Pratik Nag | Statistics | Best Researcher Award

Posted on by Academic achievements

Mr. Pratik Nag | Statistics | Best Researcher Award

Mr. Pratik Nag | Statistics – Researcher at University of Wollongong, Australia

Dr. Pratik Nag is an accomplished researcher specializing in computational statistics, spatial data analysis, and machine learning applications. With a strong academic background and a passion for data-driven solutions, he has significantly contributed to the field of large-scale spatial statistics. His work has been widely recognized through prestigious publications and awards, making him a distinguished figure in his domain.

Profile:

Orcid | Scopus

Education:

Dr. Nag has an extensive academic background in statistics and data science. He earned his Ph.D. in Statistics from King Abdullah University of Science and Technology (KAUST), where he worked under the guidance of Dr. Ying Sun. Prior to that, he completed his Master’s degree in Quality Management Science from the Indian Statistical Institute and his Bachelor’s degree in Statistics from the University of Calcutta. His educational journey has equipped him with a robust foundation in statistical modeling and computational techniques.

Experience:

Dr. Nag is currently serving as a Research Fellow in Computational Statistics at the University of Wollongong, Australia. Previously, he has worked as a Graduate Teaching Assistant at KAUST, where he contributed to the instruction of advanced statistics courses. Before his doctoral studies, he gained industry experience as a Data Science Specialist at General Electric Healthcare, where he applied statistical methodologies to solve complex data problems in the healthcare sector.

Research Interests:

Dr. Nag’s research focuses on developing innovative statistical methods for large-scale spatial and spatio-temporal data analysis. His expertise includes DeepKriging, spatial covariance estimation using convolutional neural networks, and the application of Fourier Neural Operators for space-time forecasting. His interdisciplinary work bridges statistics, machine learning, and environmental data science, providing novel solutions for real-world challenges.

Awards:

Dr. Nag’s outstanding contributions to research have been recognized with several prestigious awards, including:

  • 🏆 Al-Kindi Student Research Award (2024) – Awarded by KAUST for excellence in statistical research.
  • 🏅 Winner of KAUST Competition on Spatial Statistics for Large Datasets (2023) – Achieved top positions in subcompetitions 1b and 2a.
  • 🎓 CEMSE Dean’s List Award (2022) – Recognized for academic excellence at KAUST.
  • 🏅 Winner of KAUST Competition on Spatial Statistics for Large Datasets (2022) – Secured top rankings in subcompetitions 2a and 2b.

Publications:

Dr. Nag has authored several high-impact publications in renowned journals. Some of his key contributions include:

  • 📄 Bivariate DeepKriging for Computationally Efficient Spatial Interpolation of Large-scale Wind Fields – Technometrics (2025) | Cited by 12 articles
  • 📄 Efficient Large-scale Nonstationary Spatial Covariance Function Estimation using Convolutional Neural Networks – Journal of Computational and Graphical Statistics (2024) | Cited by 18 articles
  • 📄 Exploring the Efficacy of Statistical and Deep Learning Methods for Large Spatial Datasets: A Case Study – JABES (2024) | Cited by 9 articles
  • 📄 Spatio-temporal DeepKriging for Interpolation and Probabilistic Forecasting – Spatial Statistics (2023) | Cited by 15 articles
  • 📄 The Second Competition on Spatial Statistics for Large Datasets – Journal of Data Science (2022) | Cited by 10 articles
  • 📄 Reshaping Geostatistical Modeling and Prediction for Extreme-scale Environmental Applications – SC22 Conference (2022) | Cited by 20 articles

Conclusion:

Dr. Pratik Nag’s remarkable contributions to computational statistics and spatial data analysis make him a strong contender for the Best Researcher Award. His innovative research, strong publication record, and recognized achievements underscore his excellence in the field. While he continues to push the boundaries of statistical science, expanding his impact through industry collaborations and research leadership will further enhance his influence. Given his significant contributions and future potential, Dr. Nag is highly deserving of this award.

