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.

Ms. Kumi Rani – Machine Learning – Best Researcher Award

Posted on by Academic achievements

Ms. Kumi Rani - Machine Learning - Best Researcher Award

Indian Institute of Technology BHU, Varanasi - India

Professional Profiles

Early Academic Pursuits:

Kumi Rani's academic journey began with a passion for Computer Science and Engineering at the prestigious Indian Institute of Technology (IIT) BHU, Varanasi. During her early academic pursuits, she immersed herself in a challenging curriculum, laying the foundation for a robust understanding of computational sciences. The rigorous coursework at IIT BHU introduced her to a diverse range of subjects, including Artificial Intelligence, Neural Networks, Computer Graphics, and Mathematical Modeling.

Professional Endeavors:

Post her academic journey, Kumi Rani transitioned into the realm of academia. She served as an Assistant Professor at Sharda University, Greater Noida, where she contributed to the Computer Science and Engineering department. Subsequently, she expanded her academic footprint to include the Mathematics department at Shree DKV Science and Arts College, Jamnagar. This versatility showcased her ability to navigate and contribute to different facets of academia.

Contributions and Research Focus:

Kumi Rani's contributions in academia extend to her technical skills and her research focus. Proficient in operating systems such as Windows Vista/XP/Linux and mathematical software like Matlab R2009a, she demonstrated a command over tools crucial for computational research. Her programming expertise in C, Python, C++, and Matlab reflected her commitment to staying at the forefront of technological advancements. At the heart of her research focus lies an intersection of Machine Learning, Deep Learning, and Applied Mathematics. Her Ph.D. thesis, "Handcrafted and Deep Learning Techniques for Classification of Medical and Hyperspectral Images," underscores her commitment to addressing critical challenges in medical image analysis. By amalgamating traditional handcrafted methods with cutting-edge deep learning architectures, she aimed to elevate the precision and efficiency of medical image diagnostics. Her M.Tech thesis, "A Study of Clustering Algorithms in Fuzzy Scenario," delves into the realms of unsupervised learning and statistical data analysis. The introduction of the Kernel Intuitionistic Fuzzy c-Means algorithm reflects her innovative approach to clustering, emphasizing improved performance and robustness.

Accolades and Recognition:

Kumi Rani's academic prowess has earned her notable accolades and recognition. She secured an impressive All India Rank of 199 in the National Eligibility Test (NET) for Lectureship, a joint initiative by the Council of Scientific and Industrial Research (CSIR) and University Grants Commission (UGC). Additionally, she secured an All India Rank of 83 in the Graduate Aptitude Test in Engineering (GATE), a testament to her excellence in the field. Her pursuit of continuous learning is evident through her completion of professional development programs and courses on platforms like Coursera and Oracle Academy. This commitment to staying abreast of industry-relevant skills showcases her dedication to both personal and professional growth.

Impact and Influence:

In her professional roles, Kumi Rani has not only shared her knowledge through teaching but has also left an impact on real-world projects. Her involvement in projects at ATC Labs, including the design of a real-time broadcast communicator on the Android platform, reflects her ability to apply computational skills to practical scenarios. Her guidance on B.Tech projects further extends her influence to shaping the next generation of computational professionals.

Legacy and Future Contributions:

As Kumi Rani continues her journey, her legacy at the Indian Institute of Technology BHU, Varanasi, is marked by her early academic pursuits, versatile contributions in academia, and impactful research focus. Her commitment to education, demonstrated through the diverse courses she has taught, and her ongoing research pursuits are likely to define her future contributions. In the interdisciplinary field of computational sciences and mathematics, Kumi Rani's legacy is shaped by a dedication to excellence and a vision for the continual advancement of knowledge and application.

Notable Publications:

Classification of wireless capsule endoscopy images for bleeding using deep features fusion 2022-11-16

Cyclic learning rate based HybridSN model for hyperspectral image classification 2022-09

Automated bleeding detection in wireless capsule endoscopy images based on sparse coding 2021-08