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

 

Soumeya Belabbas | Artificial Intelligence | Best Researcher Award

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Soumeya Belabbas| Artificial Intelligence| Best Researcher Award

Soumeya Belabbas,University of Sciences and Technology Houari Boumediene,United state.

Soumeya has taught telecommunications systems and networks to fourth-year engineering students at the Higher National School of Information and Communication Technologies and Post in Algiers. Her teaching module includes mobile networks.

Publication Profile

Google Scholar

Education 

Soumeya Belabbas is currently pursuing her PhD in Telecommunication and Information Processing at the University of Sciences and Technology Houari Boumediene in Algiers, Algeria, a journey she embarked on in December 2017. Her doctoral research focuses on multi-variable acoustic modeling for assessing pathological speech understanding, showcasing her deep commitment to advancing the field of telecommunications and speech processing. In addition to her ongoing doctoral studies, Soumeya holds a Master’s degree in Telecommunications, Networks, and Multimedia, which she earned in June 2017 from the same university. This advanced degree equipped her with a robust foundation in telecommunications, further honed through her bachelor’s degree in Telecommunications and Electronics, completed in June 2015. Her academic journey began with a Baccalaureate Diploma in Experimental Sciences, awarded in July 2012, which laid the groundwork for her subsequent specialization and research. Soumeya has also actively participated in professional development activities, such as a workshop on FPGA systems in April 2024, reflecting her continuous pursuit of knowledge and expertise in her field.

Soumeya Belabbas has cultivated a solid foundation in both research and teaching throughout her academic career. As a part-time teacher at the Higher National School of Information and Communication Technologies and Post in Algiers, Algeria, she has been responsible for educating fourth-year engineering students in telecommunications systems and networks, with a specific focus on mobile networks. Her teaching role, undertaken in June 2024, has allowed her to share her extensive knowledge and experience with the next generation of engineers. Alongside her teaching duties, Soumeya has made significant contributions to the field of telecommunications and information processing through her research. She has published multiple articles and presented her findings at international conferences, showcasing her expertise in improving mobile speech recognition systems and pathological speech classification. Her role as a researcher and educator demonstrates her commitment to advancing the field and fostering academic growth.

Soumeya Belabbas’s research is centered on the cutting-edge domains of telecommunications and speech processing, with a particular emphasis on addressing challenges in automatic speech recognition and classification. Her work is dedicated to developing innovative solutions for individuals with voice disorders, aiming to enhance the robustness and accuracy of speech recognition systems. Her current PhD research project, titled “Multi-variable Acoustic Modeling for Assessing Pathological Speech Understanding,” exemplifies her focus on improving pathological speech classification systems. This project involves a comprehensive three-stage framework that incorporates advanced techniques such as speech enhancement, multi-stream approaches, and deep machine learning algorithms like convolutional neural networks (CNN) and bidirectional long short-term memory (BiLSTM) networks. Additionally, Soumeya’s interests extend to signal processing, image processing, and audio speech processing, leveraging machine learning and deep learning methodologies to tackle complex problems in these areas. Her dedication to these research areas is reflected in her numerous publications and presentations, which contribute to the advancement of knowledge and technology in telecommunications and speech processing.

Skills

Soumeya Belabbas possesses a diverse and robust skill set that spans various aspects of telecommunications, information processing, and programming. She is proficient in multiple programming languages, including C/C++, Python, Perl, MATLAB, VHDL, PHP, HTML5, and CSS3, which enable her to develop sophisticated algorithms and models for speech processing and recognition. Her technical expertise extends to the use of HTK tools, essential for hidden Markov model training and evaluation in speech recognition systems. Soumeya is also skilled in managing and operating different operating systems, including Windows Server and Linux (Ubuntu), ensuring that she can work in a versatile computing environment. Her strong foundation in signal and audio speech processing is complemented by her experience with machine learning and deep learning techniques, which she applies to enhance the performance of speech recognition systems. Additionally, Soumeya is well-versed in the use of various software tools and platforms essential for research and development in her field, making her a well-rounded and highly capable researcher and education .

Publications 📚📝