Pratik Nag | Statistics | Best Researcher Award

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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.

Mr. Akhilesh Kumar | Prediction Award | Best Researcher Award

Posted on by Academic achievements

Mr. Akhilesh Kumar | Prediction Award | Best Researcher Award

Mr. Akhilesh Kumar, Banaras Hindu University, India

Akhilesh Kumar is a dedicated Research Scholar at Banaras Hindu University (BHU) in Varanasi, Uttar Pradesh, India. He holds a Bachelor of Computer Applications (BCA), a Master of Computer Applications (MCA), and a Master of Technology (M.Tech) in Computer Science and Engineering. Currently pursuing his PhD in the Department of Computer Science, Akhilesh focuses on innovative approaches to emotion detection and classification using machine learning and deep learning techniques. His research contributions include developing frameworks for emotion recognition from physiological signals and optimizing deep learning models for EEG analysis. With a growing citation index and active engagement in the academic community, Akhilesh is committed to advancing the field of artificial intelligence.

Professional Profile:

Google Scholar

Suitability Summary for Best Researcher Award: Akhilesh Kumar:

Akhilesh Kumar, Research Scholar, Banaras Hindu University, Varanasi, India. Akhilesh Kumar is a dedicated research scholar with a robust academic background, holding degrees in BCA, MCA, and M.Tech in Computer Science. Currently pursuing his PhD, his research focuses on machine learning, deep learning, and feature engineering, particularly in emotion detection and classification. He has completed nine research projects, published three journals, and contributed significantly to innovative frameworks for emotion recognition using physiological signals.

Education:

  • Bachelor of Computer Applications (BCA)
    • Institution: [Institution Name]
    • Year of Completion: [Year]
  • Master of Computer Applications (MCA)
    • Institution: [Institution Name]
    • Year of Completion: [Year]
  • Master of Technology (M.Tech) in Computer Science and Engineering
    • Institution: [Institution Name]
    • Year of Completion: [Year]
  • PhD in Computer Science
    • Institution: Banaras Hindu University, Varanasi, Uttar Pradesh, India
    • Current Status: Ongoing

Work Experience:

  • Research Scholar
    • Institution: Banaras Hindu University, Varanasi, Uttar Pradesh, India
    • Duration: [Start Date] – Present
    • Responsibilities: Conducting research in machine learning, deep learning, and feature engineering, focusing on emotion detection and classification.

Publication top Notes:

Analysis of machine learning algorithms for facial expression recognition

Cited: 9

Nutrient composition, phytochemical profile and antioxidant properties of Morus nigra: A Review

Cited:7

Human sentiment analysis on social media through naïve bayes classifier

Cited:4

Evaluation of surface reflectance retrieval over diverse surface types using SREM algorithm in varied aerosol conditions for coarse to medium resolution data from multiple …

Cited:3

Machine learning approaches for cardiac disease prediction

Cited:2

Mohammed Bouasabah | Stochastic Processes | Best Researcher Award

Posted on by Academic achievements

Prof Dr. Mohammed Bouasabah | Stochastic Processes | Best Researcher Award 

Professor | Ibn Tofail University | Morocco

Short Biography ✨

Mohammed Bouasabah is an accomplished academic and researcher specializing in mathematical modeling, financial analytics, and applied computing. Currently serving as a Maître de Conférences Habilité at the École Nationale de Commerce et de Gestion de Kénitra, he has made significant contributions to the fields of finance and mathematics through both his research and teaching. His academic career is marked by a deep engagement with stochastic modeling, particularly in the context of financial markets, which he integrates with his expertise in mathematical analysis and computing. His journey from an engineering student to a leading academic figure highlights his commitment to advancing knowledge in these complex areas and his passion for fostering the next generation of scholars in the field.

Profile

Scopus

Education 🎓

Mohammed Bouasabah’s educational background is distinguished by a series of achievements that underscore his expertise and dedication to the field of mathematical and computational sciences. He earned his Doctorate in Mathematical Analysis from the École Nationale de Commerce et de Gestion de Kénitra between 2012 and 2016, with his thesis focusing on the stochastic modeling of exchange rates within the framework of asset-liability management. His work explored the EUR/MAD and USD/MAD exchange rates, contributing valuable insights into their behavior and prediction. Prior to this, Bouasabah completed an Engineering Degree in Computer Science and Telecommunications at the Institut National des Postes et Télécommunications in Rabat from 2007 to 2010. His strong performance in preparatory classes for engineering schools, where he was the major of his promotion, laid a solid foundation for his advanced studies. He began his academic journey with a Baccalauréat in Technical Sciences from Lycée Technique Ibn Sina in Kénitra in 2005, where he achieved a commendable mention of “Bien.”

Experience 🏛️

Mohammed Bouasabah’s professional experience spans over a decade, reflecting his expertise and versatility in both teaching and research. Since 2022, he has held the position of Maître de Conférences Habilité at the École Nationale de Commerce et de Gestion de Kénitra. In this role, he leads research projects and delivers advanced courses in mathematics and computing, contributing to the academic and professional development of students and researchers alike. From 2018 to 2022, he served as an Assistant Professor at the same institution, where he focused on teaching and developing curricula related to finance and stochastic processes. His tenure as a State Engineer in Computer Science from 2010 to 2018 involved not only teaching various courses but also managing the training room for financial markets. His role extended to providing additional training and support in the use of financial tools and methodologies, demonstrating his commitment to both education and practical application in the financial sector.

Research Interests 🔍

Mohammed Bouasabah’s research interests are deeply rooted in the intersection of mathematical modeling and financial analysis. His primary focus lies in stochastic modeling, where he examines the behavior of financial variables and develops predictive models to assess their future behavior. This includes extensive work on the stochastic modeling of exchange rates and financial indices, aiming to improve the accuracy of predictions and the management of financial risks. Bouasabah’s research often explores the application of machine learning techniques to financial data, investigating how these modern methods can enhance traditional models and provide more robust forecasts. His work is driven by a desire to bridge theoretical models with practical applications, particularly in the context of financial markets where precision and reliability are crucial.

Awards 🏆

Throughout his career, Mohammed Bouasabah has received recognition for his contributions to academia and research. His work has been published in prestigious journals such as the International Journal of Innovation and Applied Studies and Frontiers in Applied Mathematics and Statistics. His research has not only advanced the understanding of stochastic modeling but also earned him accolades in various international conferences. His presentations on topics like the predictive accuracy of financial models and the impact of COVID-19 on exchange rates have been well-received, highlighting his role as a thought leader in the field.

Publications 📚

Mohammed Bouasabah has an extensive publication record that showcases his research contributions and impact on the field. Some of his notable publications include: