Muhammad Asif Munir | Machine Learning | Best Researcher Award

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Mr. Muhammad Asif Munir | Machine Learning | Best Researcher Award

Assistant Professor| Swedish College of Engineering and Technology | Pakistan

Dr. Muhammad Asif Munir is an accomplished researcher and academic in the field of Electrical Engineering, currently serving as an Assistant Professor at the Swedish College of Engineering and Technology, District Rahim Yar Khan, Punjab, Pakistan, and pursuing his Ph.D. at The Islamia University of Bahawalpur. His research primarily focuses on machine learning and deep learning applications in biomedical image analysis, with a particular emphasis on addressing the challenges of small and imbalanced radiomics datasets. With six peer-reviewed publications indexed in SCI and Scopus journals, including IEEE Access and Future Internet (MDPI), and a growing citation record of 56 citations (h-index: 4, i10-index: 2), Dr. Munir has demonstrated consistent academic excellence and research innovation. His notable contribution, the GSRA-KL framework, introduces a novel sparse regularized autoencoder–based methodology that significantly enhances synthetic data generation and improves the predictive accuracy of gene mutation analysis in lung cancer radiomics. This work not only contributes to the evolution of precision oncology but also exemplifies the integration of AI-driven data synthesis with clinical applications. His ongoing research explores the incorporation of explainable artificial intelligence (XAI) into radiomics for more interpretable, transparent, and reliable predictive modeling, fostering clinically explainable AI systems in healthcare. Dr. Munir’s interdisciplinary approach bridges data science, medical imaging, and clinical decision support, aiming to make AI tools both scientifically robust and ethically transparent. A member of professional organizations such as IEEE and IAENG, he remains actively engaged in promoting research collaboration and advancing the global discourse on intelligent healthcare systems. Through his scholarly contributions, Dr. Munir is significantly impacting the development of data-efficient, interpretable, and patient-centered AI frameworks, reinforcing the global transition toward smart healthcare technologies and next-generation precision medicine. His commitment to research excellence and translational impact continues to position him as a promising figure in the convergence of engineering and medical AI research.

Featured Publication

Aslam, M. A., Munir, M. A., & Cui, D. (2020). Noise removal from medical images using hybrid filters of technique. Journal of Physics: Conference Series, 1518(1), 012061.

Aslam, M. A., Xue, C., Wang, K., Chen, Y., Zhang, A., Cai, W., Ma, L., Yang, Y., Sun, X., & Munir, M. A. (2020). SVM based classification and prediction system for gastric cancer using dominant features of saliva. Nano Biomedicine and Engineering, 12(1), 1–13.

Munir, M. A., Aslam, M. A., Shafique, M., Ahmed, R., & Mehmood, Z. (2022). Deep stacked sparse autoencoders – A breast cancer classifier. Mehran University Research Journal of Engineering and Technology, 41(1), 41–52.

Aslam, M. A., Munir, M. A., Ahmad, R., Samiullah, M., Hassan, N. M., & Mahnoor, S. (2022). Deep neural networks for prediction of cardiovascular diseases. Nano Biomedicine and Engineering, 14(1).

Munir, M. A., Shah, R. A., Ali, M., Laghari, A. A., Almadhor, A., & Gadekallu, T. R. (2024). Enhancing gene mutation prediction with sparse regularized autoencoders in lung cancer radiomics analysis. IEEE Access.

Dr. Muhammad Asif Munir’s research advances intelligent healthcare by integrating machine learning and explainable AI to enhance diagnostic accuracy and transparency in medical imaging. His innovations in radiomics and synthetic data generation foster data-efficient, interpretable, and globally applicable solutions that strengthen precision oncology and next-generation healthcare systems.

Hawazin Elani | Machine Learning | Best Researcher Award

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Dr. Hawazin Elani | Machine Learning | Best Researcher Award

