Sun Jong Kim | In Vitro Diagnostics | Science and Technology Pioneer Award

Posted on by Phenomenological Research Awards

Dr. Sun Jong Kim | In Vitro Diagnostics | Science and Technology Pioneer Award 

Researcher at BioFront | South Korea

Dr. Sun Jong Kim is a highly accomplished biotechnology and life sciences professional whose career reflects sustained contributions to in vitro diagnostics, stem cell science, biomolecular research, and translational biomedical innovation. Equipped with a strong academic foundation including bachelor’s, master’s, and doctoral studies in life sciences, Dr. Sun Jong Kim has developed deep expertise in cellular biology, developmental biology, and molecular mechanisms of pluripotency. His professional journey includes senior research and leadership roles across multiple biomedical organizations, where he has guided R&D programs involving the establishment and maintenance of pluripotent stem cell lines, large-scale microalgae production systems, medical device development, and regulatory preparation for diagnostic technologies. He has contributed to the development of human embryonic stem cell resources, in vitro differentiation platforms, and advanced diagnostic systems applied to areas such as oncology, COVID-19 rapid testing, and point-of-care technologies. His industrial leadership also includes oversight of product development pipelines, quality assurance systems, and multidisciplinary research operations, demonstrating an ability to translate scientific results into usable biomedical solutions that directly support clinical and research infrastructures. His research outputs include numerous scientific publications, national and international presentations, and patents in areas such as stem cell culturing techniques, photobioreactors, and biomaterial-based innovations. The measurable impact of his scholarly contribution is represented by 24 citations by 24 documents, 2 indexed documents, and an h-index of 2, reflecting ongoing engagement and recognition within the scientific community. Dr. Sun Jong Kim’s research interests encompass stem cell biology, human cell culture systems, the regulation of self-renewal and differentiation pathways, bioprocess design, clinical diagnostics, and biotechnology commercialization. His work has been supported by significant research grants and has contributed to advancements in both academic discovery and applied biomedical engineering. In addition to laboratory research, he has played a crucial role in the development, certification, and evaluation of diagnostic medical devices aligned with international regulatory standards and real-world clinical needs. Through his ongoing work at Biofront and other institutions, Dr. Sun Jong Kim continues to drive innovation in science and technology, contributing to advancements that support more accurate diagnostics, greater understanding of biological systems, and the modernization of biomedical tools used in healthcare and life science research.

Profile: Scopus

Featured Publications:

Kim, S. J.,(1999). Isolation of developmentally regulated novel genes based on sequence identity and gene expression patterns. Molecules and Cells, 9, 207–218.

Kim, S. J.,(2001). Ovarian expression of melatonin Mel(1) receptor mRNA during mouse development. Molecular Reproduction and Development, 59, 126–132.

Kim, S. J.,(2003). Isolation and culture of human embryonic stem-like cells from abnormal blastocysts. Korean Journal of Fertility and Sterility, 30, 293–301.

Kim, S. J.,(2003). Establishment and maintenance of human embryonic stem cells on STO, a permanently growing cell line. Biology of Reproduction, 69, 2007–2014.

Kim, S. J.,(2004). Establishment of embryonic germ cells from cultured human primordial germ cells and their differentiation into neuronal cells. Molecules and Cells, 17, 309–315.

Kim, S. J.,(2004). Recent advances in human embryonic stem cell research. Journal of the Korean Medical Association, 918–925.

Kim, S. J.,(2004). Effects of type IV collagen and laminin on the cryopreservation of human embryonic stem cells. Stem Cells, 22, 950–961.

Kim, S. J.,(2004). Available human feeder cells for the maintenance of human embryonic stem cells. Reproduction, 128, 727–735.

laiba Sultan Dar | Time series analysis | Best Researcher Award

Posted on by Phenomenological Research Awards

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.

Profile: Google Scholar

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.