Prof. Beloev has demonstrated consistent excellence in teaching, leadership, research innovation, and international collaboration.

Education and Training

  • Ph.D. in Transport, Shipping, and Aviation (2014–2015)
    University of Ruse “Angel Kanchev”
    Dissertation Title: Development and research of a modular system for combined energy providing and monitoring of harmful emissions of road transport.

  • Master’s Degree in Technology and Management of Transport (2013–2014)
    University of Ruse “Angel Kanchev”

  • Bachelor’s Degree in Technology and Management of Transport (2009–2013)
    University of Ruse “Angel Kanchev”
    Professional Qualification: Transport Engineer

Work Experience

  • Head of Center for Continuing Education (2023–Present)
    University of Ruse “Angel Kanchev”
    Responsible for the strategic leadership, coordination, and management of lifelong learning initiatives, promoting continuous professional development and collaboration between academia and industry.

  • Head of Department of Transport (2021–Present)
    University of Ruse “Angel Kanchev”
    Oversees academic programs, curriculum development, and departmental research in technology and transport management, ensuring academic excellence and innovation in the field.

  • Professor, Department of Transport (2023–Present)
    University of Ruse “Angel Kanchev”
    Engaged in advanced teaching, mentoring doctoral candidates, and conducting high-impact research in transport technologies and sustainable mobility systems.

  • Associate Professor, Department of Transport (2018–2023)
    University of Ruse “Angel Kanchev”
    Focused on research in transport management, emissions monitoring, and the integration of alternative energy systems in transport operations.

  • Assistant Professor, Department of Transport (2015–2018)
    University of Ruse “Angel Kanchev”
    Conducted lectures, supervised student projects, and participated in national and international transport research collaborations.

  • Assistant, Department of Transport (2014–2015)
    University of Ruse “Angel Kanchev”
    Supported teaching activities, performed laboratory work, and assisted in research related to transport technology and management.

Achievements and Specializations

  • Developed strong professional expertise in organizing and conducting experimental research.

  • Skilled in analyzing experimental data and working with various experimental and measurement equipment.

  • Participated in international academic and research collaborations, including Erasmus Intensive Programmes focused on sustainable transport and environmental protection technologies.

    • “Powering The Future with Zero Emission and Human Powered Vehicles,” Terrassa, Spain (2011)

    • “Education for Sustainable Development from the Perspective of Technologies and Materials for Environmental Protection”

Awards and Honors

  • 2017 Young Scientist Award, Austrian Ministry of Science, Research, and Economic and Institutional Affairs and Central Europe, recognizing outstanding research contributions in transport technology.

  • Best Book Award (2017) – Scientific Conference of the University of Ruse and the Union of Students, for excellence in training and innovative student professional development in transport, navigation, and aviation.

  • Publication Excellence Recognition (2016) – For the thesis “Development and supply of a modular system for combined energy supply and monitoring of harmful emissions of road transport.”

  • National Assembly of the Republic of Bulgaria (2017) – Commended for leadership in HYDRU project excellence and for enhancing the reputation of the University of Ruse.

  • Second Prize (2018) – Research Fund Prize for design, creation, experimentation, and optimization of the “City Car Logic” powered by an alternative energy source.

Publication Top Notes

  • Title: A comprehensive survey: Evaluating the efficiency of artificial intelligence and machine learning techniques on cyber security solutions
    Authors: M. Ozkan-Okay, E. Akin, Ö. Aslan, S. Kosunalp, T. Iliev, I. Stoyanov, I. Beloev
    Year: 2024
    Citations: 218

  • Title: A review on current and emerging application possibilities for unmanned aerial vehicles
    Authors: I.H. Beloev
    Year: 2016
    Citations: 90

  • Title: Artificial intelligence-driven autonomous robot for precision agriculture
    Authors: I. Beloev, D. Kinaneva, G. Georgiev, G. Hristov, P. Zahariev
    Year: 2021
    Citations: 85

  • Title: Artificial intelligence in wireless communications-evolution towards 6G mobile networks
    Authors: T.B. Iliev, E.P. Ivanova, I.S. Stoyanov, G.Y. Mihaylov, I.H. Beloev
    Year: 2021
    Citations: 36

