On March 4, 2025, The Graduate School of Westminster International University in Tashkent (WIUT) conducted the Doctorate Admission Interviews.

Candidates who applied as Independent Researchers for the PhD and DSs programs were invited to participate in the next stage of the selection process following the successful evaluation of their applications. The shortlisted applicants were invited to present their proposed research projects related to Uzbekistan and the region. As part of the process, applicants delivered short presentations outlining their research objectives, methodology, and preliminary.

The interview stage is a key part of WIUT’s commitment to supporting high-quality, locally relevant research and building the next generation of scholars in Uzbekistan. Final decisions will be made following the interview stage, with successful candidates advancing to the formal admission process.

We are pleased to announce that WIUT Research Ethics Briefing successfully took place, offering valuable insights into the fundamental principles and best practices in research ethics. The seminar was designed to serve as an introduction for junior researchers and a refresher for seasoned academics, emphasizing the importance of ethical standards in contemporary research, particularly in the social sciences.

Speakers:

• Dr. Ikrom Rikhsiboev, Dean of Graduate School (Research)
• Dr. Viktoriya Levinskaya, Global Education Department

The speakers highlighted the critical role of research ethics in maintaining public trust and ensuring the integrity of the research process. Participants were encouraged to remain informed and prioritize ethical considerations throughout their research endeavors.

This seminar underlined WIUT's commitment to fostering a culture of ethical research and academic excellence.

On February 12, 2025, the seminar, titled “Improving Econometric and Statistical Bases for Credit Risk Assessment in Credit Institutions,” was presented by Olmas Isakov, a final-year PhD student in Econometrics and Statistics and an independent researcher.

Drawing from his ongoing doctoral research, the presenter explored one of the most critical challenges faced by credit institutions—credit risk assessment. His presentation highlighted the importance of adopting advanced econometric and machine learning techniques to evaluate and predict non-performing loans (NPLs), a key indicator of financial vulnerability in lending institutions.

Isakov introduced a dynamic panel data approach to identify the determinants of NPLs and presented a machine learning workflow designed to predict loan delinquency in microfinance institutions (MFIs). The workflow included the application of eight supervised machine learning methods: Logistic Regression, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Classification Tree, Random Forest, K-Nearest Neighbors, Extreme Gradient Boosting, and Neural Networks.

Participants gained valuable insights into how traditional statistical methods and cutting-edge machine learning tools can be integrated to improve credit risk models. The session concluded with an engaging discussion, where attendees explored the practical implications of the research and its potential applications in the financial sector.

After several discussions, his dissertation was recommended to proceed to the next stage of defense/VIVA according to Supreme Attestation committee requirements.

In line with ongoing reforms in higher education and the increasing demand, Westminster International University in Tashkent (WIUT) is pleased to announce the expansion of its Scientific Council.

The Scientific Council initially established in 2019 to provide a platform for candidates to defend dissertations in "Management" (08.00.13), it has now broadened its scope to include specialty "Econometrics & Statistics" (08.00.06).

This significant development was approved by the Supreme Attestation Commission under Ministry of Higher Education, Science and Innovation during its meeting on 25 December 2024. The Council’s extension allows candidates to defend their dissertations for PhD (Doctor of Philosophy) and DSc (Doctor of Science) degrees in both disciplines "Management" (08.00.13) and "Econometrics & Statistics" (08.00.06).