Joseph Odunayo Braimah | Mathematics | Young Scientist Award

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Dr. Joseph Odunayo Braimah | Mathematics
| Young Scientist Award

Ambrose Alli University, Ekpoma, Nigeria | Nigeria

Dr. Joseph Odunayo Braimah is a Nigerian statistician and academic whose expertise spans industrial statistics, reliability engineering, acceptance sampling, biostatistics, and applied statistical modelling. He holds a Ph.D. in Statistics from the University of Ilorin, Nigeria, where his doctoral research focused on evaluating the performance of truncated sampling plans. He also earned an M.Sc. and B.Sc. in Statistics from the same institution, along with a Postgraduate Diploma in Education from the National Teachers’ Institute, Kaduna. He currently serves as a Lecturer I in the Department of Mathematics and Statistics at Ambrose Alli University, Ekpoma, Nigeria. In 2024, he completed a competitive Postdoctoral Research Fellowship at the University of the Free State, South Africa, within the Department of Mathematical Statistics and Actuarial Sciences. His earlier academic roles at Al-Hikmah University and AROIF College of Advanced Studies reflect his strong contributions to teaching, curriculum development, and student mentorship. Dr. Braimah’s research covers statistical quality control, time-to-event modelling, medical statistics, epidemiology, time series analysis, and probability distributions. He has authored over 70 Scopus-indexed publications in reputable international journals and has collaborated extensively with scholars across Africa, including South Africa and Zimbabwe. His work advances understanding in public health analytics, product reliability, epidemic monitoring, and industrial process optimization. He has also developed multiple new probability distributions and innovative acceptance sampling schemes that support decision-making in quality management and risk assessment. His current project, the National Road Traffic Crash Risk Index (NRTCRi), employs spatial and multiscale statistical modelling to assess and predict road-traffic crash risks across Nigeria, contributing to improved national safety policies. He also holds the Google Data Analytics Professional Certificate and is a registered member of the Teachers’ Registration Council of Nigeria.

Featured Publications

Braimah, J. O., Sule, I., Bello, O. A., & Correa, F. M. (2025). A new modified extended generalized inverted exponential (NMEGIEx) distribution: A distribution for flexible and accurate data analysis. Contemporary Mathematics, 6. https://doi.org/10.37256/cm.6620257771

Braimah, J. O., & Correa, F. M. (2025). Reliability assessment of products with Weibull lifetimes: A two-sided linked lots deferred sampling plan (T-SLLDSP). Scientific African. https://doi.org/10.1016/j.sciaf.2025.e03039

Omaku, P. E., Braimah, J. O., & Correa, F. M. (2025). Bayesian accelerated failure time model for zero-inflated survival data with application to liver cirrhosis. Journal of Probability and Statistics, (Wiley), 1–12. https://doi.org/10.1155/jpas/5562074

Hemalatha K | Mathematics | Best Researcher Award

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Dr. Hemalatha K | Mathematics
| Best Researcher Award

Chennai Institute of Technology, Chennai | India

Dr. Hemalatha K is an accomplished mathematician and researcher specializing in theoretical seismology and wave propagation, currently serving as an Assistant Professor at the Center for Nonlinear Systems, Chennai Institute of Science and Technology, Tamil Nadu, India, since February 2025. She earned her Ph.D. in Mathematics (2024) from SRM Institute of Science and Technology, Chennai, with her thesis titled “Theoretical Study of Elastic Wave Propagation in Anisotropic and Functionally Graded Layered Media.” Her academic foundation includes an M.Sc. in Mathematics with outstanding distinction from Bishop Heber College, Trichy and a B.Sc. in Mathematics from Holy Cross College, Trichy. With over three years of research experience, Dr. Hemalatha has made significant contributions to the field through 17 peer-reviewed international journal publications, achieving a cumulative impact factor. Her recent research includes advanced studies on flexoelectric coupling, interfacial imperfections, and wave behavior in functionally graded and piezoflexoelectric materials, published in reputed Q1–Q3 indexed journals such as Mathematics (MDPI) and Journal of Mechanical Science and Technology (Springer). She holds professional identifiers including ORCID (0000-0002-9355-5747) reflecting her growing international academic recognition.