Harvard University | United States

Dr. Hawazin W. Elani, Ph.D., is an accomplished scholar and academic leader whose research integrates dentistry, epidemiology, and health policy to advance oral health equity through data-driven, interdisciplinary approaches. She serves as an Associate Professor in the Department of Health Policy and Management at the Harvard T.H. Chan School of Public Health and in the Department of Oral Health Policy and Epidemiology at the Harvard School of Dental Medicine, with additional affiliations at the Harvard Data Science Initiative and the Kempner Institute for the Study of Natural and Artificial Intelligence. Dr. Elani earned her Ph.D. in Dental Sciences with a concentration in Epidemiology and Population Health and an M.Sc. from McGill University, as well as an MMSc in Oral Biology and a Clinical Certificate in Prosthodontics from Harvard. Her research explores health disparities, oral health policy, and the application of artificial intelligence and machine learning in predicting oral health outcomes. She has authored over 30 peer-reviewed publications in high-impact journals such as Health Services Research, JAMA Network Open, and Journal of Dental Research, with her work cited widely for shaping discussions on healthcare access and reform. As principal investigator on multiple NIH and foundation-funded projects, including R01 and K-series grants, she has led innovative studies assessing the effects of Medicaid expansion and socioeconomic factors on dental care utilization. Recognized with Harvard’s Young Mentor Award and Distinguished Junior Faculty Award in 2024, Dr. Elani also contributes to national and international committees, including the NIH, the National Academies of Sciences, and the Medicaid Policy Research Advisory Group. Through her leadership, global collaborations, and dedication to mentoring, she continues to advance the intersection of artificial intelligence, population health, and oral health policy, driving forward equitable and sustainable improvements in healthcare delivery worldwide.

Profiles: Scopus | ORCID
Featured Publication

lani, H. W., Kawachi, I., & Sommers, B. D. (2020). Changes in emergency department dental visits after Medicaid expansion. Health Services Research, 55(1), 76–84.

Elani, H. W., Simon, L., Ticku, S., Bain, P. A., Barrow, J., & Riedy, C. A. (2018). Does providing dental services reduce overall health care costs? A systematic review of the literature. Journal of the American Dental Association (1939), 149(6), 430–438.e10.

Elani, H. W., Starr, J. R., Da Silva, J. D., & Gallucci, G. O. (2018). Trends in dental implant use in the U.S., 1999–2016, and projections to 2026. Journal of Dental Research, 97(13), 1424–1430.

Gil, M. S., Ishikawa-Nagai, S., Elani, H. W., Da Silva, J. D., Kim, D. M., Tarnow, D., Schulze-Späte, U., Cleber, S., & Bittner, N. (2019). Comparison of the color appearance of peri-implant soft tissue with natural gingiva using anodized pink-neck implants and pink abutments: A prospective clinical trial. The International Journal of Oral & Maxillofacial Implants, 34(1), 168–175.

Gil, M. S., Ishikawa-Nagai, S., Elani, H. W., Da Silva, J. D., Kim, D. M., Tarnow, D., Schulze-Späte, U., & Bittner, N. (2017). A prospective clinical trial to assess the optical efficacy of pink neck implants and pink abutments on soft tissue esthetics. Journal of Esthetic and Restorative Dentistry, 29(3), 213–219.

Marco Capogni | Data Science | Best Researcher Award

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Prof. Dr. Marco Capogni | Data Science | Best Researcher Award

Researcher | ENEA – National Institute for Ionizing Radiation Metrology | Italy

Prof. Dr. Marco Capogni’s research focuses on the precise measurement and standardization of radionuclides, with a strong emphasis on ionizing radiation metrology and its applications in medicine, industry, and environmental monitoring. He has developed and maintained primary national standards for radioactivity, collaborating with international institutions such as the Bureau International des Poids et Mesures (BIPM) and contributing to interlaboratory comparisons to ensure global consistency in radionuclide measurements. His work includes the implementation of absolute measurement techniques and computational codes such as GEANT, MCNP, Penelope, and Fluka for both direct and indirect activity determination. Marco has been actively involved in projects producing medical radionuclides like Mo-99 and Cu-64, utilizing neutron activation and absolute or relative measurement systems, and has contributed to the development of innovative sources of fusion neutrons for radioisotope production under the Sorgentina-RF project. His expertise spans gamma spectrometry, liquid scintillation counting, and coincidence counting methods, and he has served as a member of international working groups including the International Committee for Radionuclide Metrology (ICRM) and the European Metrology Network for Radiation Protection (EURAMET). Marco has led and coordinated numerous European research projects funded by EMRP and EMPIR, focusing on robust production chains for medical radionuclides, radiological early warning networks, and metrology for decommissioning nuclear facilities. He has also contributed to the training of students at the master’s and doctoral levels in physics, engineering, and medical physics, supervising multiple theses on radionuclide metrology and measurement techniques. His work has resulted in significant publications, patents, and participation in international conferences, reflecting his leadership in metrological science and nuclear applications. Marco Capogni’s contributions demonstrate a blend of experimental expertise, computational proficiency, and collaborative engagement with international metrology and research networks, addressing challenges in nuclear measurement, radioprotection, and medical isotope production. He has achieved 1,882citations, authored 133 documents, and holds an h-index of 21.

