Syarifah Inayati is an academic researcher at Universitas Negeri Yogyakarta with expertise in statistics, mathematical finance, and optimization, and a scholarly record that demonstrates strong engagement with advanced quantitative modeling and applied statistical analysis. Her research primarily focuses on time series modeling, particularly Markov Switching Autoregressive (MSAR) and Bayesian time-varying parameter models, which she applies to dynamic economic forecasting and financial market analysis. Several of her studies address financial risk and investment analysis, including stock market contagion between Indonesia and the United States, portfolio analysis using Gaussian mixture distributions with expectation–maximization algorithms, and risk measurement through Value at Risk methods under Bayesian mixture frameworks. Beyond financial applications, she has made notable contributions to socio-economic and public policy research, such as forecasting BPJS health insurance beneficiaries using fuzzy time series methods and modeling the Human Development Index of Central Java using three-parameter gamma regression. Her work in optimization includes nonlinear multiobjective optimization problems solved through Pareto front and weighting approaches, demonstrating methodological depth and versatility. In addition to theoretical and applied research, Syarifah Inayati is actively involved in community service and capacity building, contributing to workshops and training programs on nonparametric analysis, factor analysis, logistic regression, and statistical methods for social sciences and education. With 39 citations, an h-index of 4, and consistent citation growth since 2020, her research reflects a balanced integration of rigorous statistical methodology, interdisciplinary collaboration, and practical relevance. Overall, her scholarly contributions strengthen the application of modern statistical and econometric techniques in finance, economics, public policy, and applied mathematics, while also supporting knowledge dissemination through educational and community-oriented initiatives.