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