Profiles: Scopus | ORCID
Featured Publication

Capogni, M., … (2024). Assessment of impurity production upon 14 MeV fusion neutron irradiation of both natural and isotopically enriched 100Mo samples. European Physical Journal Plus.
Citations: 1

Capogni, M., … (2024). Measurements of the absolute gamma-ray emission intensities from the decay of 166Ho. Applied Radiation and Isotopes.
Citations: 2

Capogni, M., … (2024). Future of 99Mo reactor-independent supply. Nature Reviews Physics.
Citations: 3

Capogni, M., … (2023). Analytical study of low energy proton interactions in the SORGENTINA’s fusion ion source-Part II: beam-gas: SORGENTINA ion beam interactions. European Physical Journal Plus.
Citations: 2

Capogni, M., … (2023). The international reference system for beta-particle emitting radionuclides: Validation through the pilot study CCRI(II)-P1.Co-60. Applied Radiation and Isotopes.
Citations: 5

Capogni, M., … (2023). The importance of uncertainty analysis and traceable measurements in routine quantitative 90Y-PET molecular radiotherapy: A multicenter experience. Pharmaceuticals.
Citations: 1

Capogni, M., … (2023). Experimental campaign on ordinary and baritic concrete samples for the SORGENTINA-RF plant: The SRF-bioshield tests. European Physical Journal Plus.
Citations: 3

Rana Ghazali | Data Science | Best Researcher Award

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Dr. Rana Ghazali | Data Science | Best Researcher Award

Researcher |McMaster University | Iran

Dr. Rana Ghazali focuses on advancing intelligent computing systems through the integration of machine learning, reinforcement learning, and large language models to optimize big data and distributed computing environments. Her work bridges the domains of cloud computing, Hadoop-based systems, and intelligent caching to enhance computational performance and resource utilization in large-scale data frameworks. She has contributed to innovative algorithms such as CLQLMRS and H-SVM-LRU for improving cache locality and intelligent cache replacement in MapReduce job scheduling, combining machine learning with distributed system optimization. Rana’s research also extends to the design and analysis of routing protocols in mobile ad hoc networks, leveraging bio-inspired algorithms such as the Ant Colony Optimization method to improve network efficiency. Her current exploration includes the application of reinforcement learning in scheduling and performance enhancement for distributed computing platforms, with additional attention to emerging paradigms like edge, fog, and serverless computing. As a researcher affiliated with the Resource Allocation and Stochastic Systems Lab at McMaster University, she contributes to cutting-edge discussions on adaptive data management, cyber and network security, and intelligent system design. Rana’s expertise further encompasses data analytics, large language models, and the intersection of artificial intelligence with real-world computing challenges. She has served as a reviewer for leading international journals including Elsevier and Wiley publications and has participated in academic collaborations that explore deep learning and resource optimization in distributed architectures. Her research endeavors consistently emphasize scalable, secure, and intelligent computational systems that advance the performance of modern data-intensive applications. Rana Ghazali has 13 citations, 2 documents, and an h-index of 2.

Profiles: Google Scholar | Scopus | ORCID
Featured Publication

Ghazali, R., Down, D. G. (2025). Smart data prefetching using KNN to improve Hadoop performance. EAI Endorsed Transactions on Scalable Information Systems, 12(3). Cited by 1

Ghazali, R., Adabi, S., Rezaee, A., Down, D. G., & Movaghar, A. (2023). Hadoop-oriented SVM-LRU (H-SVM-LRU): An intelligent cache replacement algorithm to improve MapReduce performance. arXiv preprint arXiv:2309.16471. Cited by 2

Ghazali, R., Adabi, S., Rezaee, A., Down, D. G., & Movaghar, A. (2022). CLQLMRS: Improving cache locality in MapReduce job scheduler using Q-learning. Journal of Cloud Computing, 9. Cited by 9

Ghazali, R., Adabi, S., Down, D. G., & Movaghar, A. (2021). A classification of Hadoop job schedulers based on performance optimization approaches. Cluster Computing, 24(4), 3381–3403. Cited by 11

Ghazali, R., Down, D. G. (2025). A systematic overview of caching mechanisms to improve Hadoop performance. Concurrency and Computation: Practice and Experience, 37(25–26), e70337.

