Mazlina Abdul Majid | Computer Science | Research Excellence Award

Published on by Global Scholar Awards

Research Excellence Award

Mazlina Abdul Majid
Universiti Malaysia Pahang Al-Sultan Abdullah, Malaysia

Mazlina Abdul Majid
Affiliation Universiti Malaysia Pahang Al-Sultan Abdullah
Country Malaysia
Scopus ID 57222473453
Documents 120
Citations 1,112
h-index 21
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0001-9068-7368

Mazlina Abdul Majid is a computer science academic and researcher at Universiti Malaysia Pahang Al-Sultan Abdullah whose scholarly work encompasses data analytics, simulation modelling, artificial intelligence, green information technology, optimization, software usability, and sustainability-oriented computing. Her research profile connects computational methods with operational and environmental challenges, including applications involving simulation, intelligent algorithms, data-driven analysis, and sustainable information systems. Institutional and scholarly profiles identify her with research activities in data science, simulation and modelling, green technology, software engineering, and analytics. [1] [2]

Abstract

Mazlina Abdul Majid is a Malaysian computer science researcher whose work integrates data analytics, artificial intelligence, simulation modelling, optimization, green information technology, and sustainable computing. Her research addresses computational approaches for operational, environmental, and organizational challenges, with applications spanning intelligent algorithms, data-driven decision making, software systems, and sustainability assessment. Her scholarly record includes studies of green information technology adoption, sustainable enterprise strategies, simulation-based operational analysis, artificial intelligence, and optimization methods. Recent publications further demonstrate engagement with engineering optimization and computer vision applications. These interdisciplinary contributions connect computational techniques with practical sustainability objectives and support evidence-based innovation across contemporary digital research environments.[5]

Keywords

Computer science; artificial intelligence; data analytics; simulation modelling; optimization; green information technology; sustainability; green computing; software usability; enterprise systems; agent-based modelling; operational research; convolutional neural networks; genetic algorithms; engineering optimization; differential evolution; Lévy flight; harmony search; environmental sustainability; air quality estimation; data science.

Introduction

Mazlina Abdul Majid has developed a research profile within computer science that emphasizes the application of computational intelligence to operational and sustainability-related problems. Her institutional profile identifies expertise in modelling and simulation, green operations research, sustainability impact analysis, and software consultancy, while other scholarly sources associate her work with artificial intelligence, data analytics, optimization, and software usability. [1] [3]

Research Profile

Mazlina Abdul Majid’s research profile spans data science, simulation modelling, artificial intelligence, green information technology, and sustainability-oriented computing. Mazlina Abdul Majid has also been associated with the Data Science and Simulation Modeling research environment at Universiti Malaysia Pahang Al-Sultan Abdullah, where computational modelling is positioned as a means of supporting data-driven innovation and analytical solutions. [1] [4]

Research Contributions

Mazlina Abdul Majid has contributed to research examining computational approaches for sustainability, information technology adoption, operational modelling, and intelligent optimization. Mazlina Abdul Majid has participated in studies addressing green information technology adoption in government institutions, sustainable enterprise strategies, agent-based green information systems, and optimization algorithms. More recent work extends these interests toward computer vision and intelligent estimation of environmental conditions. [5] [6]

Publications

Mazlina Abdul Majid has published research across green information technology, sustainability, simulation, artificial intelligence, data analytics, and optimization. Mazlina Abdul Majid is listed as a contributor to the study “A novel method of S-box design based on discrete chaotic maps and cuckoo search algorithm,” and to recent work on image-based air quality estimation using convolutional neural networks optimized by genetic algorithms. [5] [6]

Research Impact

Mazlina Abdul Majid’s research impact can be considered through the breadth of computational topics represented in her scholarly record, including sustainability, green information systems, simulation modelling, artificial intelligence, optimization, and data analytics. Mazlina Abdul Majid’s work connects methodological development with applied problems, particularly where computational models can support operational decisions, environmental assessment, and sustainable technology practices. [2]

Award Suitability

Mazlina Abdul Majid’s documented research activity aligns with the scope of a Research Excellence Award because her scholarly profile combines sustained publication activity with interdisciplinary work in computer science, data analytics, artificial intelligence, optimization, simulation, and sustainable information technology. Mazlina Abdul Majid’s publication themes demonstrate the application of computational methods to practical research problems, providing a coherent basis for recognition within the Computer Science category of the Global Scholar Awards.[5]

Conclusion

Mazlina Abdul Majid represents a multidisciplinary computer science research profile centered on intelligent computation, simulation, analytics, optimization, and sustainability. Mazlina Abdul Majid’s publications demonstrate the application of computational techniques to green information technology, operational modelling, environmental estimation, and engineering optimization. The combination of these research themes provides a relevant scholarly foundation for consideration for the Research Excellence Award.[4]

References

  1. Universiti Malaysia Pahang Al-Sultan Abdullah. (n.d.). UMPSA Expert Directory: Professor Ts. Dr. Mazlina Binti Abdul Majid.
    https://apps.ump.edu.my/expertDirectory/profile.jsp?email=mazlina%40ump.edu.my
  2. ORCID. (n.d.). Mazlina Abdul Majid, ORCID iD 0000-0001-9068-7368.
    https://orcid.org/0000-0001-9068-7368
  3. International Journal of Science of Technology. (n.d.). Editorial Team: Prof. Dr. Ts. Mazlina Abdul Majid.
    https://ijsot.org/index.php/ijsot/about/editorialTeam
  4. Universiti Malaysia Pahang Al-Sultan Abdullah. (n.d.). Data Science & Simulation Modeling Research Group.
    https://fk.umpsa.edu.my/index.php/component/sppagebuilder?id=298&view=page
  5. Majid, M. A., et al. (2019). Green information technology adoption towards a sustainability policy agenda for government-based institutions: An administrative perspective. Journal of Science and Technology Policy Management, 10(2), 274–300.
    https://doi.org/10.1108/JSTPM-11-2017-0056
  6. Khan, A. A., Majid, M. A., & Dandoush, A. (2025). Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach. International Journal of Advanced Computer Science and Applications, 16(3).
    https://thesai.org/Downloads/Volume16No3/Paper_113-Image_Based_Air_Quality_Estimation_Using_Convolutional_Neural_Network.pdf
  7. Qin, F., Zain, A. M., Zhou, K.-Q., Yusup, N. B., Prasetya, D. D., Jalil, R. A., Abidin, Z. Z., Bahari, M., Kamin, Y., & Majid, M. A. (2025). Hybrid Harmony Search Algorithm Integrating Differential Evolution and Lévy Flight for Engineering Optimization. IEEE Access.
    https://doi.org/10.1109/ACCESS.2025.3529714

Dominic Ayamga | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Best Researcher Award

Dominic Ayamga — University of Technology Sydney

Dominic Ayamga
Affiliation University of Technology Sydney
Country Ghana
Scopus ID 59668577800
Documents 2
Citations 1
h-index 1
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0001-8264-3189

Dominic Ayamga is a computer science researcher whose documented work focuses on enterprise security architecture, inference attacks, cybersecurity governance, and information security. His research addresses how established security models can encounter inference-related weaknesses and how organizational practices influence security outcomes. His scholarly profile reflects an emerging contribution to cybersecurity research. [1]

Abstract

Dominic Ayamga is a computer science researcher affiliated with the University of Technology Sydney whose work examines enterprise security architecture, inference attacks, cybersecurity governance, and human factors in information security. His documented research includes studies of the Bell-LaPadula model and inference attacks, alongside emerging work connecting cybersecurity culture, governance, and organizational behavior. These contributions address security risks arising from information flow, access control, policy implementation, and user practices. With publications indexed in scholarly databases and an identified ORCID record, Ayamga’s research profile reflects an developing focus on socio-technical cybersecurity, resilient enterprise information protection, and secure digital governance practices. research practice.[5]

Keywords

Inference attacks, enterprise security architecture, Bell-LaPadula model, information flow, cybersecurity governance, cybersecurity culture, access control, human behaviour, information security, organizational security, NIST Cybersecurity Framework, ISO/IEC 27001, inference attack detection, digital security, socio-technical cybersecurity.[2]

Introduction

Dominic Ayamga’s research sits within computer science and cybersecurity, with particular attention to enterprise security architecture and inference-related risks. His published work considers how established security models perform when information can be inferred from authorized or indirect access. This focus connects technical controls with governance and organizational practice in contemporary environments. [1]

Research Profile

Dominic Ayamga is affiliated with the University of Technology Sydney associated with research in cybersecurity and enterprise security architecture. Records identify his ORCID as 0000-0001-8264-3189 and document work presented through the International Conference on Security of Information and Networks. His profile emphasizes focused information security, inference attacks, governance, and protection. [3]

Research Contributions

Dominic Ayamga contributes to cybersecurity research by examining weaknesses emerging when enterprise security models encounter inference attacks. His Bell-LaPadula study evaluates information-flow protection in relation to inference risks, while later work broadens the analysis toward cybersecurity culture, governance, access practices, and organizational behavior. Studies connect security architecture with socio-technical risk. [1] [2]

Publications

Dominic Ayamga’s publications include The Bell-LaPadula (BLP) Enterprise Security Architecture Model vs Inference Attacks, published in the 2024 International Conference on Security of Information and Networks, and Cybersecurity Culture, Governance, and Inference Attacks: A Developing-Country Case Study on Enterprise Security Architecture Adaptation, posted as a 2026 preprint. Works establish trajectory. [1] [2]

Research Impact

Dominic Ayamga’s research impact is presently reflected through a focused publication record addressing inference attacks and enterprise security architecture. The work contributes to discussions about information flow, access governance, security culture, and organizational behavior. Available bibliographic information reports one citation and an h-index of one, indicating an early-stage scholarly profile. [2]

Award Suitability

Dominic Ayamga appears suitable for consideration for Best Researcher Award within a computer science or cybersecurity category because his documented work addresses a specialized security problem across technical and organizational dimensions. His research connects formal security architecture with inference risks, governance, and human behavior, providing a scholarly basis for recognition.[4]

Conclusion

Dominic Ayamga’s research profile demonstrates a developing contribution to cybersecurity, particularly enterprise security architecture and inference attacks. His publications progress from model-level analysis toward broader governance and behavioral considerations. The combination of technical security concerns, organizational context, and identifiable scholarly outputs provides a foundation for continued research and academic recognition.[2]

References

  1. Ayamga, D., Nanda, P., & Mohanty, M. (2024). The Bell-LaPadula (BLP) Enterprise Security Architecture Model vs Inference Attacks. 2024 17th International Conference on Security of Information and Networks (SIN), 1–8. https://doi.org/10.1109/SIN63213.2024.10871247
  2. Ayamga, D., Nanda, P., & Mohanty, M. (2026). Cybersecurity Culture, Governance, and Inference Attacks: A Developing-Country Case Study on Enterprise Security Architecture Adaptation. SSRN. https://doi.org/10.2139/ssrn.6212346
  3. University of Technology Sydney. (2024). The Bell-LaPadula (BLP) Enterprise Security Architecture Model vs Inference Attacks. Open Publications of UTS Scholars. https://opus.lib.uts.edu.au/handle/10453/185595
  4. ORCID. (n.d.). ORCID record: Dominic Ayamga, 0000-0001-8264-3189.
    https://orcid.org/0000-0001-8264-3189
  5. Elsevier. (n.d.). Scopus author details: Dominic Ayamga, Author ID 59668577800. Scopus.
    https://www.scopus.com/pages/authors/59668577800

SeongJeong Yoon | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Best Researcher Award

SeongJeong Yoon
Swiss School of Management

SeongJeong Yoon
Affiliation Swiss School of Management
Country South Korea
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0001-5188-801X

SeongJeong Yoon is affiliated with the Swiss School of Management and is recognized for scholarly contributions in Computer Science through research that supports technological innovation, intelligent computing, digital transformation, and interdisciplinary collaboration. The academic profile reflects sustained engagement with internationally indexed publications and professional research activities that contribute to contemporary scientific knowledge and practical applications within computing disciplines.[1]

Abstract

SeongJeong Yoon has developed an academic profile centered on Computer Science, emphasizing intelligent information systems, digital innovation, software engineering, data analytics, artificial intelligence, cloud technologies, cybersecurity, and emerging computational methodologies. Research activities demonstrate consistent engagement with internationally indexed publications, interdisciplinary collaborations, and knowledge dissemination through scholarly communication. The work contributes to technological advancement by integrating theoretical understanding with practical implementation while addressing contemporary scientific and industrial challenges. Continued participation in academic research reflects commitment to innovation, evidence-based investigation, sustainable digital transformation, and the advancement of global computing knowledge through impactful scholarly contributions and collaborative scientific excellence.[1][2]

Keywords

Artificial Intelligence, Machine Learning, Data Analytics, Software Engineering, Intelligent Systems, Digital Transformation, Cloud Computing, Cybersecurity, Information Systems, Deep Learning, Big Data, Computer Vision.

Introduction

SeongJeong Yoon advances Computer Science through interdisciplinary investigations integrating intelligent computing, software development, and digital technologies. Academic activities emphasize rigorous methodology, collaborative research, and internationally visible publications that strengthen technological innovation while supporting practical applications, sustainable development, and continued scientific progress across evolving computational environments.[1]

Research Profile

SeongJeong Yoon maintains an internationally oriented research profile supported by scholarly publications, institutional collaboration, and participation within modern computing disciplines. Research interests encompass intelligent systems, digital innovation, information technologies, and computational problem solving while contributing to knowledge exchange across academic and professional scientific communities worldwide.[2]

Research Contributions

SeongJeong Yoon contributes through scholarly investigations exploring advanced computing technologies, analytical methodologies, and innovative digital solutions. Research integrates theoretical concepts with practical implementation, encouraging interdisciplinary collaboration while supporting technological advancement, academic excellence, and sustainable innovation across diverse Computer Science research applications.[3]

Publications

SeongJeong Yoon has authored and collaborated on scholarly publications addressing contemporary Computer Science themes including artificial intelligence, software engineering, information systems, cloud computing, and digital transformation. Published research demonstrates methodological consistency, academic relevance, and valuable contributions supporting evidence-based technological development within international scientific literature.[2]

Research Impact

SeongJeong Yoon demonstrates measurable research impact through internationally indexed publications, scholarly visibility, citation activity, and interdisciplinary engagement. Academic contributions encourage knowledge transfer, technological innovation, and collaborative scientific advancement while supporting future investigations addressing emerging computational challenges across academic and industrial environments.[4]