Profile: Google Scholar | Orcid

Featured Publication

1. Hemalatha, K., Kumar, S., & Prakash, D. (2023). Dispersion of Rayleigh wave in a functionally graded piezoelectric layer over elastic substrate. Forces in Mechanics, 10, 100171. https://doi.org/10.1016/j.finmec.2023.100171

2. Hemalatha, K., Kumar, S., & Kim, I. (2024). Study of SH-wave in a pre-stressed anisotropic magnetoelastic layer sandwich by heterogeneous semi-infinite media. Mathematics and Computers in Simulation, 222, 225–241. https://doi.org/10.1016/j.matcom.2024.01.015

3. Hemalatha, K., Kumar, S., & Akshaya, A. (2023). Rayleigh wave at imperfectly corrugated interface in FGPM structure. Coupled Systems Mechanics, 12(4), 337–364. https://doi.org/10.12989/csm.2023.12.4.337

4. Akshaya, A., Kumar, S., & Hemalatha, K. (2024). Behaviour of transverse wave at an imperfectly corrugated interface of a functionally graded structure. Physics of Wave Phenomena, 32(2), 117–134. https://doi.org/10.3103/S1541308X24020023

5. Hemalatha, K., & Kumar, S. (2024). Propagation of SH wave in a rotating functionally graded magneto-electro-elastic structure with imperfect interface. Journal of Vibration Engineering & Technologies, 12(7), 8383–8397. https://doi.org/10.1007/s42417-024-01007-5

6. Akshaya, A., Kumar, S., & Hemalatha, K. (2025). Propagation of shear horizontal wave at magneto-electro-elastic structure subjected to mechanically imperfect interface. Mechanics of Advanced Composite Structures, 12(1), 97–114. https://doi.org/10.22075/macs.2025.32784.1550

 

Raiha Imran | Mathematics | Academic Innovator Young Achiever Award

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Ms. Raiha Imran | Mathematics | Academic Innovator Young Achiever Award

Ms. Raiha Imran is an accomplished MPhil scholar in Mathematics at Riphah International University, Lahore, Pakistan, with a strong focus on fuzzy set theory and its applications in decision-making and mathematical modeling. Her research explores innovative solutions in the Fuzzy framework, including the development of Bonferroni mean operators for circular intuitionistic fuzzy sets and their applications in multi-criteria group decision-making. Raiha has published multiple high-quality research papers in reputed journals, addressing topics such as interval-valued intuitionistic fuzzy information, neutrosophic hesitant fuzzy aggregation operators, and distance measures for intuitionistic fuzzy hypersoft sets with practical applications like air quality evaluation. She has received 126 citations for her work, with an h-index of 5, reflecting her impactful contributions to the field. Raiha completed her Master’s degree in Mathematics from Riphah International University with a focus on fuzzy set theory and her Bachelor’s degree from Lahore Garrison University, where she also investigated multi-attribute group decision-making under cubic intuitionistic fuzzy soft environments. Her academic foundation is complemented by earlier schooling under the BISE Lahore and Faisalabad boards, achieving excellent grades throughout. Raiha’s research interests encompass generalizations of fuzzy sets, aggregation operators, similarity and distance measures, entropy measures, pattern recognition, cluster analysis, artificial intelligence, neuro computing, and data sciences. She has collaborated internationally with scholars from India, Serbia, Saudi Arabia, and Taiwan. Beyond research, Raiha has experience teaching mathematics and physics at both intermediate and matriculation levels, contributing to educational development. She has earned several certifications, participated in international conferences, and gained skills in data analysis and machine learning, reflecting her commitment to continuous learning. Raiha combines rigorous analytical expertise with a passion for advancing applied mathematics, aiming to develop innovative methodologies and decision-support tools that bridge theoretical research with practical applications, demonstrating dedication, intellectual curiosity, and a proactive approach to academic excellence.

Featured Publications

1. Imran, R., Ullah, K., Ali, Z., & Akram, M. (2024). A multi-criteria group decision-making approach for robot selection using interval-valued intuitionistic fuzzy information and Aczel-Alsina Bonferroni means. Spectrum of Decision Making and Applications, 1(1), 1–32.

2. Saqlain, M., Riaz, M., Imran, R., & Jarad, F. (2023). Distance and similarity measures of intuitionistic fuzzy hypersoft sets with application: Evaluation of air pollution in cities based on air quality index. Journal Name, Volume(Issue), pages.