Golnar Mazdayasna | Big Data | Best Researcher Award

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Prof. Dr. Golnar Mazdayasna | Big Data | Best Researcher Award

Professor at Department of English Literature and Language, Yazd University | Iran

Prof. Golnar Mazdayasna is a distinguished scholar in applied linguistics whose research has significantly influenced the fields of English for Specific and Academic Purposes (ESP/EAP) and language needs analysis. Through her innovative studies, she has advanced understanding of curriculum design, materials development, and effective language teaching methodologies. Her extensive teaching experience at Yazd University, coupled with her supervision of numerous M.A. and Ph.D. theses, reflects her commitment to shaping the next generation of researchers and educators. Prof. Mazdayasna’s publications in internationally recognized journals such as Frontiers in Psychology, Heliyon, and the Journal of Computer Assisted Learning demonstrate her strong global impact and scholarly visibility. Beyond research, she is actively engaged in academic leadership, professional associations, and collaborative projects that bridge theory and practice. Her contributions embody a balance of innovation, mentorship, and academic excellence, positioning her as an influential figure in applied linguistics with a lasting international reputation.

Professional Profile

Google Scholar 

Education

Prof. Golnar Mazdayasna holds a Ph.D. and M.A. in Teaching English as a Foreign Language (TEFL) from the University of Isfahan, Iran, and a B.A. in English Literature from the University of Bombay, India. She is a Professor of Applied Linguistics at Yazd University, where she has taught a wide range of courses across undergraduate, postgraduate, and doctoral programs, including English for Specific and Academic Purposes, Curriculum Development, Materials Preparation, Speaking and Listening, and Advanced Writing. With extensive supervisory experience, she has guided several doctoral dissertations and numerous master’s theses, contributing to the academic growth of her students. Her expertise lies in curriculum design, applied linguistics, academic supervision, and innovative teaching methodologies. Her research focuses on needs analysis, English for Academic Purposes, and advances in English language teaching, with publications in respected journals such as Heliyon, Frontiers in Psychology, and the Journal of Computer Assisted Learning. She has also been recognized by the British Council for her co-authored book chapter on English language teaching in Iran.

Experience

Prof. Golnar Mazdayasna holds a Ph.D. and M.A. in Teaching English as a Foreign Language (TEFL) from the University of Isfahan, Iran, and a B.A. in English Literature from the University of Bombay, India. She serves as a Professor of Applied Linguistics at Yazd University, where she has taught English for Specific and Academic Purposes, Curriculum Development, Materials Preparation, Speaking and Listening, and Advanced Writing. She has successfully supervised several Ph.D. dissertations and M.A. theses, contributing extensively to graduate research and academic development. Her expertise includes curriculum design, materials development, applied linguistics research, and fostering innovative approaches to English language education. With a research focus on needs analysis, English for Academic and Specific Purposes, and innovations in applied linguistics, she has published in leading journals such as Heliyon, Frontiers in Psychology, and the Journal of Computer Assisted Learning. Recognized internationally, she received a British Council award for her co-authored book chapter on English language teaching in Iran and is an active member of the Association of Language Awareness.

Skills and Expertise

Prof. Golnar Mazdayasna holds a Ph.D. and M.A. in Teaching English as a Foreign Language (TEFL) from the University of Isfahan, Iran, and a B.A. in English Literature from the University of Bombay, India. She serves as a Professor of Applied Linguistics at Yazd University, where she has taught English for Specific and Academic Purposes, Curriculum Development, Materials Preparation, Speaking and Listening, and Advanced Writing across undergraduate, postgraduate, and doctoral levels. She has supervised several Ph.D. dissertations and numerous M.A. theses, significantly contributing to graduate research. Her professional strengths include curriculum design, materials development, applied linguistics research, academic supervision, and fostering innovation in English language teaching. Her research primarily focuses on needs analysis, English for Academic and Specific Purposes, and advancements in applied linguistics. She has published widely in international journals including Heliyon, Frontiers in Psychology, and the Journal of Computer Assisted Learning. Recognized globally, she received a British Council award for her co-authored book chapter on English language teaching in Iran and remains an active member of the Association of Language Awareness.

Research Focus

Prof. Golnar Mazdayasna holds a Ph.D. and M.A. in Teaching English as a Foreign Language (TEFL) from the University of Isfahan, Iran, along with a B.A. in English Literature from the University of Bombay, India. She is a Professor of Applied Linguistics at Yazd University, where she has taught English for Specific and Academic Purposes, Curriculum Development, Materials Preparation, Speaking and Listening, and Advanced Writing at undergraduate, postgraduate, and doctoral levels. She has successfully supervised several Ph.D. dissertations and numerous M.A. theses, contributing significantly to graduate research and academic development. Her professional strengths include curriculum design, materials development, applied linguistics research, academic supervision, and the advancement of innovative approaches to English language education. Her research explores needs analysis, English for Academic and Specific Purposes, and innovations in language education. She has published in prestigious journals including Heliyon, Frontiers in Psychology, and the Journal of Computer Assisted Learning. She also received recognition from the British Council for a co-authored book chapter on English language teaching in Iran.

