Hamidou Tembine | Mathematics | Best Scholar Award

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Prof. Dr. Hamidou Tembine | Mathematics | Best Scholar Award

Professor of AI at UQTR, Canada

Prof. Dr. Hamidou Tembine is a senior research scientist at the King Abdullah University of Science and Technology (KAUST), specializing in applied mathematics and computational science. His research integrates uncertainty quantification, evolutionary game theory, and distributed learning to tackle complex problems in wireless communications and beyond. Tembine has made significant contributions to optimizing systems in uncertain environments, helping to advance the understanding of complex stochastic systems. He has been recognized for his innovative research, especially for its societal impact.

Professional Profile

Education

Prof. Tembine completed his higher education in mathematical engineering. He earned his Ph.D. from the University of Paris-Est, where he developed expertise in stochastic processes, optimization, and game theory. His academic background laid a strong foundation for his subsequent research in applied mathematics and computational science, where he focuses on areas including strategic learning, communication networks, and mathematical models of uncertainty​

Professional Experience

Throughout his career, Prof. Tembine has held significant academic and research positions. He is currently a senior research scientist at KAUST, where he contributes to the Stochastic Numerics Research Group (StochNum). He has also held roles in various academic institutions, developing expertise in communication systems, distributed networks, and optimization under uncertainty​

Research Interests

Prof. Tembine’s research interests are diverse, spanning from uncertainty quantification to evolutionary game theory. His work aims to solve real-world problems in areas like wireless communications, distributed strategic learning, and multi-agent systems. He focuses on optimizing communication networks by applying advanced mathematical models, offering insights into complex systems where uncertainty plays a central role​

Research Skills

Prof. Tembine is skilled in stochastic numerics, optimization techniques, and mathematical modeling. His expertise includes developing algorithms for uncertain systems, conducting theoretical research in game theory, and applying these models to real-world communication and network systems. He is proficient in a range of mathematical tools, from evolutionary strategies to advanced computational methods, enhancing the performance of complex systems under uncertain conditions​

Awards and Honors

Prof. Tembine has received numerous accolades for his groundbreaking research. One of his significant awards is the IEEE Communications Society (ComSoc) EMEA Outstanding Young Researcher Award, recognizing his contributions to society through his research in wireless communications and uncertainty quantification.

Conclusion

Prof. Dr. Tembine’s outstanding scholarly contributions and innovative research place him in strong contention for the Best Scholar Award. He has demonstrated a strong leadership role in advancing his field and has the potential to enhance the impact of his work by further expanding collaborations and promoting interdisciplinary initiatives.

Publications Top Notes

  • Game theory and learning for wireless networks: fundamentals and applications
    • Authors: S. Lasaulce, H. Tembine
    • Year: 2011
    • Citations: 349
  • Underwater wireless sensor networks: A survey on enabling technologies, localization protocols, and internet of underwater things
    • Authors: M. Jouhari, K. Ibrahimi, H. Tembine, J. Ben-Othman
    • Year: 2019
    • Citations: 308
  • Evolutionary games in wireless networks
    • Authors: H. Tembine, E. Altman, R. El-Azouzi, Y. Hayel
    • Year: 2009
    • Citations: 227
  • Electrical vehicles in the smart grid: A mean field game analysis
    • Authors: R. Couillet, S. M. Perlaza, H. Tembine, M. Debbah
    • Year: 2012
    • Citations: 203
  • Risk-sensitive mean-field games
    • Authors: H. Tembine, Q. Zhu, T. Başar
    • Year: 2013
    • Citations: 190
  • Distributed strategic learning for wireless engineers
    • Authors: H. Tembine
    • Year: 2018
    • Citations: 159
  • Game theory for wireless communications and networking
    • Authors: Y. Zhang, M. Guizani
    • Year: 2011
    • Citations: 155
  • Game dynamics and cost of learning in heterogeneous 4G networks
    • Authors: M. A. Khan, H. Tembine, A. V. Vasilakos
    • Year: 2011
    • Citations: 153
  • A stochastic maximum principle for risk-sensitive mean-field type control
    • Authors: B. Djehiche, H. Tembine, R. Tempone
    • Year: 2015
    • Citations: 122
  • Mean-field-type games in engineering
    • Authors: B. Djehiche, A. Tcheukam, H. Tembine
    • Year: 2017
    • Citations: 116

 

 

Okechukwu Obulezi | Mathematics | Best Researcher Award

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Dr. Okechukwu Obulezi | Mathematics | Best Researcher Award

Lecturer at Nnamdi Azikiwe University, Awka, Nigeria.