Award Suitability

SeongJeong Yoon demonstrates qualities consistent with recognition through the Best Researcher Award by maintaining sustained scholarly productivity, international academic engagement, and impactful Computer Science research. Professional achievements illustrate commitment to innovation, scientific integrity, collaborative excellence, and meaningful contributions benefiting contemporary global research communities.[5]

Conclusion

SeongJeong Yoon represents an accomplished academic whose Computer Science research supports technological advancement through interdisciplinary scholarship, internationally indexed publications, and collaborative scientific engagement. Continued research activities reinforce professional excellence while contributing valuable knowledge that advances innovation, digital transformation, and sustainable computing research worldwide.[1]

References

  1. Moon, J.-H., Kim, N., Kim, W., & Yoon, S. (2024). A research on the technological elements of the digital twin operation platform in the industrial metaverse federation. https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11933357
  2. ORCID. (n.d.). ORCID record for SeongJeong Yoon.
    https://orcid.org/0000-0001-5188-801X
  3. Kim, N., Kim, W., & Yoon, S. (2024). Field empirical research on generative artificial intelligence job file generation and worker behavior issues.
    https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11742484
  4. Choi, J., Kim, N., Kim, W., & Yoon, S. (2023). Research on trends and key issues in industrial collaborative robots and worker interaction.
    https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11509571
  5. Global Scholar Awards. (n.d.). Best Researcher Award Recognition.
    https://globalscholarawards.com/

Mazen Ramadhan | Computer Science | Innovative Research Award

Published on by Global Scholar Awards

Innovative Research Award

Mazen Ramadhan
Multimedia University, Malaysia

Mazen Ramadhan
Affiliation Multimedia University
Country Malaysia
Scopus ID 57215557743
Documents 16
Citations 176
h-index 6
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0001-9555-7781

Mazen Ramadhan is a researcher at Multimedia University, Malaysia, whose scholarly work primarily focuses on computer science, intelligent systems, cybersecurity, machine learning, digital technologies, and applied computing. His research demonstrates interdisciplinary collaboration and addresses practical technological challenges through innovative computational methods. With publications indexed in major academic databases and measurable citation impact, his contributions have supported advancements in emerging digital technologies and continue to influence research within computer science and related engineering disciplines.[1]

Abstract

Mazen Ramadhan has established a research portfolio centered on computer science with emphasis on cybersecurity, intelligent systems, machine learning, software engineering, digital transformation, and data-driven technologies. His scholarly publications demonstrate practical applications of computational techniques for addressing contemporary technological problems while encouraging interdisciplinary collaboration. Through peer-reviewed research, measurable citation performance, and international academic visibility, his work contributes to knowledge development in emerging digital domains. The consistency of his publications, collaborative research activities, and recognized academic profile reflect sustained contributions to advancing innovation, computational methodologies, and applied scientific research within the global computer science community.[2]

Keywords

Cybersecurity, Machine Learning, Artificial Intelligence, Internet of Things, Software Engineering, Deep Learning, Computer Networks, Data Analytics, Intelligent Systems, Cloud Computing, Digital Transformation, Information Security.

Introduction

Mazen Ramadhan conducts research addressing modern computing challenges through interdisciplinary methods integrating artificial intelligence, cybersecurity, and software technologies. His publications reflect practical problem solving, collaborative investigation, and continuous engagement with emerging digital innovations supporting academic advancement and technological development across diverse computer science applications.[3]

Research Profile

Mazen Ramadhan maintains an internationally visible research profile supported by Scopus, Google Scholar, ORCID, ResearchGate, and institutional records. His publication metrics demonstrate consistent scholarly productivity, interdisciplinary collaboration, and citation impact within computer science, reflecting recognized academic participation in global research communities.[1]

Research Contributions

Mazen Ramadhan contributes to advancing intelligent computing by investigating secure digital systems, machine learning applications, software engineering practices, and innovative computational methodologies. His research supports practical implementations while encouraging multidisciplinary collaboration, enabling improvements in technology adoption, cybersecurity resilience, and intelligent information processing.[4]

Publications

Mazen Ramadhan has authored peer-reviewed publications indexed by Scopus and Google Scholar covering cybersecurity, artificial intelligence, machine learning, digital technologies, and software engineering. These publications demonstrate methodological diversity, collaborative research, and meaningful academic dissemination across recognized international journals and conference proceedings.[2]

Research Impact

Mazen Ramadhan has achieved measurable research influence through citations, indexed publications, and collaborative scientific activities. His scholarly output supports ongoing developments in computer science while contributing evidence-based knowledge that benefits researchers, practitioners, and future investigations across intelligent digital technologies and computational innovation.[1]

Award Suitability

Mazen Ramadhan demonstrates qualifications appropriate for the Innovative Research Award through sustained publication activity, interdisciplinary computer science research, international academic visibility, and measurable scholarly impact. His research achievements illustrate innovation, scientific consistency, and meaningful contributions supporting technological advancement and global academic collaboration.[5]

Conclusion

Mazen Ramadhan continues contributing to computer science through interdisciplinary research, impactful scholarly publications, and international collaboration. His academic profile reflects sustained scientific productivity, practical innovation, and commitment to advancing intelligent digital technologies, supporting recognition within prestigious international research and innovation award programs.[2]

External Links

References

  1. Elsevier. (n.d.). Scopus Author Details: Mazen Ramadhan, Author ID 57215557743. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57215557743
  2. Google Scholar. (n.d.). Mazen Ramadhan Citation Profile.
    https://scholar.google.com/citations?user=-vuQJ7IAAAAJ&hl=en&oi=ao
  3. Multimedia University. (n.d.). Academic Expert Profile: Mazen Ramadhan.
    https://mmuexpert.mmu.edu.my/ramadhanmazen
  4. ORCID. (n.d.). Mazen Ramadhan Research Record.
    https://orcid.org/0000-0001-9555-7781
  5. IEEE. (2019). Representative publication in intelligent computing.
    https://doi.org/10.1109/ACCESS.2020.2970475

Boris Goldengorin | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Prof. Boris Goldengorin | Computer Science | Best Researcher Award

Optimal Management of Tools in Computer Science at Ohio University, United States

Prof. Boris Goldengorin is a globally recognized expert in combinatorial optimization, applied mathematics, and operations research, with a career spanning over five decades. Holding multiple PhDs and a Doctor of Science, he pioneered groundbreaking data correcting algorithms that revolutionized the solving of complex optimization problems such as the Quadratic Cost Partition, Max-Cut, and Traveling Salesman Problems. With over 100 publications in leading international journals and numerous books and monographs, his research has significantly advanced quantitative logistics, supply chain management, and industrial engineering. His algorithms have consistently outperformed global benchmarks, holding world records in solving large-scale combinatorial problems. Prof. Goldengorin has also served as an associate editor for several prestigious journals and has mentored generations of top-performing researchers and students. Honored internationally for his scientific contributions, he continues to influence both theoretical research and practical applications across disciplines, making him a leading figure in modern combinatorial optimization and applied mathematics.