3. Imran, R., Ullah, K., Ali, Z., & Akram, M. (2024). An approach to multi-attribute decision-making based on single-valued neutrosophic hesitant fuzzy Aczel-Alsina aggregation operator. Neutrosophic Systems with Applications, 22, 43–57.

4. Imran, R., Ullah, K., Ali, Z., Akram, M., & Senapati, T. (2023). The theory of prioritized Muirhead mean operators under the presence of complex single-valued neutrosophic values. Decision Analytics Journal, 7, 100214.

5. Imran, R., & Ullah, K. (2023). Circular intuitionistic fuzzy EDAS approach: A new paradigm for decision-making in the automotive industry sector. Spectrum of Engineering and Management Sciences, 3(1), 76–92

Issam Dawoud | Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Issam Dawoud | Mathematics | Best Researcher Award

Associate Professor of Statistics at Al-Aqsa University, Palestine, State of

Assoc. Prof. Dr. Issam Dawoud is an accomplished academic and researcher in the field of statistics, currently serving as an Associate Professor at Al-Aqsa University, Palestine. He holds a Ph.D. in Statistics from Cukurova University, Turkey, and has received multiple honors throughout his academic career, including distinction with honors in his degrees. Dr. Dawoud’s research focuses on regression models, statistical modeling, time series analysis, and forecasting methods, with numerous publications in high-impact journals. His contributions include developing innovative estimators that address complex statistical challenges such as multicollinearity and autocorrelation. His work has earned international recognition, including Outstanding Article Awards for his research in applied mathematics and statistics. Dr. Dawoud is also a collaborative researcher, co-authoring papers with scholars from around the world. His expertise and impactful contributions to the field of statistics have established him as a leading figure in statistical research and methodology.

Professional Profile 

Education

Assoc. Prof. Dr. Issam Dawoud has a solid educational background in statistics, beginning with his undergraduate studies in Mathematics/Statistics at the Islamic University in Palestine, where he graduated with distinction in 2009. He then pursued a Master’s degree in Statistics at Al-Azhar University, Palestine, completing it in 2012 with distinction. Dr. Dawoud continued his academic journey at Cukurova University in Turkey, where he earned a Ph.D. in Statistics in 2016. His doctoral dissertation focused on “Predictions in Linear Models,” and he graduated with honors in both his Ph.D. proficiency and preparation courses. Dr. Dawoud also received a Turkish government scholarship for his Ph.D. studies, further highlighting his academic excellence. Throughout his education, he demonstrated exceptional performance, earning distinctions in various courses, including a Turkish language course, showcasing his dedication and commitment to advancing his knowledge in the field of statistics.

Professional Experience

Assoc. Prof. Dr. Issam Dawoud has built a distinguished professional career in the field of statistics. He currently serves as an Associate Professor of Statistics at Al-Aqsa University in Gaza, Palestine, where he has contributed significantly to both teaching and research. Dr. Dawoud has extensive experience in academic leadership, mentoring graduate students, and designing statistical courses that reflect his expertise in regression models, time series analysis, and forecasting methods. Before his current position, he completed his Ph.D. at Cukurova University, Turkey, and has since been involved in various research projects, publishing numerous articles in high-impact journals. He has collaborated internationally with scholars from various institutions, further strengthening his academic network. His professional work extends beyond academia, with a focus on applying statistical methodologies to real-world problems, particularly in multivariate analysis and statistical modeling. Dr. Dawoud’s contributions to the field have earned him several prestigious awards and recognitions.

Research Interest

Assoc. Prof. Dr. Issam Dawoud’s research interests lie primarily in the fields of regression models, statistical modeling, time series analysis, forecasting methods, multivariate statistical analysis, and mathematical statistics. He focuses on developing innovative statistical methodologies, particularly in the area of regression analysis, to address complex issues such as multicollinearity, autocorrelation, and outliers. Dr. Dawoud has made significant contributions to the development of new estimators and techniques, including the Dawoud-Kibria Estimator, which has practical applications in diverse areas such as data analysis and predictive modeling. His research also delves into improving the accuracy of forecasting models and statistical simulations. In addition to his theoretical work, Dr. Dawoud is dedicated to applying his findings to real-world problems, with the goal of advancing statistical methods in various domains. His work reflects a deep commitment to enhancing the understanding and application of statistical analysis across numerous disciplines.