Okechukwu Jeremiah Obulezi, M.Sc., is a dedicated academic and researcher specializing in Probability Distributions and Machine Learning Models, with applications in survival analysis, competing risks, and acceptance sampling. He is currently a Lecturer I in the Statistics Department at Nnamdi Azikiwe University, Awka, Nigeria, where he has progressed through various academic roles since 2019. Obulezi holds a Master’s degree in Statistics from the same institution and is pursuing a Ph.D. in the same field. His research contributions include multiple published journal articles, focusing on topics such as statistical modeling and estimation techniques. He actively participates in academic leadership roles, serving as a reviewer for several reputable journals. Obulezi is also involved in student advising and departmental coordination, reflecting his commitment to both teaching and research excellence. His expertise positions him as a strong candidate for recognition in the Best Researcher Award.

Profile:

Education

Okechukwu Jeremiah Obulezi holds a robust educational background in statistics, anchored by his ongoing Ph.D. studies at Nnamdi Azikiwe University, where he focuses on advancing statistical methodologies. He earned his Master of Science (M.Sc) in Statistics from the same institution in 2016, with a thesis titled “BIC-Based Relative Influence Measure for Outlier Detection and Variable Selection in Regression Analysis.” Before this, he completed a Postgraduate Diploma (PGD) in Statistics at Nnamdi Azikiwe University in 2012, exploring “Discriminant Analysis of the Nigerian Fixed Assets.” His foundational education includes a Higher National Diploma (HND) in Statistics from Abia State Polytechnic, where he conducted a project on “Discriminant Analysis of the Performance of Secondary School Students.” Obulezi’s academic journey illustrates a consistent commitment to mastering statistical concepts and their practical applications, establishing a strong foundation for his research and teaching endeavors.

Professional Experiences 

Okechukwu Jeremiah Obulezi, M.Sc., is a dedicated academic with a robust professional background in statistics. Currently serving as a Lecturer I in the Statistics Department at Nnamdi Azikiwe University, Awka, Nigeria, he has progressed through various academic roles, including Lecturer II and Assistant Lecturer since 2019. Prior to this, he contributed to Abia State Polytechnic, where he served as a Senior Instructor and Instructor I in the Statistics Department from 2011 to 2019. Okechukwu’s responsibilities at Nnamdi Azikiwe University encompass teaching courses such as Biostatistics and Statistical Applications, along with mentoring undergraduate students as their level adviser. He actively participates in various academic committees, including the University Water Board Committee and the Faculty ICT Committee, showcasing his commitment to enhancing the academic environment. His continuous engagement in research and peer review further highlights his dedication to advancing statistical knowledge and education.

Research Interests

Okechukwu Jeremiah Obulezi, M.Sc, has a strong research focus on probability distributions and machine learning models, particularly their applications in survival analysis, competing risks, acceptance sampling, optimum sampling, and handling masked data and censoring schemes. His work is characterized by the integration of statistical theory and practical applications, aiming to enhance the reliability and efficiency of statistical models in real-world scenarios. With an emphasis on optimizing models for financial volatility and developing new statistical distributions, Obulezi’s research contributes significantly to the fields of statistics and data science. His expertise also extends to biostatistics and various statistical methodologies, positioning him as a key figure in advancing innovative approaches within the statistical community. Through his academic endeavors, he strives to address complex challenges in statistical modeling, ultimately benefiting both academic research and industry applications.

