Mehdi Hasan Rafi | Weather & Atmosphere | Best Researcher Award

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Mr. Mehdi Hasan Rafi | Weather & Atmosphere | Best Researcher Award

PhD Scholar of Full-Time Ph.D. Researcher, Bangladesh.

Mehdi Hasan Rafi is a distinguished researcher with notable expertise in geospatial data analysis and weather forecasting. His recent accolade, the Best Paper Award at the 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), highlights his significant contributions to the field. Rafi is proficient in programming languages like Python, R, and MATLAB, and excels in data manipulation, visualization, and mining, utilizing advanced techniques in machine learning and deep learning. His research, including journal publications and conference presentations, demonstrates a strong impact on atmospheric studies and ionospheric research. Currently serving as a Senior Executive in Research & Development at FIFOTech, he combines practical industry experience with his academic background. Despite his impressive achievements, expanding his research scope and increasing public engagement could further enhance his impact. Rafi’s strong technical skills and recognized contributions make him a compelling candidate for the Research for Best Researcher Award.

Profile
Education

Mehdi Hasan Rafi’s educational journey reflects a strong foundation in electrical and electronic engineering. He completed his Bachelor of Science (B.Sc.) in Electrical and Electronic Engineering from Daffodil International University (DIU) in 2014, where he earned a CGPA of 3.46 out of 4.00. His academic excellence continued with a Master of Science (M.Sc.) degree in the same field from Military Institute of Science and Technology (MIST) in 2023, achieving a CGPA of 3.08 out of 4.00. Rafi’s early education includes a robust science background, having completed his Higher Secondary Certificate (HSC) and Secondary School Certificate (SSC) from Khulna Government Model School & College and Saint Joseph’s High School, respectively. His strong academic performance, underscored by high GPAs, laid the groundwork for his research and professional achievements in atmospheric data analysis and geospatial research.

Professional Experience

Mehdi Hasan Rafi brings a wealth of experience in atmospheric research and data analysis. Currently, he serves as a Senior Executive in Research & Development at FIFOTech, where he leads market and industry research, manages projects, and develops innovative strategies. His role involves analyzing data, preparing reports, and representing the company at industry conferences. Previously, Rafi was a co-investigator at Frederick University, Cyprus, focusing on atmospheric research projects, including the Rate of Total Electron Content Index (ROTI) of the ionosphere. His academic background includes degrees in Electrical and Electronic Engineering from Military Institute of Science and Technology (MIST) and Daffodil International University, with a notable track record in geospatial data analysis, programming, and machine learning. His work is recognized through prestigious awards, including the Best Paper Award at the 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT).

Research Interest

Mehdi Hasan Rafi’s research interests are centered around atmospheric sciences and geospatial data analysis, with a particular focus on ionospheric studies and weather forecasting. His work involves utilizing advanced programming languages such as Python, R, and MATLAB to manipulate and analyze large datasets, employing machine learning and deep learning techniques to extract meaningful insights. Rafi is skilled in data mapping using GIS technologies and has conducted significant research on the Rate of Total Electron Content Index (ROTI) of the ionosphere, exploring variations in electron density over European and North American sectors. His research also encompasses global lightning phenomena and time series modeling of lightning radiance, aiming to enhance the understanding of atmospheric processes. Rafi’s interdisciplinary approach and expertise in both theoretical and practical aspects of atmospheric research contribute to advancements in weather prediction and atmospheric data interpretation.

Research Skills

Mehdi Hasan Rafi demonstrates a robust set of research skills, particularly in the domain of geospatial data analysis and atmospheric research. He excels in programming languages such as Python, R, and MATLAB, which are integral to his work in manipulating and analyzing complex datasets. His proficiency extends to data visualization, mapping, and mining, where he employs GIS techniques to extract meaningful insights from vast data sources. Rafi’s expertise in machine learning and deep learning, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), further enhances his capability to develop advanced analytical models. His research on ionospheric phenomena and lightning detection showcases his ability to handle intricate data sets, identify trends, and contribute valuable findings to the field. Rafi’s skills in integrating diverse data sources and utilizing cutting-edge analytical methods underscore his strong research acumen and innovative approach to addressing atmospheric challenges.

Awards and Recognition

Mehdi Hasan Rafi has garnered notable awards and recognition for his significant contributions to the field of atmospheric research. In May 2024, he received the prestigious Best Paper Award (First Prize) at the 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT) for his outstanding research. His academic excellence was further acknowledged with the Dr. Aminul Islam Scholarship, awarded by Daffodil International University in January 2018. Rafi’s research has been published in esteemed journals, including the Journal of Geophysical Research: Atmospheres and Atmosphere, showcasing his impact in the field. His contributions extend to various conferences, where he has presented his work, further establishing his reputation in the scientific community. These accolades reflect his commitment to advancing atmospheric research and highlight his role as a leading researcher in his area of expertise.

Conclusion

Mehdi Hasan Rafi is a strong candidate for the Research for Best Researcher Award due to his significant contributions to atmospheric research, technical skills, and industry experience. His accomplishments in data analysis and programming, coupled with his recognized awards and publications, make him a standout nominee. Addressing areas for improvement, such as increasing public engagement and exploring broader research areas, could further strengthen his profile and impact in the research community.

Publications Top Notes

  1. Evaluation of Detection Efficiency of World Wide Lightning Location Network in Southeast Asian Region
    • Authors: M.H. Rafi, R.H. Holzworth, M.G. Mostafa
    • Year: 2024
  2. Correlation of Rate of TEC Index and Spread F over European Ionosondes
    • Authors: K.S. Paul, M.H. Rafi, H. Haralambous, M.G. Mostafa
    • Year: 2024
  3. Space-Based Investigation of the Topside Ionosphere over Bangladesh Including IRI Predictions
    • Authors: N. Fatima, N. Salsabil, M.H. Rafi, M.G. Mostafa
    • Year: 2024
  4. Investigation of Ionospheric Diurnal Double Maxima over Bangladesh
    • Authors: J.F. Preeti, R. Amreen, M.H. Rafi, M.G. Mostafa
    • Year: 2024
  5. Examining the Consistency Between Quality-Assured Radio Occultation Data in Bangladesh and IRI Predictions
    • Authors: S.S. Mahmood, A.H. Shawon, M.H. Rafi, M.G. Mostafa
    • Year: 2024
  6. Time Series Models for Radiated Electromagnetic Energy of Lightning Strokes Detected by World Wide Lightning Location Network
    • Authors: M.H. Rafi, G. Mostafa
    • Year: 2023
  7. Global Lightning Phenomena and Time Series Model of Lightning Flash Radiance
    • Authors: M.H. Rafi, M.G. Mostafa
    • Year: 2022
    • Citations: 1