  • Title: Investigation of the tractor performance when ballasting its rear half-frame
    Authors: V. Bulgakov, R. Antoshchenkov, V. Adamchuk, I. Halych, Y. Ihnatiev, I. Beloev
    Year: 2022
    Citations: 32

  • Title: A review of the characteristics of modern unmanned aerial vehicles
    Authors: G.V. Hristov, P.Z. Zahariev, I.H. Beloev
    Year: 2016
    Citations: 31

  • Title: Web-based environment for virtual laboratories in the field of electrical engineering
    Authors: B. Evstatiev, K. Gabrovska-Evstatieva, V. Voynohovska, I. Beloev
    Year: 2019
    Citations: 26

  • Title: Numerical simulation of processes in an electrochemical cell using COMSOL Multiphysics
    Authors: I.K. Iliev, A.R. Gizzatullin, A.A. Filimonova, N.D. Chichirova, I.H. Beloev
    Year: – (Not provided)
    Citations: 25

Dr. Mojtaba Ahmadieh khanesar | Metrology | Best Researcher Award

Posted on by Global Sensor Awards

Dr. Mojtaba Ahmadieh khanesar | Metrology | Best Researcher Award 

Dr. Mojtaba Ahmadieh khanesar | Metrology | University of Nottingham | United Kingdom

Dr. Mojtaba Ahmadieh Khanesar is a distinguished research fellow in optical metrology and machine learning at the Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham. He holds a Ph.D. in Control Engineering from K. N. Toosi University of Technology and has extensive experience in metrology, robotics, control systems, artificial intelligence, and machine learning. Throughout his career, Dr. Khanesar has contributed to internationally recognized projects funded by EPSRC, including Robodome imaging for high-performance aerostructures, HARISOM for precise industrial robot manipulation, and Chattyfactories for next-generation industrial systems, demonstrating proficiency in experimental design, data acquisition, and real-time control using advanced robotics platforms such as UR5, Baxter, Sawyer, and laser tracking systems. He has also supervised Ph.D. and undergraduate students, providing mentorship in control, robotics, and machine learning projects, and delivered lectures on Bayesian learning and reinforcement learning at the University of Nottingham. Dr. Khanesar has held research and teaching positions across Denmark, Turkey, Iran, and the United Kingdom, reflecting his global research engagement and collaborative approach. His research has been widely published, with 112 documents, 2,377 citations, and an h-index of 25, including publications in high-impact journals such as IEEE Transactions, Robotics, Mechanism and Machine Theory, and Sensors. His professional affiliations include SMIEEE, MIET, and MASME, highlighting his recognized standing in international technical communities.

Professional Profile: ORCID | Scopus

Selected Publications 

  1. Ahmadieh Khanesar, M. (2025). Inkjet printing of ZIF-67 based-polymer composite membranes. Separation and Purification Technology. 0 citations.

  2. Ahmadieh Khanesar, M. (2025). Multi-Objective Intelligent Industrial Robot Calibration Using Meta-Heuristic Optimization Approaches. Robotics. 0 citations.

  3. Ahmadieh Khanesar, M. (2025). Virtual Instrument for a Multi-illumination Dome System. Conference Paper. 0 citations.

  4. Ahmadieh Khanesar, M. (2023). Precision Denavit–Hartenberg Parameter Calibration for Industrial Robots Using a Laser Tracker System and Intelligent Optimization Approaches. Sensors, Basel, Switzerland. 25 citations.

  5. Ahmadieh Khanesar, M. (2023). A Neural Network Separation Approach for the Inclusion of Static Friction in Nonlinear Static Models of Industrial Robots. IEEE ASME Transactions on Mechatronics. 9 citations.

