Posted on 23/11/202423/11/2024 by sciencefather 78 / 100 Powered by Rank Math SEO Mr. Farooq ahmad | Forecasting | Best Researcher Award Mr. Farooq ahmad, Department Statistical Science, Pakistan Farooq Ahmad is a doctoral candidate in Statistical Sciences at the University of Padova, Italy, with a focus on forecasting hydropower using innovation diffusion models. His academic journey began at the University of Peshawar, where he earned his Bachelor’s and Master’s degrees in Statistics. With a strong background in teaching and applied statistics, Farooq has held lecturer positions at the University of Peshawar and the University of Malakand. He is particularly interested in innovation diffusion modeling, sports statistics, and machine learning, driven by a commitment to advancing statistical research and its applications. PROFILE Orcid Profile Educational Details Farooq Ahmad is a PhD student in Statistical Sciences at the University of Padova, Italy, where he has been studying since March 2022 under the supervision of Prof. Livio Finos and co-supervisor Prof. Mariangela Guidolin. His doctoral research focuses on “Forecasting Hydropower with Innovation Diffusion Models: A Cross-Country Analysis,” aiming for expected completion in March 2025. Farooq earned his Master’s degree in Sports Statistics from the University of Peshawar, Pakistan, in 2017, with a dissertation titled “Structural Equation Modeling for Evaluating the Performance of Test Match Winning Teams” and a final mark of 3.4/4.0. He completed his Bachelor’s degree in Statistics at the same university in 2013, presenting research on the effects of bowling combinations in test cricket. Professional Experience Farooq Ahmad began his teaching career as a Visiting Lecturer in the Department of Statistics at the University of Peshawar from 2014 to 2017. Subsequently, he joined the University of Malakand, Pakistan, as a Lecturer in the Department of Statistics, where he worked from September 2018 to January 2022. During his academic career, he has taught various courses in basic statistics, data processing, statistical computing, probability, and applied statistics, including practical skills in software like SPSS, Minitab, C++, and FORTRAN. Research Interests Farooq’s research spans multiple areas within applied and theoretical statistics, with a particular focus on innovation diffusion modeling, sports statistics, machine learning, time series modeling, and applied statistics. His current research investigates the potential of innovation diffusion models for hydropower forecasting, reflecting his interest in applying statistical methods to address real-world challenges. Top Notable Publications Forecasting Saudi Arabia’s Refined Petroleum Products: An In-depth Analysis of Time Series vs Machine Learning Models Authors: Not provided Year: 2024 Publication Date: November 21, 2024 Type: Preprint DOI: 10.20944/preprints202411.1557.v1 Source: Crossref Forecasting Hydropower with Innovation Diffusion Models: A Cross-Country Analysis Authors: Not provided Year: 2024 Publication Date: November 16, 2024 Type: Journal Article Journal: Forecasting DOI: 10.3390/forecast6040052 Source: Crossref Modeling the Future of Hydroelectric Power: A Cross-Country Study Authors: Not provided Year: 2024 Publication Date: July 19, 2024 Type: Conference Paper DOI: 10.3390/engproc2024068056 Source: Crossref Conclusion In summary, Mr. Farooq Ahmad is a highly suitable candidate for the Best Researcher Award. His impactful work on forecasting hydropower through innovative diffusion models, combined with his extensive academic background, teaching experience, technical skills, and a record of recognition, make him a promising researcher with the potential to contribute significantly to forecasting science. His research aligns well with global needs, particularly in renewable energy forecasting, making him an exceptional choice for this award. Farooq ahmad | Forecasting | Best Researcher Award
Farooq Ahmad began his teaching career as a Visiting Lecturer in the Department of Statistics at the University of Peshawar from 2014 to 2017. Subsequently, he joined the University of Malakand, Pakistan, as a Lecturer in the Department of Statistics, where he worked from September 2018 to January 2022. During his academic career, he has taught various courses in basic statistics, data processing, statistical computing, probability, and applied statistics, including practical skills in software like SPSS, Minitab, C++, and FORTRAN. Research Interests Farooq’s research spans multiple areas within applied and theoretical statistics, with a particular focus on innovation diffusion modeling, sports statistics, machine learning, time series modeling, and applied statistics. His current research investigates the potential of innovation diffusion models for hydropower forecasting, reflecting his interest in applying statistical methods to address real-world challenges. Top Notable Publications Forecasting Saudi Arabia’s Refined Petroleum Products: An In-depth Analysis of Time Series vs Machine Learning Models Authors: Not provided Year: 2024 Publication Date: November 21, 2024 Type: Preprint DOI: 10.20944/preprints202411.1557.v1 Source: Crossref Forecasting Hydropower with Innovation Diffusion Models: A Cross-Country Analysis Authors: Not provided Year: 2024 Publication Date: November 16, 2024 Type: Journal Article Journal: Forecasting DOI: 10.3390/forecast6040052 Source: Crossref Modeling the Future of Hydroelectric Power: A Cross-Country Study Authors: Not provided Year: 2024 Publication Date: July 19, 2024 Type: Conference Paper DOI: 10.3390/engproc2024068056 Source: Crossref Conclusion In summary, Mr. Farooq Ahmad is a highly suitable candidate for the Best Researcher Award. His impactful work on forecasting hydropower through innovative diffusion models, combined with his extensive academic background, teaching experience, technical skills, and a record of recognition, make him a promising researcher with the potential to contribute significantly to forecasting science. His research aligns well with global needs, particularly in renewable energy forecasting, making him an exceptional choice for this award.