Professional Profile

Education

Prof. Boris Goldengorin possesses an extensive and diverse educational background, reflecting his deep expertise across engineering, applied mathematics, and optimization. He earned his first MSc in Electrical Engineering from Ryazan Radio-Engineering Institute, Russia, in 1967, followed by a second MSc in Applied Mathematics from the Moscow Institute of Electronics and Mathematics in 1973. He completed his PhD in Engineering Sciences at the prestigious VNIINMASH, part of the USSR Ministry of Standardization, in 1975. Further demonstrating his commitment to advanced research, he earned a Doctor of Science (ScD) in Engineering Sciences from the Institute for System Analysis at the USSR Academy of Sciences in 1989. His academic journey continued internationally, obtaining a PhD in Combinatorial Optimization from the University of Groningen, The Netherlands, in 200

Professional Experience

Prof. Boris Goldengorin has built a distinguished career as a researcher, professor, and global leader in combinatorial optimization and operations research. He has held prominent academic and research positions at top institutions, including the University of Groningen (Netherlands), Ohio University (USA), and Khmelnitsky National University (Ukraine), contributing extensively to the fields of mathematical programming, quantitative logistics, and industrial engineering. His pioneering work on data correcting algorithms has shaped modern approaches to solving large-scale optimization problems. Prof. Goldengorin also serves as an associate editor for leading journals such as the Journal of Global Optimization, Journal of Combinatorial Optimization, and Journal of Computational and Applied Mathematics, showcasing his influence in global scientific discourse. Alongside his research, he has mentored generations of students, many of whom have become world-class researchers. His career reflects a rare blend of theoretical innovation, practical application, and global academic leadership, making him a pivotal figure in applied mathematics and operations research.

Research Interest

Prof. Boris Goldengorin’s research interests lie at the intersection of combinatorial optimization, operations research, applied mathematics, and quantitative logistics, where he has made pioneering contributions for over five decades. His primary focus is on developing data correcting algorithms (DCA) and tolerance-based approaches, which have significantly advanced the efficient solving of large-scale optimization problems. His work spans supply chain management, industrial engineering, network analysis, and scheduling problems, with a particular emphasis on benchmark instances such as the Quadratic Cost Partition Problem, Max-Cut Problem, Traveling Salesman Problem, and Simple Plant Location Problem. Beyond classical optimization, Prof. Goldengorin explores the mathematical foundations of algorithmic efficiency and robustness, contributing to big data analysis, game theory, and image processing. His research combines theoretical rigor with computational innovation, enabling faster and more accurate solutions to some of the most computationally challenging problems across disciplines, ensuring long-term impact on both academia and industry applications.

Awards and Honors

Prof. Boris Goldengorin has received numerous awards and honors throughout his illustrious career, recognizing his extraordinary contributions to combinatorial optimization, applied mathematics, and operations research. In 2015, he was named C. Paul Stocker Honorary Professor in Industrial and Systems Engineering at Ohio University, USA. In 2013, the United States Citizenship and Immigration Services (USCIS) granted him Honorable Recognition as an Alien with Extraordinary Ability in Science, Technology, and Education. In 2008, he was recognized as the Best Scientist in Applied Mathematics and Informatics by the Municipality of Khmelnitsky Region, Ukraine. His contributions were further acknowledged in 2005 when Khmelnitsky National University awarded him an Honorary Doctorate in Applied Mathematics and Computer Technologies. Earlier, in 2003, he was named a Fellow in Quantitative Logistics by the Royal Netherlands Academy of Arts and Sciences. These prestigious honors reflect Prof. Goldengorin’s global impact and pioneering role in advancing applied mathematics and optimization research.

Research Skills

Prof. Boris Goldengorin possesses exceptional research skills that span theoretical development, algorithm design, computational experimentation, and interdisciplinary application. His ability to formulate complex combinatorial optimization problems, develop innovative algorithms such as Data Correcting Algorithms (DCA), and rigorously validate their performance through extensive computational benchmarking sets him apart as a world-class researcher. His expertise includes algorithmic design for large-scale optimization problems, quantitative logistics modeling, and supply chain optimization, showcasing his ability to translate mathematical theory into practical solutions. Prof. Goldengorin also excels in analyzing computational complexity, ensuring his algorithms not only produce optimal solutions but do so with unmatched speed and efficiency, often outperforming the leading methods globally. His collaborative research style, combining mentorship, teamwork, and interdisciplinary thinking, has produced high-impact publications across applied mathematics, operations research, game theory, and industrial engineering, making him a highly versatile and innovative researcher with profound analytical and computational skills.

Conclusion

Dr. Boris Goldengorin is highly suitable for the Best Researcher Award.

His exceptional track record in combinatorial optimization, algorithmic innovations, world-record computational achievements, and long-term research leadership position him as a top contender for such a prestigious award.

His global impact, cross-disciplinary contributions, and ability to outperform top research teams in algorithmic efficiency make him a standout figure in applied mathematics, optimization, and industrial engineering.

Publications Top Noted

  • Proceedings of the 11th International Conference on Integer Programming and Combinatorial Optimization
    M. Jünger, V. Kaibel
    Springer-Verlag
    2005 — 233 citations

  • Branch and peg algorithms for the simple plant location problem
    B. Goldengorin, D. Ghosh, G. Sierksma
    Computers & Operations Research 30 (7), 967-981
    2003 — 112 citations

  • The data-correcting algorithm for the minimization of supermodular functions
    B. Goldengorin, G. Sierksma, G.A. Tijssen, M. Tso
    Management Science 45 (11), 1539-1551
    1999 — 76 citations

  • Improvements to MCS algorithm for the maximum clique problem
    M. Batsyn, B. Goldengorin, E. Maslov, P.M. Pardalos
    Journal of Combinatorial Optimization 27, 397-416
    2014 — 65 citations

  • Network approach for the Russian stock market
    A. Vizgunov, B. Goldengorin, V. Kalyagin, A. Koldanov, P. Koldanov, etc.
    Computational Management Science 11, 45-55
    2014 — 65 citations

  • A hybrid method of 2-TSP and novel learning-based GA for job sequencing and tool switching problem
    E. Ahmadi, B. Goldengorin, G.A. Süer, H. Mosadegh
    Applied Soft Computing 65, 214-229
    2018 — 60 citations

  • Tolerance-based branch and bound algorithms for the ATSP
    M. Turkensteen, D. Ghosh, B. Goldengorin, G. Sierksma
    European Journal of Operational Research 189 (3), 775-788
    2008 — 54 citations

  • Lower tolerance-based branch and bound algorithms for the ATSP
    R. Germs, B. Goldengorin, M. Turkensteen
    Computers & Operations Research 39 (2), 291-298
    2012 — 47 citations

  • Tolerances applied in combinatorial optimization
    B. Goldengorin, G. Jäger, P. Molitor
    Journal of Computational Science 2 (9), 716-734
    2006 — 47 citations

  • Cell formation in industrial engineering: Theory, Algorithms and Experiments
    B. Goldengorin, D. Krushinsky, P.M. Pardalos
    Springer
    2013 — 45 citations

  • Solving the simple plant location problem using a data correcting approach
    B. Goldengorin, G.A. Tijssen, D. Ghosh, G. Sierksma
    Journal of Global Optimization 25, 377-406
    2003 — 38 citations

  • Requirements of standards: optimization models and algorithms
    B. Goldengorin
    (No specific journal listed)
    1995 — 35 citations

  • Worst case analysis of max-regret, greedy, and other heuristics for multidimensional assignment and traveling salesman problems
    G. Gutin, B. Goldengorin, H.J.
    Journal of Heuristics, 169-181
    2008 — 34 citations

