laiba Sultan Dar | Time series analysis | Best Researcher Award

Ms. laiba Sultan Dar | Time series analysis | Best Researcher Award 

Phd Student at Abdul wali khan university | Pakistan

Ms. Laiba Sultan Dar is a dedicated researcher and Ph.D. scholar at Abdul Wali Khan University, specializing in time series analysis and decomposition techniques. Her academic journey is marked by a strong foundation in applied mathematics and data analytics, enabling her to contribute effectively to statistical modeling, forecasting, and computational research. She has developed expertise in identifying patterns and trends within large datasets, applying modern analytical frameworks to address complex problems in areas such as economics, climate studies, and system optimization. Her research integrates both theoretical and empirical approaches, focusing on improving the precision and interpretability of time-dependent models. Through her doctoral studies, she has actively engaged in institutional research projects and contributed to scholarly publications in recognized international journals, including those indexed by Scopus and ScienceDirect. Her work demonstrates a balance between mathematical rigor and practical application, particularly in designing adaptive models for real-world data forecasting. In addition to her academic pursuits, Ms. Laiba Sultan Dar has shown growing involvement in research collaborations and interdisciplinary studies that bridge statistical science and technological innovation. Her ability to combine methodological sophistication with computational efficiency has made her research relevant to emerging domains such as artificial intelligence-driven data analysis and predictive modeling. She continuously enhances her research capabilities by incorporating advanced tools and techniques, fostering a deeper understanding of time series dynamics. With a citation index reflecting the recognition of her early scholarly efforts, she remains committed to producing impactful research that advances statistical methodologies and contributes to data-driven decision-making. Her intellectual curiosity and analytical acumen position her as a promising researcher in quantitative sciences. Ms. Laiba Sultan Dar’s long-term goal is to strengthen the integration of mathematical modeling with applied sciences, promoting innovation and scientific development in her field. Her commitment to excellence, collaborative mindset, and ongoing pursuit of research excellence make her a deserving candidate for recognition among emerging scholars in data analytics and statistical research.

Featured Publications:

  • Dar, L., Akmal, A., Naseem, M. A., & Khan, K. U. D. (2011). Impact of stress on employees’ job performance in the business sector of Pakistan. Global Journal of Management and Business Research, 11(6), 1–4.

  • Dar, L. A., Naseem, M. A., Rehman, R. U., & Niazi, G. S. (2011). Corporate governance and firm performance: A case study of Pakistan oil and gas companies listed in Karachi Stock Exchange. Global Journal of Management and Business Research, 11(8), 1–10.

  • Malik, M., Wan, D., Dar, L., Akbar, A., & Naseem, M. A. (2014). The role of work-life balance in job satisfaction and job benefit. Journal of Applied Business Research (JABR), 30(5), 1627–1638.

  • Dar, L. S., Aamir, M., Khan, Z., Bilal, M., Boonsatit, N., & Jirawattanapanit, A. (2022). Forecasting crude oil price volatility by reconstructing EEMD components using ARIMA and FFNN models. Frontiers in Energy Research, 10, 991602.

  • Dar, L. S., Aamir, M., Bibi, S., & Bilal, M. (2025). A novel robust adaptive decomposition approach for solar energy potential using atmospheric transparency and UV radiation indicators. Journal of Radiation Research and Applied Sciences, 18(4), 101946.

  • Dar, L. S., Aamir, M., Hamraz, M., Faiz, N., Emam, W., & Tashkandy, Y. (2025). A robust adaptive signal decomposition method for enhanced mode extraction in financial time series. IEEE Access.

  • Saleem, Q., Dar, L., Shahid, M., & Rana, S. (2012). A quantitative analysis of the role of human resource development in economic growth in Pakistan. International Journal of Management Sciences and Business Research.

  • Bilal, M., Aamir, M., Abdullah, S., Mahmood, N., Khalil, U., Khalid, N., Ahmed, M., & Dar, L. (2022). Assessment of the COVID-19 pandemic’s impact on gasoline prices in Pakistan. VFAST Transactions on Mathematics, 10(2), 52–67.