Mr. Ahsan Jamil | Machine Learning | Best Researcher Award

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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 🌎, specializing in machine learning and geospatial data science 🖥️. He is focused on applying computational geoscience and satellite imagery analysis 🌐 to address earth and environmental challenges. With expertise in data-driven insights and problem-solving, Ahsan is passionate about sustainable environmental solutions 🌱 and is an effective science communicator 📚, 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 🌊, particularly in machine learning and geospatial data science 🧠. 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 🌍. Ahsan has consistently demonstrated leadership in his research projects, including his work with the U.S. Department of Energy 🌟, 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 📜 and awards 🏆, such as the Baldwin and Reichert Scholar Award.

Education 

Ahsan Jamil is currently pursuing his PhD in Water Science & Management at New Mexico State University 🏫, with a focus on geophysical electrical resistivity algorithms 🔬.

Professional 

Ahsan Jamil has actively contributed to advancing his skills through certifications in remote sensing, big data analysis, and machine learning 📊. His participation in programs such as NASA’s Advanced Remote Sensing 🌌 and UNU-INWEH’s Big Data for Water 🌊 highlights his commitment to continued professional growth. He has also been recognized with prestigious awards including the Baldwin and Reichert Scholar Award 🏆 and the Encompass Scholar title by the American Society of Agronomy 🌱.

Experience

He has an MSc in Remote Sensing & GIS from PMAS-AAUR, Pakistan 🎓 and a BSc in Geophysics 🧭 from Bahria University, Islamabad. Ahsan’s career includes roles as a Graduate Research Assistant at NMSU, GIS Analyst at Wateen Telecom 🌍, and Visiting Lecturer in Pakistan 🎓, as well as freelance GIS consulting 🌐.

Research Focus

Ahsan Jamil’s research is centered on computational geoscience, with a particular focus on machine learning 🧠 and geospatial data science 🌍. He utilizes satellite imagery 📸 and advanced data analytics to solve critical earth and environmental challenges 🌱. His work contributes to understanding water management 💧, hydrogeological characterization 🏞️, and sustainable environmental solutions 🌍, making significant strides in both academia and practical applications.

Awars and Honors

  • Baldwin and Reichert Scholar Award, New Mexico State University (2024).
  • Encompass Scholar (2021–2022), 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, 12–22. [Link Disabled]
  • Citations: 2

 

MohammadSadeq Mottaqi | Machine Learning | Best Researcher Award

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MohammadSadeq Mottaqi | Machine Learning | Best Researcher Award

Dr. MohammadSadeq Mottaqi, City University of New York, United States.

Dr. MohammadSadeq Mottaqi is a Ph.D. candidate in Biochemistry at the City University of New York, with a background in Biotechnology from the University of Tehran. Proficient in Python and R, Mohammad excels in bioinformatics tools like PyMol and Gromacs. His research spans machine learning-based drug action prediction, molecular dynamics simulations, and protein-ligand interactions. He has published on topics such as SARS-CoV-2 infection responses and cyanobacterial genera identification. Mohammad’s technical prowess extends to data analysis, visualization, and high-performance computing, reflecting his commitment to advancing biotechnological and computational research. 🧬🔬💻

Publication Profile

Scopus

orcid

Education 🎓

Ph.D. in Biochemistry
City University of New York, New York, NY
Aug 2022 – Present

Bachelor of Science in Biotechnology
University of Tehran, Tehran, Iran
Sep 2017 – March 2022

Experience 💼

Graduate Assistant
City University of New York, New York, NY
Aug 2022 – Present

  • Assisting in bioinformatics and computational biochemistry research.

Research Experience

  • Conducted molecular dynamics simulations of mutated HER2 proteins.
  • Investigated protein-ligand interactions using Python and PyMOL.
  • Developed machine learning models for predicting drug actions.

 

Professional Development

Mr.Mohammad Sadeq Mottaqi is currently immersed in his Ph.D. journey in Biochemistry at the City University of New York, focusing on computational biochemistry. His research expertise includes pioneering machine learning approaches for predicting drug actions and analyzing transcriptomics data to advance personalized medicine. Mohammad’s impactful contributions extend to molecular dynamics simulations of protein interactions and investigating the molecular mechanisms of SARS-CoV-2 mutations. With a foundation in biotechnology from the University of Tehran, he blends technical skills in Python, R, and bioinformatics tools like Gromacs and PyMol. Mohammad is dedicated to pushing the boundaries of bioinformatics, bridging theoretical insights with practical applications in healthcare and environmental management.🌱

Research Focus

Mr. MohammadSadeq Mottaqi is a biochemist and computational scientist specializing in bioinformatics and machine learning applications in drug discovery and molecular biology. His research includes predictive modeling for drug actions, molecular dynamics simulations, and protein-ligand interactions. Mohammad has contributed significantly to understanding SARS-CoV-2 through machine learning approaches and automated identification of toxigenic cyanobacterial genera for water quality control. His work, cited extensively, showcases his expertise in integrating computational tools and biotechnological research, making impactful advancements in these fields. 🌐🔬💻📊

Publications 📚📝

  • Automated identification of toxigenic cyanobacterial genera for water quality control purposes, Journal of Environmental Management, 2024 🌿
  • Contribution of machine learning approaches in response to SARS-CoV-2 infection, Informatics in Medicine Unlocked, 2021 🦠
  • Mutations in SARS-CoV-2; Consequences in structure, function, and pathogenicity of the virus, Microbial Pathogenesis, 2021 🧬