  • Complexity evaluation of benchmark instances for the p-median problem
    B. Goldengorin, D. Krushinsky
    Mathematical and Computer Modelling 53 (9-10), 1719-1736
    2011 — 32 citations

  • Flexible PMP approach for large-size cell formation
    B. Goldengorin, D. Krushinsky, J. Slomp
    Operations Research 60 (5), 1157-1166
    2012 — 31 citations

Naeem Ullah | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Mr. Naeem Ullah | Computer Science | Best Researcher Award

PhD Student at Software Engineering Research Group (SERG-UOM) University of Malakand, Pakistan

Mr. Naeem Ullah is a dedicated academic and researcher currently pursuing a PhD in Computer Science, with a focus on cybersecurity challenges in vehicle-to-vehicle communication from a software engineering perspective. Holding a strong academic record with a CGPA of 3.75/4.00, he has presented his research at international forums, such as the 2nd Annual International Workshop on Software Engineering, where he shared his Multivocal Literature Review (MLR) protocol on cybersecurity culture. Mr. Ullah has also received recognition for his teaching excellence, earning the Best Teacher Award in 2018. His work experience includes roles as a lecturer at the University Model College KPK, part-time tutor at Allama Iqbal Open University, and facilitator for continuous professional development programs for teachers. His research, currently under review, addresses crucial cybersecurity issues in vehicle-to-vehicle communications. Mr. Ullah’s commitment to furthering his knowledge is evident through multiple certifications in data science, networking, and cybersecurity.

Professional Profile 

Education

Mr. Naeem Ullah has a strong educational background in Computer Science. He is currently pursuing a PhD in Computer Science with a focus on cybersecurity challenges in vehicle-to-vehicle communication, maintaining an impressive CGPA of 3.75/4.00. His research aims to develop a mitigation model for cybersecurity issues in connected vehicle systems, reflecting his deep engagement with current technological challenges. Mr. Ullah completed his Master’s degree in Computer Science in 2019, achieving a CGPA of 3.7/4.00, with his thesis titled Software Development Process Improvement Model for Small Pakistani Software Development Companies. He also holds a Bachelor’s degree in Computer Science from 2014, with a CGPA of 3.62/4.00. His final year project, Auction Management System, showcased his ability to apply practical solutions to real-world problems. Mr. Ullah’s academic journey is marked by consistent excellence and a strong commitment to advancing his expertise in the field of computer science.

Professional Experience

Mr. Naeem Ullah has accumulated diverse professional experience in both academic and research roles. He has served as a Lecturer in Computer Science at the University Model College KPK, Peshawar, Pakistan, where he taught and mentored students in various computer science subjects. In addition, he has worked as a part-time tutor for Allama Iqbal Open University, Islamabad, since 2022, focusing on Information and Communication Technologies (ICT). Mr. Ullah has also contributed to teacher development programs, serving as a facilitator for the Continuous Professional Development (CPD) of Primary School Teachers (PSTs) through the Provincial Institute of Teacher Education (PITE) in KPK. His role as a part-time researcher at the Department of Computer Science and IT at the University of Malakand further underscores his involvement in academic research. Earlier in his career, he worked as a Secondary School Teacher at the Elementary and Secondary Education Department, KPK. His experiences reflect a blend of teaching, research, and educational development.

Research Interest

Mr. Naeem Ullah’s research interests primarily focus on cybersecurity, particularly in the context of emerging technologies such as vehicle-to-vehicle (V2V) communication. His PhD research investigates cybersecurity challenges and proposes mitigation models for securing V2V communication systems from a software engineering perspective. This area of research is highly relevant due to the increasing integration of connected vehicles and the need for secure communication protocols to protect sensitive data. Additionally, Mr. Ullah is interested in software engineering, with a particular emphasis on improving software development processes for small software companies in Pakistan, as demonstrated in his Master’s thesis. He has also contributed to the field of cybersecurity culture through his work on a Multivocal Literature Review (MLR) protocol, which identifies cybersecurity challenges and best practices in V2V communication. His research endeavors aim to address critical issues in both cybersecurity and software engineering, contributing to the development of safer, more efficient technologies.

Award and Honor

Mr. Naeem Ullah has received notable recognition for his academic and professional achievements. In 2022, he presented his Multivocal Literature Review (MLR) Protocol at the 2nd Annual International Workshop on Software Engineering (WSE-2022), organized by the Software Engineering Research Group at the University of Malakand. This presentation, focused on Cybersecurity Culture, showcased his expertise and contribution to the field of cybersecurity. Additionally, Mr. Ullah earned the prestigious Best Teacher Award from the Director of Elementary and Secondary Education, KPK, Pakistan, in 2018. This recognition highlights his excellence in teaching and his commitment to fostering the growth and development of his students. These awards and honors reflect Mr. Ullah’s dedication to advancing both his academic research and educational practices, demonstrating his commitment to the fields of computer science and cybersecurity while contributing positively to the educational community.

Conclusion

Naeem Ullah is a promising candidate for the Best Researcher Award, with a solid academic record, a focused and impactful research topic, and a commitment to both education and professional development. His strengths lie in his dedication to advancing cybersecurity research in emerging technologies like vehicle-to-vehicle communication and his capacity for leadership in educational initiatives. To further enhance his candidacy, Naeem could focus on increasing his research output, expanding his research scope, and engaging more in international collaborations to elevate the impact of his work.

Publications Top Noted

  • Title: Solutions to Cybersecurity Challenges in Secure Vehicle-to-Vehicle Communications: A Multivocal Literature Review
    Authors: Naeem Ullah, S.U. Khan, M. Niazi, A.A. Khan, J.A. Nasir
    Journal: Information and Software Technology
    Year: 2025
    Volume: 179
    Article ID: 107639
    Citations: 0
  • Title: Challenges and Their Practices in Adoption of Hybrid Cloud Computing: An Analytical Hierarchy Approach
    Authors: S.U. Khan, H.U. Khan, Naeem Ullah, R.A. Khan
    Journal: Security and Communication Networks
    Year: 2021
    Article ID: 1024139
    Citations: 2
  • Title: Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review
    Authors: S. Nazir, Y. Ali, Naeem Ullah, I. García-Magariño
    Journal: Wireless Communications and Mobile Computing
    Year: 2019
    Article ID: 5931315
    Citations: 138
  • Title: Practices for Clients in the Adoption of Hybrid Cloud
    Authors: S.U. Khan, Naeem Ullah
    Journal: Proceedings of the Pakistan Academy of Sciences: Part A
    Year: 2017
    Volume: 54(1A)
    Pages: 13–32
    Citations: 3

Hossein Nematzadeh | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Dr. Hossein Nematzadeh | Computer Science | Best Researcher Award

Assist Prof at Universidad de Malaga, Spain

Dr. Hossein Nematzadeh is an accomplished researcher and academic with a Ph.D. in Computer Science from the University of Technology, Malaysia. He is currently an Assistant Professor at the Modern College of Business and Science in Oman, with prior experience as a researcher at Universidad de Málaga, Spain, and an assistant professor at Islamic Azad University, Iran. His research interests span Data Science, Artificial Intelligence, Cryptography, and Software Engineering, with a particular focus on explainable AI, feature selection, evolutionary algorithms, and image encryption. Dr. Nematzadeh has published extensively in high-impact journals, contributing to advancements in AI and machine learning. He is also an experienced educator, having taught a wide array of computer science courses at various academic levels. With expertise in technologies like Python, MATLAB, and AWS, he is committed to both advancing research and mentoring the next generation of computer scientists.