Dr. Yuting Ye – Statistics – Best Researcher Award

Posted on by Academic achievements

Dr. Yuting Ye - Statistics - Best Researcher Award

Southern University of Science and Technology -China

Professional Profiles

Early Academic Pursuits

Yuting Ye's academic journey commenced with a strong foundation in Mathematical Sciences at Tsinghua University, where she excelled as the top student in the Division of Probability and Statistics. Her undergraduate education laid the groundwork for her future pursuits in biostatistics and data science.

Professional Endeavors

After completing her bachelor's degree, Yuting pursued advanced studies at UC Berkeley, where she obtained both her master's and doctoral degrees in Biostatistics. Under the guidance of esteemed advisers Peter J. Bickel and Haiyan Huang, she delved into various aspects of statistical theory and computation, fostering a deep understanding of the field.

Contributions and Research Focus On Statistics

Yuting's research interests span across machine learning, statistics, and computational biology. She has made significant contributions to the theory of nonconvex learning, graph neural networks, and multi-label classification within the realm of machine learning. Additionally, her expertise extends to stats, particularly in areas such as multiple hypothesis testing, Bayesian modeling, and non-parametric stats. Moreover, her work in computational biology has addressed critical issues in pharmacogenomics, bioinformatics, and disease diagnosis, showcasing her interdisciplinary approach to problem-solving.

Accolades and Recognition In Statistics

Yuting's dedication to academic excellence has been recognized through various honors and awards. Notably, she was the recipient of prestigious fellowships such as the Genentech Fellowship Award and the Mayhew & Helen Derryberry Fellowship, acknowledging her outstanding contributions to the field of biostats. Furthermore, her academic prowess earned her the National Scholarship and the Zheng ZongCheng Scholarship during her undergraduate years at Tsinghua University.

Impact and Influence In Statistics

Yuting's research and contributions have left a significant impact on the fields of statistics and data science. Her innovative work in machine learning algorithms and statistical methodologies has advanced the frontier of knowledge, offering new insights and tools for solving complex real-world problems. Moreover, her interdisciplinary approach has facilitated collaborations across diverse domains, fostering a broader exchange of ideas and methodologies.

stats: The science of collecting, analyzing, interpreting, and presenting data to make informed decisions. It encompasses various methodologies, including probability theory, hypothesis testing, and regression analysis, applied across diverse fields such as economics, sociology, and healthcare. stats plays a pivotal role in understanding patterns, trends, and uncertainties, driving evidence-based decision-making and informing policies for societal advancement

Legacy and Future Contributions To Statistics

As an Assistant Professor in Statistics and Data Science at SUSTech, Yuting is poised to continue her trajectory of academic excellence and innovation. Her role as an educator and mentor will undoubtedly inspire the next generation of researchers, instilling in them the same passion and rigor that defines her own work. Furthermore, her ongoing research endeavors promise to push the boundaries of knowledge further, addressing pressing challenges in machine learning, stats, and computational biology.

In conclusion, Yuting Ye's journey from a distinguished undergraduate at Tsinghua University to an accomplished researcher and educator reflects her unwavering commitment to excellence in academia. Her diverse contributions across multiple disciplines attest to her versatility and ingenuity, establishing her as a prominent figure in the fields of statistics and data science. As she continues to pursue her academic and professional endeavors, Yuting's legacy is sure to leave a lasting impact on the advancement of knowledge and the development of innovative solutions to complex problems.

Notable Publications

Towards Robust Off-Policy Learning for Runtime Uncertainty 2022

Bipartite graph-based approach for clustering of cell lines by gene expression-drug response associations 2021

UNDERSTANDING THE ROLE OF IMPORTANCE WEIGHTING FOR DEEP LEARNING 2021

The existence of maximum likelihood estimate in high-dimensional binary response generalized linear models 2020