Research skills 

Okechukwu Jeremiah Obulezi possesses a robust skill set that enhances his research capabilities, particularly in the fields of statistics and machine learning. His expertise in probability distributions and their applications to survival analysis, competing risks, and acceptance sampling underscores his strong analytical skills. Obulezi has demonstrated proficiency in developing and optimizing statistical models, as evident in his published work on GARCH models for financial volatility. His experience in handling complex data sets, including those with missing data and censoring schemes, reflects his adeptness in statistical programming and data analysis. Furthermore, his involvement as a reviewer for various reputable journals showcases his critical thinking and attention to detail. Obulezi’s commitment to continuous learning is evidenced by his ongoing Ph.D. studies, further solidifying his position as a knowledgeable and skilled researcher in his field. Overall, his combination of technical skills and practical experience positions him well for impactful contributions to academic research.

Award And Recognition 

Okechukwu Jeremiah Obulezi has made significant contributions to the field of statistics, particularly in probability distributions and machine learning models, earning recognition for his innovative research and teaching excellence. His publications in esteemed journals, such as the Alexandria Engineering Journal and Scientific African, highlight his expertise in survival analysis and acceptance sampling. As a reviewer for several reputable academic journals, he actively contributes to the scientific community by ensuring the quality and integrity of published research. His commitment to academic leadership is evident through his roles as a seminar coordinator and undergraduate advisor at Nnamdi Azikiwe University, where he fosters student development. Furthermore, his ongoing Ph.D. studies and participation in various research committees exemplify his dedication to advancing statistical methodologies and applications, making him a commendable candidate for the Best Researcher Award.

Conclusion

Okechukwu Jeremiah Obulezi is a strong candidate for the Best Researcher Award due to his diverse research interests, extensive publication record, and dedication to teaching and academic leadership. While there are opportunities for growth, such as enhancing collaboration networks and securing research funding, his commitment to advancing statistical knowledge and mentoring future statisticians positions him as a valuable asset to the academic community. Awarding him this honor would recognize his contributions and motivate further excellence in his ongoing research endeavors.

Publication Top Notes
  1. Sine generalized family of distributions: Properties, estimation, simulations and applications
    • Authors: Oramulu, D.O., Alsadat, N., Kumar, A., Bahloul, M.M., Obulezi, O.J.
    • Year: 2024
    • Journal: Alexandria Engineering Journal
    • Volume/Issue/Page: 109, pp. 532–552
  2. A more flexible Lomax distribution: Characterization, estimation, group acceptance sampling plan and applications
    • Authors: Ekemezie, D.-F.N., Alghamdi, F.M., Aljohani, H.M., El-Raouf, M.M.A., Obulezi, O.J.
    • Year: 2024
    • Journal: Alexandria Engineering Journal
    • Volume/Issue/Page: 109, pp. 520–531
  3. Group acceptance sampling plan based on truncated life tests for Type-I heavy-tailed Rayleigh distribution
    • Authors: Nwankwo, M.P., Alsadat, N., Kumar, A., Bahloul, M.M., Obulezi, O.J.
    • Year: 2024
    • Journal: Heliyon
    • Volume/Issue/Page: 10(19), e38150
  4. Group acceptance sampling plans for type-I heavy-tailed exponential distribution based on truncated life tests
    • Authors: Nwankwo, B.C., Obiora-Ilouno, H.O., Almulhim, F.A., SidAhmed Mustafa, M., Obulezi, O.J.
    • Year: 2024
    • Journal: AIP Advances
    • Volume/Issue/Page: 14(3), 035310
  5. New Lifetime Distribution with Applications to Single Acceptance Sampling Plan and Scenarios of Increasing Hazard Rates
    • Authors: Chinedu, E.Q., Chukwudum, Q.C., Alsadat, N., Almetwally, E.M., Tolba, A.H.
    • Year: 2023
    • Journal: Symmetry
    • Volume/Issue/Page: 15(10), 1881
  6. A New Distribution for Modeling Data with Increasing Hazard Rate: A Case of COVID-19 Pandemic and Vinyl Chloride Data
    • Authors: Tolba, A.H., Onyekwere, C.K., El-Saeed, A.R., Alohali, H., Obulezi, O.J.
    • Year: 2023
    • Journal: Sustainability (Switzerland)
    • Volume/Issue/Page: 15(17), 12782