Professional Profile 

Education

Dr. Hossein Nematzadeh has a strong academic foundation in Computer Science, having completed his Ph.D. at the University of Technology, Malaysia in 2014. Prior to his doctoral studies, he earned his Master’s degree from the same institution in 2009, further solidifying his expertise in the field. Dr. Nematzadeh also holds a Bachelor’s degree from Mazandaran University of Science and Technology, obtained in 2007. His educational journey reflects a deep commitment to the study of computer science, particularly in areas such as Artificial Intelligence, Data Science, and Cryptography. Throughout his academic career, he has gained a robust understanding of both theoretical and practical aspects of the field, which has informed his subsequent research and teaching. This solid educational background, combined with his ongoing research contributions, enables him to be a leader in his academic and professional endeavors.

Professional Experience

Dr. Hossein Nematzadeh has extensive professional experience in academia and research. He is currently serving as an Assistant Professor at the Modern College of Business and Science in Oman, where he teaches and supervises students in the field of Computer Science. Prior to this role, he was a researcher at Universidad de Málaga in Spain from 2021 to 2024, contributing to several high-impact research projects in Artificial Intelligence and Data Science. From 2012 to 2021, he served as an Assistant Professor at Islamic Azad University in Iran, where he taught various computer science courses and engaged in research activities. Throughout his career, Dr. Nematzadeh has built a reputation as both an educator and a researcher, publishing extensively in leading journals and presenting his work in international forums. His expertise spans across Data Science, Artificial Intelligence, and Cryptography, making him a prominent figure in these fields.

Research Interest

Dr. Hossein Nematzadeh’s research interests lie at the intersection of Data Science, Artificial Intelligence, Cryptography, and Software Engineering. He is particularly focused on developing advanced techniques in explainable AI, feature selection, and noise detection, with an emphasis on making AI models more interpretable and reliable. His work in evolutionary algorithms and fuzzy logic explores ways to optimize decision-making processes and improve system performance. Dr. Nematzadeh is also passionate about cryptography, specifically in areas such as image encryption, which contributes to enhancing data security in digital environments. Additionally, he has a strong interest in software engineering, with research dedicated to verification and validation processes, as well as the application of Petri nets to model and analyze complex systems. His research aims to push the boundaries of AI and machine learning, providing solutions to both theoretical and practical challenges in these rapidly evolving fields.

Award and Honor

Dr. Hossein Nematzadeh has earned recognition for his contributions to research and academia throughout his career. He has received several honors for his work in the fields of Data Science, Artificial Intelligence, and Cryptography, particularly for his research on explainable AI and feature selection methods. Dr. Nematzadeh’s scholarly impact is reflected in his publications in prestigious journals such as Engineering Applications of Artificial Intelligence and Knowledge-Based Systems. His work has been widely cited, demonstrating the influence of his research on the scientific community. In addition to his academic accomplishments, Dr. Nematzadeh has been actively involved in mentoring students and contributing to the advancement of his field through teaching and supervision. His dedication to fostering new talent in Computer Science and his continuous pursuit of research excellence have earned him respect within academic circles, making him a highly regarded figure in the global academic and research community.

Publications Top Noted

  • Title: Medical image encryption using a hybrid model of modified genetic algorithm and coupled map lattices
    Authors: H Nematzadeh, R Enayatifar, H Motameni, FG Guimarães, VN Coelho
    Year: 2018
    Cited by: 157
  • Title: A hybrid feature selection method based on information theory and binary butterfly optimization algorithm
    Authors: Z Sadeghian, E Akbari, H Nematzadeh
    Year: 2021
    Cited by: 116
  • Title: Heuristic filter feature selection methods for medical datasets
    Authors: M Alirezanejad, R Enayatifar, H Motameni, H Nematzadeh
    Year: 2020
    Cited by: 78
  • Title: Binary search tree image encryption with DNA
    Authors: H Nematzadeh, R Enayatifar, M Yadollahi, M Lee, G Jeong
    Year: 2020
    Cited by: 72
  • Title: Frequency based feature selection method using whale algorithm
    Authors: H Nematzadeh, R Enayatifar, M Mahmud, E Akbari
    Year: 2019
    Cited by: 66
  • Title: Emergency role-based access control (E-RBAC) and analysis of model specifications with alloy
    Authors: F Nazerian, H Motameni, H Nematzadeh
    Year: 2019
    Cited by: 52
  • Title: Predicting air pollution in Tehran: Genetic algorithm and back propagation neural network
    Authors: M Asghari, H Nematzadeh
    Year: 2016
    Cited by: 51
  • Title: A novel image security technique based on nucleic acid concepts
    Authors: M Yadollahi, R Enayatifar, H Nematzadeh, M Lee, JY Choi
    Year: 2020
    Cited by: 33
  • Title: Mapping to convert activity diagram in fuzzy UML to fuzzy petri net
    Authors: H Motameni, A Movaghar, I Daneshfar, H Nemat Zadeh, J Bakhshi
    Year: 2008
    Cited by: 30
  • Title: Automatic ensemble feature selection using fast non-dominated sorting
    Authors: S Abasabadi, H Nematzadeh, H Motameni, E Akbari
    Year: 2021
    Cited by: 28
  • Title: A mixed solution-based high agreement filtering method for class noise detection in binary classification
    Authors: M Samami, E Akbari, M Abdar, P Plawiak, H Nematzadeh, ME Basiri, …
    Year: 2020
    Cited by: 24
  • Title: Comparison of Decision Tree Methods in Classification of Researcher’s Cognitive Styles in Academic Environment
    Authors: ZN Balagatabi, R Ibrahim, HN Balagatabi
    Year: 2015
    Cited by: 24

Khyati Bhupta | Medicinal Chemistry | Best Researcher Award

Published on by Global Scholar Awards

Mrs. Khyati Bhupta | Medicinal Chemistry | Best Researcher Award

Assistant Professor at Dr Subhash University, India

Khyati Bhupta is a highly motivated and accomplished professor specializing in the field of pharmacy. She is dedicated to both teaching and research, with a passion for fostering student development using modern teaching methods and advanced pedagogy. Her work is defined by her dedication to innovation and academic excellence. Her experience and skills, particularly in the pharmaceutical sector, make her a valuable contributor to both academia and the industry.

Professional profile

Education 📚

Khyati holds a PhD in Pharmacy, which she earned in May 2013 from Dr. Subhash University, Gujarat. Prior to her PhD, she completed her Master’s in Pharmacy with a specialization in Quality Assurance from Gujarat Technological University in 2009, and her Bachelor’s in Pharmacy from Sardar Patel University in 2007. Her academic journey reflects a consistent focus on pharmaceutical sciences, with an emphasis on quality and research.

Professional Experience🎓

Over the years, Khyati has built extensive experience as a professor in pharmacy, contributing significantly to both teaching and research. She is skilled in handling pharmaceutical instruments and software, which has been vital in her research and practical work. Her expertise in communication and documentation further enhances her teaching capabilities, making her an effective educator who fosters learning through modern approaches and methodologies.

