Prof. Rafik Aguech | Probabilities | Best Researcher Award
Prof. Rafik Aguech | Professor | King Saud University | Saudi Arabia
Academic Background
Rafik Aguech holds advanced qualifications in mathematics with a specialization in probability and statistics, achieved through progressive academic training in leading institutions in France and Tunisia. His doctoral research focused on stochastic algorithms, supervised at a renowned probability laboratory. His scholarly journey includes a habilitation degree in mathematical sciences, along with earlier postgraduate and undergraduate qualifications in probability, fundamental mathematics, and applications. His academic credentials led to formal recognition for university-level teaching and research roles in both French and Tunisian systems. With a strong publication footprint, his citation record reflects consistent scholarly influence. Scopus lists over 51 citations with an h-index of 5 across 21 indexed documents, while Google Scholar reports more than one 125 citations with an h-index of 7 and an i10-index of three. These metrics underscore his sustained contributions to stochastic processes, urn models, and random structures.
Research Focus
His research centers on stochastic algorithms, urn models, random walks, fragmentation processes, branching structures, and probabilistic analysis in theoretical and applied contexts. His work bridges probability theory with computer science, algorithmic modeling, and combinatorics, offering mathematical insights with cross-disciplinary relevance.
Work Experience
He has served in academic and research capacities across institutions in Europe, North Africa, and the Middle East. His roles have progressively advanced from adjunct and assistant professor positions to associate professorship at a leading Gulf institution in mathematical sciences. He has delivered lectures, supervised research, and contributed to graduate and postgraduate education in probability, statistics, stochastic modeling, and advanced mathematical theory. His teaching portfolio spans foundational mathematics, applied probability, nonparametric statistics, and statistical theory for both undergraduate and graduate cohorts across several universities.
Key Contributions
He has authored and coauthored numerous works on random structures, stochastic tracking algorithms, urn models, and algorithmic probability. His pioneering contributions to the study of elephant random walks, generalized urn schemes, and recursive tree behavior form a significant body of work influencing both theoretical development and applied probability. His collaborative research has connected probability with computer systems theory, combinatorial models, and asymptotic behavior of algorithms.
Awards & Recognition
His research influence is acknowledged through sustained collaboration with leading mathematicians, invitations to international research institutes, and repeated participation as an invited speaker at global probability and algorithmic meetings.
Professional Roles & Memberships
He has played a pivotal role in research communities through involvement in international working groups, collaborations with French and Tunisian research teams, and membership in organizations bridging informatics and mathematics. He has also chaired and organized thematic schools, probability colloquia, and international conferences, contributing to academic exchange and institutional visibility.
Publication Profile
Scopus | ORCID | Google Scholar
Featured Publications
Aguech, R., Moulines, E., & Priouret, P. (2000). On a perturbation approach for the analysis of stochastic tracking algorithms. SIAM Journal on Control and Optimization, 39(3), 872–899.
Aguech, R. (2009). Limit theorems for random triangular urn schemes. Journal of Applied Probability, 46(3), 827–843.
Aguech, R., Lasmar, N., & Mahmoud, H. (2006). Limit distribution of distances in biased random tries. Journal of Applied Probability, 43(2), 377–390.
Aguech, R., Jedidi, W. (2019). New characterizations of completely monotone functions and Bernstein functions. Arab Journal of Mathematical Sciences, 25(1), 57–82.
Aguech, R., El Machkouri, M. (2024). Gaussian fluctuations for the elephant random walk with gradually increasing memory. Journal of Physics A: Mathematical and Theoretical, 57(6), 065203.
Impact Statement / Vision
His academic path reflects a commitment to advancing probability theory through rigorous analysis and collaborative inquiry. By linking abstract stochastic models with algorithmic structures, his research enhances understanding of random processes in computation, information sciences, and applied mathematics. He aims to continue driving innovation in probabilistic modeling and mentoring emerging scholars in mathematical research.