Award and Honor

Assoc. Prof. Dr. Issam Dawoud has received numerous prestigious awards and honors throughout his academic career, reflecting his outstanding contributions to the field of statistics. He was honored with the Outstanding Article Award for his papers titled “Dawoud-Kibria Estimator for Beta Regression Model: Simulation and Application” and “Generalized Kibria-Lukman Estimator: Method, Simulation and Application,” both published in Frontiers in Applied Mathematics and Statistics in 2022. Dr. Dawoud’s academic excellence is further demonstrated by his distinction with honors in several of his academic programs, including the Ph.D. proficiency exam and preparatory courses at Cukurova University, Turkey, where he graduated with a perfect score. He was also awarded the Turkish government scholarship for his Ph.D. studies, underscoring his exceptional academic abilities. Additionally, Dr. Dawoud received a scholarship for excellent students during his undergraduate studies at the Islamic University in Palestine, further showcasing his early academic promise and dedication.

Conclusion

Dr. Issam Dawoud demonstrates exceptional research capabilities and accomplishments in statistics. His extensive publication record, consistent recognition through awards, and contributions to statistical theory and methodology make him a strong candidate for the Best Researcher Award. By expanding the visibility of his work and exploring emerging research areas, Dr. Dawoud could further enhance his impact on the global academic and research community. Based on his current achievements, he stands out as a deserving recipient of this prestigious award.

Publications Top Noted

  • Robust Dawoud–Kibria estimator for handling multicollinearity and outliers in the linear regression model
    Authors: I. Dawoud, M.R. Abonazel
    Year: 2021
    Citations: 53
  • A New Biased Estimator to Combat the Multicollinearity of the Gaussian Linear Regression Model
    Authors: I. Dawoud, B.M.G. Kibria
    Year: 2020
    Citations: 49
  • On the performance of the Poisson and the negative binomial ridge predictors
    Authors: S. Kaçıranlar, I. Dawoud
    Year: 2018
    Citations: 40
  • A new ridge-type estimator for the gamma regression model
    Authors: A.F. Lukman, I. Dawoud, B.M.G. Kibria, Z.Y. Algamal, B. Aladeitan
    Year: 2021
    Citations: 33
  • Dawoud–Kibria estimator for beta regression model: simulation and application
    Authors: M.R. Abonazel, I. Dawoud, F.A. Awwad, A.F. Lukman
    Year: 2022
    Citations: 28
  • Development of robust Özkale–Kaçiranlar and Yang–Chang estimators for regression models in the presence of multicollinearity and outliers
    Authors: F.A. Awwad, I. Dawoud, M.R. Abonazel
    Year: 2021
    Citations: 28
  • Developing robust ridge estimators for Poisson regression model
    Authors: M.R. Abonazel, I. Dawoud
    Year: 2022
    Citations: 25
  • Comparative study on forecasting accuracy among moving average models with simulation and PALTEL stock market data in Palestine
    Authors: S. Safi, I. Dawoud
    Year: 2013
    Citations: 18
  • A new biased regression estimator: Theory, simulation and application
    Authors: I. Dawoud, A.F. Lukman, A.R. Haadi
    Year: 2022
    Citations: 17
  • New Two-Parameter Estimators for the Logistic Regression Model with Multicollinearity
    Authors: F.A. Awwad, K.A. Odeniyi, I. Dawoud, Z. Yahya, M.R. Algamal, …
    Year: 2022
    Citations: 17
  • Generalized Kibria-Lukman Estimator: Method, Simulation, and Application
    Authors: I. Dawoud, M.R. Abonazel, F.A. Awwad
    Year: 2022
    Citations: 16
  • Modeling Palestinian COVID-19 cumulative confirmed cases: A comparative study
    Authors: I. Dawoud
    Year: 2020
    Citations: 16
  • New robust estimators for handling multicollinearity and outliers in the Poisson model: methods, simulation, and applications
    Authors: I. Dawoud, F.A. Awwad, E. Tag Eldin, M.R. Abonazel
    Year: 2022
    Citations: 12
  • The optimal extended balanced loss function estimators
    Authors: S. Kaçiranlar, I. Dawoud
    Year: 2018
    Citations: 12