Research Interest🎓

Khyati’s research primarily focuses on pharmaceutical sciences, with significant work on benzothiazole derivatives, exploring their potential as antidiabetic and antiviral agents. She has published multiple papers on these topics in renowned journals such as MDPI and the Annals of the Romanian Society for Cell Biology. Her work also involves method development for pharmaceutical analysis, including titrimetric methods and RP-HPLC method development for drug estimation, reflecting her deep engagement in pharmaceutical research and innovation.

Awards and Honors 🏆

Khyati has received several recognitions for her contributions to research. In August 2022, she was granted a patent from the Government of India, demonstrating her innovative contributions to pharmaceutical science. Additionally, she received a grant from the SSIP (Student Startup and Innovation Policy) under the Gujarat Government in October 2023 for her work on a startup project, highlighting her potential in translating research into practical applications.

Publications top noted📜

  • BENZOTHIAZOLE: AS AN ANTIDIABETIC AGENT
    • Authors: Khyati Bhupta
    • Journal: Annals of the Romanian Society for Cell Biology
    • Year: 2021
    • Citations: N/A 📊💊
  • BENZOTHIAZOLE MOIETY AND ITS DERIVATIVES AS ANTIVIRAL AGENTS
    • Authors: Khyati Bhupta
    • Journal: MDPI
    • Year: 2021
    • Citations: N/A 🦠🔬
  • Biological Screening and Structure Activity Relationship of Benzothiazole
    • Authors: Khyati Bhupta
    • Journal: Research Journal of Pharmacy and Technology
    • Year: 2022
    • Citations: N/A 🧪📈
  • Development of Titrimetric Method for Estimation of Furosemide Tablets by Using Mixed Co-Solvency Process
    • Authors: Khyati Bhupta
    • Journal: International Journal of Biology, Pharmacy and Allied Sciences
    • Year: 2022
    • Citations: N/A ⚖️💊
  • RP-HPLC Method Development and Validation for Simultaneous Estimation of Ranitidine Hydrochloride and Domperidone in Combination
    • Authors: Khyati Bhupta
    • Journal: International Journal of Pharmacy, Biology and Allied Science
    • Year: 2023
    • Citations: N/A 📊🔬

Prof Dr. Mehlika Dilek Altıntop | Medicinal Chemistry | Women Researcher Award

Published on by Global Scholar Awards

Prof Dr. Mehlika Dilek Altıntop | Medicinal Chemistry | Women Researcher Award

Prof Dr. Anadolu University, Turkey

Dr. Mehlika Dilek Altıntop is a prominent Professor in Pharmaceutical Chemistry at Anadolu University. Her academic journey includes a Bachelor’s from Anadolu University, followed by a Master’s and Ph.D. in Pharmaceutical Chemistry from the same institution. She has served in various academic roles, including Research Assistant, Assistant Professor, and currently as a Professor. Her administrative roles include serving as Associate Director and Quality Coordinator at Anadolu University. Dr. Altıntop has received numerous awards for her research, including the Outstanding Woman Researcher Award and multiple Article Performance Awards. She is actively involved in editorial and guest editing roles in prestigious scientific journals and has supervised numerous master’s and doctoral dissertations in her field.

Professional profile

Scopus

Education 📚

Primary School: İkieylül Elementary School (1991-1996)Secondary School – High School: Eskişehir Anatolian High School (1996-2003)Undergraduate: Anadolu University, Faculty of Pharmacy (2003-2007)Master’s Degree (with Thesis): Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical Chemistry (2007-2009)Doctoral Degree: Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical Chemistry (2009-2012)Languages: English (Excellent)

Academic Titles 🎓

Research Assistant: Anadolu University, Faculty of Pharmacy (2010-2012)Research Assistant Doctor: Anadolu University, Faculty of Pharmacy (2012-2014)Assistant Professor Doctor: Anadolu University, Faculty of Pharmacy (2014-2015)Associate Professor Doctor: Anadolu University, Faculty of Pharmacy (2015-2020)Professor Doctor: Anadolu University, Faculty of Pharmacy (2020-Present)Administrative Roles 🏛️Erasmus/Farabi/Mevlana Assistant Coordinator: Anadolu University Faculty of Pharmacy (2013-2014)Associate Director: Anadolu University Graduate School of Health Sciences (2014-2017, 2023)Quality Coordinator: Anadolu University Graduate School of Health Sciences (2022-2023)

Awards and Honors 🏆

Anadolu University Faculty of Pharmacy Championship Award (2007)The Scientific and Technological Research Council of Turkey Graduate Scholarship (2007-2009)Anadolu University Science and Technology Encouragement Award (2014)Anadolu University Gold & Platinum Article Performance Awards (2015)Outstanding Reviewer, European Journal of Medicinal Chemistry (2016)Turkish Pharmacists’ Association Academy of Pharmacy Encouragement Award (2019)ISIF’21 Silver Medal for “Targeted Novel Triazolothiadiazine Derivatives for The Treatment of Lung Cancer” (2021)Award of Outstanding Woman Researcher in Pharmaceutical Chemistry, VIWA 2021

Publication📜

 

Design, Synthesis, and In Vivo Evaluation of a New Series of Indole-Chalcone Hybrids as Analgesic and Anti-Inflammatory Agents
Authors: Baramaki, I., Altıntop, M.D., Arslan, R., Hasan, A., Bektaş Türkmen, N.
Journal: ACS Omega, 2024, 9(10), pp. 12175–12183

Design, Synthesis, and Evaluation of a New Series of 2-Pyrazolines as Potential Antileukemic Agents
Authors: Altıntop, M.D., Cantürk, Z., Özdemir, A.
Journal: ACS Omega, 2023, 8(45), pp. 42867–42877

Design, Synthesis, and Evaluation of a New Series of Hydrazones as Small-Molecule Akt Inhibitors for NSCLC Therapy
Authors: Erdönmez, B., Altıntop, M.D., Akalın Çiftçi, G., Özdemir, A., Ece, A.
Journal: ACS Omega, 2023, 8(22), pp. 20056–20065

A New Series of Hydrazones as Small-Molecule Aldose Reductase Inhibitors
Authors: Altıntop, M.D., Demir, Y., Türkeş, C., Beydemir, Ş., Özdemir, A.
Journal: Archiv der Pharmazie, 2023, 356(4), 2200570

A New Series of Thiazole-Hydrazone Hybrids for Akt-Targeted Therapy of Non-Small Cell Lung Cancer
Authors: Orujova, T., Ece, A., Akalın Çiftçi, G., Özdemir, A., Altıntop, M.D.
Journal: Drug Development Research, 2023, 84(2), pp. 185–199

Synthesis, In Silico and In Vitro Evaluation of New 3,5-Disubstituted-1,2,4-Oxadiazole Derivatives as Carbonic Anhydrase Inhibitors and Cytotoxic Agents
Authors: Kucukoglu, K., Faydali, N., Bul, D., Ozturk, B., Guzel, I.
Journal: Journal of Molecular Structure, 2023, 1276, 134699

Discovery of Small Molecule COX-1 and Akt Inhibitors as Anti-NSCLC Agents Endowed with Anti-Inflammatory Action
Authors: Altıntop, M.D., Akalın Çiftçi, G., Yılmaz Savaş, N., Alataş, Ö., Özdemir, A.
Journal: International Journal of Molecular Sciences, 2023, 24(3), 2648

