On 14 November 2025, the Department of “System Analysis and Mathematical Modeling” at the University of World Economy and Diplomacy hosted a scientific lecture delivered by scholar — Dr. Friday Zinzendoff Okwonu, Director of Information & Communication Technology and Lecturer at the Department of Mathematics, Delta State University, Abraka.

The presentation, titled “Computational Statistical Classifier Models for Solving High-Dimensional and Imbalanced Sample Size Problems,” was devoted to research in statistical modeling, machine learning, and high-dimensional classification. The speaker reviewed modern and classical classification methods, key limitations of existing models when working with high-dimensional and imbalanced data, and introduced several of his own methodological developments: Point Extraction Method, Benchmark Extraction Method (BEM), Multidimensional Bayes Classifier (MBC), Benchmark Evaluation Threshold (BETH), Mean-Variance Cloning Technique (MVCT), Threshold Mahalanobis Distance (TMD), Recursive Prediction Model (RP), and the Sycophants Curve Model (SCM). Special emphasis was placed on their practical advantages, robustness, and resistance to overfitting and outliers.

The seminar was attended by faculty members and researchers of the university. Among the invited guests was professor Olimjon Sharipov, Head of the Department of “Probability Theory and Mathematical Statistics” at the National University of Uzbekistan, who highly appreciated the relevance and scientific value of the research presented.

The parties noted a strong potential for further collaboration and discussed several avenues for joint work, including conducting academic and scientific seminars, preparing publications in international journals, developing joint projects in high-dimensional classification, machine learning, applied statistics, and big data analysis. Opportunities for participation in international conferences and preparation of inter-university grant proposals were also highlighted. The discussion demonstrated mutual interest in strengthening academic ties and fostering long-term scientific cooperation.