Awards and Honors

Prof. Golnar Mazdayasna holds a Ph.D. and M.A. in Teaching English as a Foreign Language (TEFL) from the University of Isfahan, Iran, and a B.A. in English Literature from the University of Bombay, India. She is a Professor of Applied Linguistics at Yazd University, where she has taught courses such as English for Specific and Academic Purposes, Curriculum Development, Materials Preparation, Speaking and Listening, and Advanced Writing. With extensive supervisory experience, she has guided several Ph.D. dissertations and numerous M.A. theses, playing a key role in graduate research and academic advancement. Her professional strengths include curriculum design, materials development, applied linguistics research, academic supervision, and fostering innovation in English language teaching. Her research explores needs analysis, English for Academic and Specific Purposes, and innovations in language education, with publications in respected journals including Heliyon, Frontiers in Psychology, and the Journal of Computer Assisted Learning. She received recognition from the British Council for a co-authored book chapter on English language teaching in Iran and is an active member of the Association of Language Awareness.

Publication

Title: Developing a profile of the ESP needs of Iranian students: The case of students of nursing and midwifery
Authors: G. Mazdayasna, M.H. Tahririan
Journal: Journal of English for Academic Purposes, 7 (4), 277–289
Citations: 272

Title: The impact of computer‐based instruction on the development of EFL learners’ writing skills
Authors: A. Zaini, G. Mazdayasna
Journal: Journal of Computer Assisted Learning, 31 (6), 516–528
Citations: 60

Title: The effect of computer assisted language learning on the development of EFL learners’ writing skills
Authors: A. Zaini, G. Mazdayasna
Journal: Procedia – Social and Behavioral Sciences, 98, 1975–1982
Citations: 58

Title: Dynamic assessment of morphological awareness in the EFL context
Authors: M. Hamavandi, M.J. Rezai, G. Mazdayasna
Journal: Cogent Education, 4 (1), 1324254
Citations: 38

Title: Objective assessment of oral presentations and EFL learners’ speaking development
Authors: G. Mazdayasna
Journal: Journal of Foreign Language Teaching and Translation Studies, 1 (1), 23–38
Citations: 33

Title: Impact of genre-based instruction on development of students’ letter writing skills: The case of students of textile engineering
Authors: N. Rashidi, G. Mazdayasna
Journal: Journal of Research in Applied Linguistics, 7 (2), 55–72
Citations: 18

Title: The effect of collaborative prewriting discussions on L2 writing development and learners’ identity construction
Authors: G. Mazdayasna, A. Zaini
Journal: Iranian Journal of Applied Linguistics (IJAL), 18 (2), 141–164
Citations: 16

Title: A triangulated study of target situation needs of Iranian undergraduate students of English language and literature
Authors: M. Noori, G. Mazdayasna
Journal: Procedia – Social and Behavioral Sciences, 98, 1374–1379
Citations: 13

Title: Examining the association of grit profiles with big five personality and achievement among Iranian foreign language learners
Authors: M. Khodaverdian Dehkordi, A.A. Jabbari, G. Mazdayasna
Journal: Frontiers in Psychology, 12, 801844
Citations: 12

Title: Investigating the effect of team-teaching approach on ESP students’ English proficiency; evidence from students’ attitudes
Authors: M. Besharati, G. Mazdayasna
Journal: International Journal of Applied Linguistics and English Literature, 6 (5), 41–50
Citations: 10

Title: Peer-review, teacher feedback and EFL learners’ writing development
Authors: G. Mazdayasna, M.H. Tahririan
Journal: Iranian Journal of Applied Linguistics (IJAL), 5 (1), 55–67
Citations: 10

Conclusion

Prof. Golnar Mazdayasna exemplifies the qualities of a Best Researcher Award recipient through her distinguished research, innovative contributions, and strong record of mentorship. Her work in applied linguistics, with a focus on ESP/EAP and needs analysis, has advanced both theoretical understanding and practical applications in language education. She has published extensively in high-impact international journals and received recognition for her scholarship from esteemed organizations such as the British Council. In addition to her research excellence, she has played a key role in supervising graduate students, fostering academic growth, and promoting innovation in English language teaching. While expanding interdisciplinary collaborations and enhancing her global academic networks could further strengthen her international visibility, her current profile already reflects a remarkable balance of research productivity, educational leadership, and scholarly influence. Prof. Mazdayasna’s contributions not only advance applied linguistics but also nurture future generations of researchers, making her a truly deserving candidate for this prestigious honor.