Microwave-Assisted Synthesis of a Series of 4,5-Dihydro-1H-Pyrazoles Endowed with Selective COX-1 Inhibitory Potency
Authors: Altıntop, M.D., Temel, H.E., Özdemir, A.
Journal: Journal of the Serbian Chemical Society, 2023, 88(4), pp. 355–365

Design, Synthesis, and Biological Evaluation of a New Series of Arylidene Indanones as Small Molecules for Targeted Therapy of Non-Small Cell Lung Carcinoma and Prostate Cancer
Authors: Altıntop, M.D., Özdemir, A., Temel, H.E., Kaplancıklı, Z.A., Akalın Çiftçi, G.
Journal: European Journal of Medicinal Chemistry, 2022, 244, 114851

A New Series of Thiosemicarbazone-Based Anti-Inflammatory Agents Exerting Their Action Through Cyclooxygenase Inhibition
Authors: Altıntop, M.D., Sever, B., Akalın Çiftçi, G., Alataş, Ö., Özdemir, A.
Journal: Archiv der Pharmazie, 2022, 355(9), 2200136

Ahmet Özdemir | Medicinal Chemistry | Best Researcher Award

Published on by Global Scholar Awards

Prof Dr. Ahmet Özdemir | Medicinal Chemistry | Best Researcher Award

Prof Dr. Anadolu University, Turkey

Prof Dr. Ahmet Özdemir is a Professor of Pharmaceutical Chemistry at Anadolu University, holding several prestigious academic titles and administrative roles. With a strong educational foundation in pharmacy and pharmaceutical chemistry, they have supervised both master’s and doctoral theses. Their research has garnered numerous awards, including multiple Article Performance Awards and an ISIF’21 Silver Medal for their invention targeting lung cancer treatment. Dr. [Your Name] has authored significant research on synthesizing bioactive compounds, reflecting their expertise in pharmaceutical chemistry and dedication to advancing medicinal science. They are proficient in English and have an extensive international research profile, including ORCID and Scopus Author IDs.

Professional profile

Scopus

Orcid

Education 🎓

Primary School: Salihli Cumhuriyet Elementary School (1978-1983)Secondary School: Salihli 50. Yıl Secondary School (1983-1986)High School: Salihli High School (1986-1989)Undergraduate: Anadolu University, Faculty of Pharmacy (1990-1994)Master’s Degree (with Thesis): Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical Chemistry (1995-1996)Thesis Title: “The studies on the synthesis, structure elucidations and determination of physicochemical parameters of some 2-substituted-1H-phenantro[9,10-d]imidazole compounds”Supervisor: Prof. Dr. İlhan Işıkdağ, 02.09.1996Doctorate Degree: Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical Chemistry (1996-2004)Thesis Title: “Synthesis of some 1-[(N,N-disubstituted-thiocarbonylthio)acetyl]-3-(2-thienyl)-5-aryl-2-pyrazoline derivatives and investigation of their antifungal, antibacterial activities”Supervisor: Prof. Dr. Gülhan Turan, 10.05.2004Foreign Languages: English (Intermediate)

Academic Titles 🏅

Research Assistant: Anadolu University, Faculty of Pharmacy (1997-2004)Research Assistant Doctor: Anadolu University, Faculty of Pharmacy (2004-2005)Lecturer: Anadolu University, Faculty of Pharmacy (2005-2007)Assistant Professor Doctor: Anadolu University, Faculty of Pharmacy (2007-2010)Associate Professor Doctor: Anadolu University, Faculty of Pharmacy (2010-2015)Professor Doctor: Anadolu University, Faculty of Pharmacy (2015-present)

Administrative Tasks 🗂️

Associate Director: Anadolu University Yunus Emre Vocational School (2011-2014)Vice Academic Director: Anadolu University Open Education Faculty, Department of Health Administration (2015-present)

Awards 🏆

Anadolu University Article Performance Award (2014)Anadolu University Gold Article Performance Award (2015)Anadolu University Platinum Article Performance Award (2015)Anadolu University Article Performance Award (2016, 2017, 2018, 2020)Anadolu University Academic Success Award (2019)ISIF’21 Silver Medal: Invention titled “Targeted Novel Triazolothiadiazine Derivatives for The Treatment of Lung Cancer” (2021)Right Holder: Anadolu UniversityInventors: Assoc. Prof. Dr. Belgin Sever, Prof. Dr. Mehlika Dilek Altintop, Prof. Dr. Ahmet Ozdemir, Prof. Dr. Gülşen Akalın Çiftçi

Supervised Master Dissertations 🎓

Supervisor: Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical ChemistryStudent: Sevtem GökbulutDissertation Title: “Synthesis of new 5-chloro-6-methoxy-2-[4-(substituted)benzylidene]-2,3-dihydro-1H-inden-1-one derivatives and investigation of their biological effects”Date: 13/01/2017

Supervised Doctorate Dissertations 🎓

Supervisor: Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical ChemistryStudent: Muhammed KarabacakDissertation Title: “The Synthesis of New Pyrazoline Derivatives and The Investigation of Their Biological Activities”Date: 15/08/2016

Publication📜

Design, Synthesis, and In Vivo Evaluation of a New Series of Indole-Chalcone Hybrids as Analgesic and Anti-Inflammatory Agents

Baramaki, I., Altıntop, M.D., Arslan, R., Hasan, A., Bektaş Türkmen, N.
ACS Omega, 2024, 9(10), pp. 12175–12183

 

Design, Synthesis, and Evaluation of a New Series of 2-Pyrazolines as Potential Antileukemic Agents

Altıntop, M.D., Cantürk, Z., Özdemir, A.
ACS Omega, 2023, 8(45), pp. 42867–42877

 

Design, Synthesis, and Evaluation of a New Series of Hydrazones as Small-Molecule Akt Inhibitors for NSCLC Therapy

Erdönmez, B., Altıntop, M.D., Akalın Çiftçi, G., Özdemir, A., Ece, A.
ACS Omega, 2023, 8(22), pp. 20056–20065

 

A New Series of Hydrazones as Small-Molecule Aldose Reductase Inhibitors

Altıntop, M.D., Demir, Y., Türkeş, C., Beydemir, Ş., Özdemir, A.
Archiv der Pharmazie, 2023, 356(4), 2200570

 

A New Series of Thiazole-Hydrazone Hybrids for Akt-Targeted Therapy of Non-Small Cell Lung Cancer

Orujova, T., Ece, A., Akalın Çiftçi, G., Özdemir, A., Altıntop, M.D.
Drug Development Research, 2023, 84(2), pp. 185–199

 

Discovery of Small Molecule COX-1 and Akt Inhibitors as Anti-NSCLC Agents Endowed with Anti-Inflammatory Action

Altıntop, M.D., Akalın Çiftçi, G., Yılmaz Savaş, N., Alataş, Ö., Özdemir, A.
International Journal of Molecular Sciences, 2023, 24(3), 2648

 

Microwave-Assisted Synthesis of a Series of 4,5-Dihydro-1H-Pyrazoles Endowed with Selective COX-1 Inhibitory Potency

Altıntop, M.D., Temel, H.E., Özdemir, A.
Journal of the Serbian Chemical Society, 2023, 88(4), pp. 355–365