Dr. Nan Liu | Intelligent Manufacturing Awards | Best Researcher Award

Posted on by Global Sensor Awards

Dr. Nan Liu | Intelligent Manufacturing Awards | Best Researcher Award 

Dr. Nan Liu, Hefei University of Technology, China

Dr. Nan Liu is a dedicated researcher and faculty member at Hefei University of Technology, specializing in intelligent manufacturing with a focus on optimizing gear production through AI-driven algorithms. His work aims to enhance processing quality, reduce costs, and advance smart manufacturing technologies. He has led research funded by the National Natural Science Foundation of China (Project No. U22B2084) and authored high-impact publications, including a notable SCI-indexed article on spiral bevel gear grinding force prediction using generalized regression neural networks. Dr. Liu’s contributions lie at the intersection of mechanical engineering and artificial intelligence, positioning him as a rising expert in the field of advanced manufacturing systems.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award – Dr. Nan Liu

Dr. Nan Liu demonstrates strong potential and emerging excellence in the domain of intelligent manufacturing, particularly through the integration of artificial intelligence in gear processing. His current research under the National Natural Science Foundation of China (Project No. U22B2084) exemplifies his capability to address complex engineering problems using AI-driven methodologies.

🎓 Education & Qualifications

  • Ph.D. in Mechanical or Manufacturing-related field (inferred from expertise, institution not specified)

  • Expert in Artificial Intelligence Applications in gear manufacturing and intelligent systems

💼 Work Experience

  • Assistant Professor, Hefei University of Technology

  • Specializes in applying AI algorithms to optimize gear manufacturing processes

  • Focused on improving grinding force prediction, processing quality, and reducing production costs

🏆 Achievements

  • 🔬 Research Grant from National Natural Science Foundation of China (Project No. U22B2084)

  • 📄 Published a high-impact journal article in Engineering Applications of Artificial Intelligence (Elsevier, 2025)

  • 🧠 Developed a Generalized Regression Neural Network model for spiral bevel gear force prediction

  • 🛠️ Contributed to advancing intelligent manufacturing technologies

🥇 Award & Honors

  • 🏅 Award Category Preference: Best Research Scholar Award

  • 📌 Recognized for bridging AI techniques with precision gear manufacturing

Publication Top Notes:

Research on grinding force prediction of spiral bevel gear based on generalized regression neural network and undeformed grinding chips

Research on a nonlinear quasi-zero stiffness vibration isolator with a vibration absorber

Assoc. Prof. Dr. Xiaozhen Lian | Product Design Awards | Best Researcher Award

Posted on by Global Sensor Awards

Assoc. Prof. Dr. Xiaozhen Lian | Product Design Awards | Best Researcher Award 

Assoc. Prof. Dr. Xiaozhen Lian, Jimei University, China

Dr. Xiaozhen Lian is a dedicated researcher in product innovation design and intelligent manufacturing, with a Ph.D. in Mechanical Design and Theory from Xiamen University (2023). She also holds a Master’s degree in Management Science and Engineering from China University of Mining and Technology and a Bachelor’s degree in Industrial Engineering from Anhui Polytechnic University. Her academic and professional work centers on quality control in manufacturing processes, multi-attribute decision-making, risk prediction, modular product design, and user-centered redesign strategies. Dr. Lian has led and contributed to multiple national research projects, including those funded by the Ministry of Science and Technology and the National Natural Science Foundation of China. She has published extensively in top-tier journals such as Advanced Engineering Informatics, Journal of Engineering Design, and Soft Computing. In addition to her academic achievements, she holds several patents, has reviewed manuscripts for leading SCI and EI journals, and is recognized for her leadership and excellence in student organizations and technical competitions. A passionate long-distance runner and basketball enthusiast, she brings perseverance and teamwork into both her research and life pursuits.

Professional Profile:

SCOPUS

Summary of Suitability – Dr. Lian Xiaozhen for Best Researcher Award

Dr. Lian Xiaozhen is a highly promising and impactful early-career researcher in the field of intelligent manufacturing and product innovative design, with a strong academic foundation and a growing international research presence. With a Ph.D. in Mechanical Design and Theory from Xiamen University (2023), Dr. Lian integrates engineering, data science, and decision theory to advance modern manufacturing systems.

