Mr. Ahsan Jamil | Machine Learning | Best Researcher Award

Mr. Ahsan Jamil | Machine Learning | Best Researcher Award

Mr. Ahsan Jamil | New Mexico State University | United States

Ahsan Jamil is a PhD candidate in Water Science & Management at New Mexico State University ๐ŸŒŽ, specializing in machine learning and geospatial data science ๐Ÿ–ฅ๏ธ. He is focused on applying computational geoscience and satellite imagery analysis ๐ŸŒ to address earth and environmental challenges. With expertise in data-driven insights and problem-solving, Ahsan is passionate about sustainable environmental solutions ๐ŸŒฑ and is an effective science communicator ๐Ÿ“š, committed to raising awareness of critical environmental issues.

Professional Profile

Scopus

Suitability

Ahsan Jamil is highly deserving of the Best Researcher Award due to his exceptional contributions to the field of Water Science & Management ๐ŸŒŠ, particularly in machine learning and geospatial data science ๐Ÿง . His cutting-edge research, such as the development of ML-based geophysical inversion algorithms for hydrogeological characterization, showcases his ability to solve complex environmental challenges using innovative methodologies ๐ŸŒ. Ahsan has consistently demonstrated leadership in his research projects, including his work with the U.S. Department of Energy ๐ŸŒŸ, and his scientific articles have been published in renowned journals. He is a committed scholar who continuously strives for professional development, as evidenced by his numerous prestigious certifications ๐Ÿ“œ and awards ๐Ÿ†, such as the Baldwin and Reichert Scholar Award.

Educationย 

Ahsan Jamil is currently pursuing his PhD in Water Science & Management at New Mexico State University ๐Ÿซ, with a focus on geophysical electrical resistivity algorithms ๐Ÿ”ฌ.

Professionalย 

Ahsan Jamil has actively contributed to advancing his skills through certifications in remote sensing, big data analysis, and machine learning ๐Ÿ“Š. His participation in programs such as NASAโ€™s Advanced Remote Sensing ๐ŸŒŒ and UNU-INWEHโ€™s Big Data for Water ๐ŸŒŠ highlights his commitment to continued professional growth. He has also been recognized with prestigious awards including the Baldwin and Reichert Scholar Award ๐Ÿ† and the Encompass Scholar title by the American Society of Agronomy ๐ŸŒฑ.

Experience

He has an MSc in Remote Sensing & GIS from PMAS-AAUR, Pakistan ๐ŸŽ“ and a BSc in Geophysics ๐Ÿงญ from Bahria University, Islamabad. Ahsan’s career includes roles as a Graduate Research Assistant at NMSU, GIS Analyst at Wateen Telecom ๐ŸŒ, and Visiting Lecturer in Pakistan ๐ŸŽ“, as well as freelance GIS consulting ๐ŸŒ.

Research Focus

Ahsan Jamil’s research is centered on computational geoscience, with a particular focus on machine learning ๐Ÿง  and geospatial data science ๐ŸŒ. He utilizes satellite imagery ๐Ÿ“ธ and advanced data analytics to solve critical earth and environmental challenges ๐ŸŒฑ. His work contributes to understanding water management ๐Ÿ’ง, hydrogeological characterization ๐Ÿž๏ธ, and sustainable environmental solutions ๐ŸŒ, making significant strides in both academia and practical applications.

Awars and Honors

  • Baldwin and Reichert Scholar Award, New Mexico State University (2024).
  • Encompass Scholar (2021โ€“2022), American Society of Agronomy.
  • Media Fellowship, ICIMOD (2015).
  • Vice Chancellor Talent Scholarship, PMAS-AAUR (2017).

Publication top notes

Bokhari, R., Shu, H., Tariq, A., Jamil, A., Aslam, M. (2023). Land subsidence analysis using synthetic aperture radar data. Heliyon, 9(3), e14690. [Link Disabled]
  • Citations: 27
Tariq, A., Ali, S., Basit, I., Junaid, M.B., Hatamleh, W.A. (2023). Terrestrial and groundwater storage characteristics and their quantification in the Chitral (Pakistan) and Kabul (Afghanistan) river basins using GRACE/GRACE-FO satellite data. Groundwater for Sustainable Development, 23, 100990. [Link Disabled]
  • Citations: 25
Zheng, X., Sarwar, A., Islam, F., Aslam, M., Soufan, W. (2023). Rainwater harvesting for agriculture development using multi-influence factor and fuzzy overlay techniques. Environmental Research, 238, 117189. [Link Disabled]
  • Citations: 16
Feng, L., Khalil, U., Aslam, B., Aslam, M., Soufan, W. (2024). Evaluation of soil texture classification from orthodox interpolation and machine learning techniques. Environmental Research, 246, 118075. [Link Disabled]
  • Citations: 12
Zaman-ul-Haq, M., He, M., Kanwal, A., Mubbin, M., Bokhari, S.A. (2024). Remote Sensing-Based Assessments of Socioeconomic Factors for Urban Ecological Resilience in the Semi-Arid Region. Rangeland Ecology and Management, 96, 12โ€“22. [Link Disabled]
  • Citations: 2