Sagnik Mondal | Best Researcher Award-Award Winner 2023
Mr. Sagnik Mondal: Statistical Methodologies
Congratulations, Mr. Sagnik Mondal, on winning the Best Researcher Award for Statistical Methodologies at the International Research Awards on Fiber Reinforced Polymer! Your achievement is remarkable and a testament to your outstanding contributions. Well done!
Professional Profiles:
Early Academic Pursuits:
Sagnik Mondal embarked on a scholarly journey driven by a passion for statistics. Starting with a Bachelor's in Statistics from Asutosh College, University of Calcutta, and progressing to a Master's at Indian Institute of Technology Kanpur (IITK), his foundational education laid the groundwork for his illustrious career.
Professional Endeavors:
Pursuing a Ph.D. in Statistics at the King Abdullah University of Science and Technology (KAUST), Sagnik delved into sophisticated research realms, exploring Multivariate Analysis, Copula Models, and Non-Gaussian Random Fields. His association with esteemed professors and institutions further honed his expertise.
Contributions and Research Focus:
Sagnik's research journey is marked by groundbreaking contributions in statistical methodologies. His work on "Non-Gaussian Random Vectors and Fields" and publications like "A Nonstationary Factor Copula Model for Non-Gaussian Spatial Data" exemplify his innovative approaches to complex statistical models.
Accolades and Recognition:
Sagnik's exceptional academic prowess has been consistently acknowledged. Notably, his paper on "Parallel Approximations of the Tukey g-and-h Likelihoods" secured top honors at the International Parallel and Distributed Processing Symposium (IPDPS) 2022, ranking 1st out of 51 papers.
Impact and Influence:
His impactful research in spatial statistics and parallel computation has been published in prestigious journals and presented at renowned conferences like the Joint Statistical Meeting (JSM) and the International Indian Statistical Association Conference (IISA), leaving a lasting impression on the statistical community.
Legacy and Future Contributions:
Sagnik's legacy is characterized by his pioneering work in advancing statistical methodologies, particularly in dealing with non-Gaussian distributions and spatial statistics. His dedication to unraveling complexities in statistical modeling sets a high benchmark for future researchers. As he continues to explore uncharted territories in statistics, his innovative insights are poised to shape the future landscape of the field.
Notable Publications:
- Parallel Approximations of the Tukey g-and-h Likelihoods and Predictions for Non-Gaussian Geostatistics. Mondal, S., Abdulah, S., Ltaief, H., ...Genton, M.G., Keyes, D.E., Proceedings - 2022 IEEE 36th International Parallel and Distributed Processing Symposium, IPDPS 2022, 2022, pp. 379–389, (1)
- Tile low-rank approximations of non-Gaussian space and space-time Tukey g-and-h random field likelihoods and predictions on large-scale systems. Mondal, S., Abdulah, S., Ltaief, H., ...Genton, M.G., Keyes, D.E. Journal of Parallel and Distributed ComputingThis link is disabled., 2023, 180, 104715