🎓 Education Background

  • 📍 Ph.D. in Mechanical Design and Theory
    Xiamen University, July 2023

  • 📍 Master’s in Management Science and Engineering
    China University of Mining and Technology (CUMT), July 2018

  • 📍 Bachelor’s in Industrial Engineering
    Anhui Polytechnic University (AHPU), July 2015

💼 Work & Research Experience

  • 🔬 Research Interests:

    • Product Innovative Design

    • Intelligent Manufacturing

    • Manufacturing Process Quality Control

    • Product Modular Design Theory

    • MADM, Risk Identification, Fuzzy Theory

  • 📊 Projects Involved:

    • Ministry of Science and Technology of China

    • Natural Science Foundation of China (multiple projects on inverse design, function module partition)

📝 Selected Publications

  • 📘 Advanced Engineering Informatics, 2023

  • 📘 Journal of Engineering Design, 2022

  • 📘 Soft Computing, 2023

  • 📘 Symmetry, 2022

  • 📘 Computer Integrated Manufacturing Systems

  • 📘 Journal of Machine Design

  • 📘 Journal of Shanghai Jiao Tong University

  • 📘 Conference on Frontiers of Design and Manufacturing (Accepted)

🏅 Achievements & Awards

  • 🥇 Postgraduate National Scholarship

  • 🥈 Undergraduate National Inspirational Scholarship

  • 🏆 First-Class Graduate Scholarships at CUMT & AHPU

  • 👏 Outstanding Student & Graduate of CUMT

  • 💡 Founder of IE Association at CUMT

  • 🗣️ 2nd Prize in PPT Speech Contest

  • 🏭 Excellent Intern at Tianma Microelectronics

  • 💬 Best Customer Satisfaction Intern at East China Institute of Optoelectronics

📑 Review & Patent Contributions

  • 🧪 SCI/EI Journal Reviewer (Reviewed >16 manuscripts)

  • 🛠️ 2 Utility Model Patents (1st Author)

  • 🔬 4 Invention Patents (1st Author)

🎖️ Additional Honors & Qualities

  • 👨‍🏫 Class Monitor, Department Director, Academic Secretary

  • 🧠 Strong adaptability, teamwork, and learning ability

  • 🏃‍♂️ Competed in National Half Marathons (2017, 2022)

  • 🧮 Participant in Huawei Cup & Jiangsu Math Modeling Contests

  • 📈 Proven personal growth and responsibility during Ph.D.

Publication Top Notes:

Selection method of design scheme for LCD products based on RA and DFMEA

Best Industrial Sensing Technology

Posted on by Global Sensor Awards

Introductio Best Industrial Sensing Technology

Welcome to the Best Industrial Sensing Technology Award, recognizing excellence in the development and application of sensor technologies across industries. This prestigious award aims to honor individuals and organizations pushing the boundaries of sensing technology to drive innovation and efficiency in industrial processes.

About the Award:

The Best Industrial Sensing Technology Award is open to individuals and organizations worldwide who have made significant contributions to the field of industrial sensing technology. There are no age limits for eligibility, and both professionals and academics are encouraged to apply. Qualifications should demonstrate a deep understanding of sensing technologies and their applications in industrial settings. Publications related to sensing technology are considered a strong indicator of eligibility.

Requirements:

Applicants are required to submit a detailed description of their work in the field of industrial sensing technology, including relevant publications and qualifications. Evaluation criteria include the originality, impact, and feasibility of the proposed technology, as well as its potential for advancing industrial processes. Submissions should adhere to the submission guidelines outlined below.

Submission Guidelines:

Submissions should include a biography of the applicant, an abstract of the sensing technology project, and supporting files such as publications or patents. The abstract should clearly describe the technology, its application, and its potential impact on industrial processes. Supporting files should provide evidence of the technology’s effectiveness and relevance.

Evaluation Criteria:

Submissions will be evaluated based on the originality, impact, and feasibility of the proposed technology, as well as the applicant’s qualifications and publications in the field of industrial sensing technology. Preference will be given to technologies that have the potential to significantly improve industrial processes and efficiency.

Recognition:

Winners of the Best Industrial Sensing Technology Award will receive a certificate of recognition and will be featured on our website and social media channels. They will also have the opportunity to present their work at an industry conference or seminar.

Community Impact:

The Best Industrial Sensing Technology Award aims to promote innovation and collaboration in the field of industrial sensing technology, ultimately leading to advancements that benefit industries and society as a whole.