Abul Abrar Masrur Ahmed | Water Engineering | Best Researcher Award

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Dr. Abul Abrar Masrur Ahmed | Water Engineering | Best Researcher Award

A dedicated data scientist with expertise in applied AI (deep and machine learning) techniques for air quality, bias correction, hydrology, water resources, and climate extremes. I have a decade of experience in building robust Machine Learning solutions, combining professional and research experience to gain deep knowledge in hydrology and water resources. I am passionate about leveraging data science and AI to drive impactful data-driven decisions.

Publication profile

Scopus

Scholar

 

šŸ† Evaluation for Best Researcher Award

šŸ” Streng ths for the Award:

Extensive Research Experience: With over a decade of experience in applied AI and machine learning for hydrology, climate extremes, and air quality, Dr. Masrur Ahmed has developed a solid research foundation, making significant contributions to environmental and climate sciences. Prolific Publications: A commendable h-index of 16 and an i10-index of 25, along with a considerable number of publications in high-impact journals, reflects Dr. Ahmed’s active research engagement and scholarly impact. Innovative Application of AI: His work in developing hybrid deep learning models for hydrological prediction and air quality forecasting is cutting-edge, pushing the boundaries of traditional environmental science research. Recognized Expertise: His role as a reviewer and guest editor in respected journals, along with memberships in several professional organizations, underscores his standing in the scientific community. Global Collaboration: His involvement in international projects, such as those with the University of Melbourne, CSIRO, and BOM, indicates his ability to work effectively across disciplines and borders.

šŸ”„ Areas for Improvement:

Interdisciplinary Applications: While Dr. Ahmed excels in his niche, expanding his AI applications to other fields, such as agriculture or public health, could further enhance his research portfolio. Leadership Roles: Although he has served as Head of the Civil Engineering Department, more leadership roles in larger, interdisciplinary research projects could solidify his candidacy for top awards. Public Engagement: Increasing efforts to communicate his research to a broader audience through public talks, popular science articles, or media could enhance the societal impact of his work.

šŸŽ“ EDUCATION

2019 ā€“ 2022 PhD in Applied Artificial Intelligence University of Southern Queensland, Australia Thesis: Development of Deep Learning Hybrid Models for Hydrological Prediction. 2011 ā€“ 2017 MSc in Civil & Environmental Engineering Shahjalal University of Science & Technology
Thesis: Development of ANN Model to Predict the DO Concentration of the Surma River. 2005 ā€“ 2009 BSc in Civil & Environmental Engineering
Shahjalal University of Science & Technology

šŸ’¼ WORK EXPERIENCE

Scientist, Climate and Atmospheric Science Department of Climate Change, Energy, the Environment and Water JAN/2024 ā€“ Present Developing machine learning and deep learning models focused on emission modeling and air quality forecasting. Research Fellow in Water Resource Modelling The University of Melbourne, Australia FEB/2022 ā€“ JAN/2024 Conducted research in water demand forecasting under global warming scenarios, developed probabilistic deep learning models, and collaborated with leading institutions like CSIRO and BOM. Research Scholar
University of Southern Queensland (UniSQ), Australia FEB/2019 ā€“ FEB/2022 Developed hybrid deep learning algorithms for hydrological forecasting in the Australian Murray Darling Basin.

šŸ§Ŗ RESEARCH HIGHLIGHTS

  • ORCiD: 0000-0002-7941-3902
  • Google Scholar: Link
  • Citations: 1048
  • h-index: 16
  • i10-index: 25
  • Review/Guest Editor:
    • Frontiers in Artificial Intelligence
    • Journal of Land (Special Edition)

 

Publication top notes

  1. Title: Application of adaptive neuro-fuzzy inference system (ANFIS) to estimate the biochemical oxygen demand (BOD) of Surma River
    Authors: AAM Ahmed, SMA Shah
    Year: 2017

 

  1. Title: Prediction of dissolved oxygen in Surma River by biochemical oxygen demand and chemical oxygen demand using the artificial neural networks (ANNs)
    Authors: AAM Ahmed
    Year: 2014

 

  1. Title: Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity
    Authors: AAM Ahmed, RC Deo, Q Feng, A Ghahramani, N Raj, Z Yin, L Yang
    Year: 2021

 

  1. Title: LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios
    Authors: AAM Ahmed, RC Deo, A Ghahramani, N Raj, Q Feng, Z Yin, L Yang
    Year: 2021

 

  1. Title: Deep learning forecasts of soil moisture: convolutional neural network and gated recurrent unit models coupled with satellite-derived MODIS, observations and synoptic-scale variables
    Authors: AAM Ahmed, RC Deo, N Raj, A Ghahramani, Q Feng, Z Yin, L Yang
    Year: 2021

 

  1. Title: A Canadian water quality guideline-water quality index (CCME-WQI) based assessment study of water quality in Surma River
    Authors: GM Munna, MMI Chowdhury, AAM Ahmed, S Chowdhury, MM Alom
    Year: 2013

 

  1. Title: Hybrid deep learning method for a week-ahead evapotranspiration forecasting
    Authors: AAM Ahmed, RC Deo, Q Feng, A Ghahramani, N Raj, Z Yin, L Yang
    Year: 2022

 

  1. Title: New double decomposition deep learning methods for river water level forecasting
    Authors: AAM Ahmed, RC Deo, A Ghahramani, Q Feng, N Raj, Z Yin, L Yang
    Year: 2022

 

  1. Title: Hybrid intelligence models for compressive strength prediction of MPC composites and parametric analysis with SHAP algorithm
    Authors: MA Haque, B Chen, A Kashem, T Qureshi, AAM Ahmed
    Year: 2023

šŸ… Conclusion:

Dr. Masrur Ahmed is a strong contender for the Best Researcher Award, given his significant contributions to applied AI in environmental sciences, extensive publication record, and active role in the research community. To further strengthen his candidacy, broadening the interdisciplinary application of his work and increasing his public engagement could be beneficial.

Alemeshet Kebede Yimer | Remot sensing and hydrology | Best Researcher Award

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Mrs. Alemeshet Kebede Yimer | Virtual Reality | Young Scientist Award

Mrs at Arba Minch University, Ethiopia Ethiopia

Dr. Alemkebede Yimer is a researcher and educator specializing in Irrigation and Drainage Engineering, GIS, and Remote Sensing. Since 2003, he has taught and conducted research at Arba Minch University, Ethiopia, focusing on water resource management and irrigation. His expertise includes remote sensing for irrigated area mapping and model-based water abstraction evaluation. He holds a Ph.D. in Irrigation and Drainage Engineering, an MSc in Climate Change & Development, and a BSc in Civil Engineering, all from Arba Minch University. He also has a BED in Physics from Dilla University and various certifications in climate modeling and teaching methodology.

Publication Profile

Scholar

šŸ¢ Work Experience

Researcher and Lecturer, Arba Minch University, Ethiopia 07/08/2003 ā€“ Present Specializing in Irrigation and Drainage Engineering, GIS and Remote Sensing, Environmental Science, and Physics. Focused on Remote Sensing-based irrigated area mapping and water resource consultancy. Expertise in evaluating water abstraction in basins and implementing model-based approaches in irrigation.

šŸŽ“ Education and Training

Ph.D. in Irrigation and Drainage Engineering, Arba Minch University, Ethiopia 2019 ā€“ Present. MSc in Climate Change & Development, Arba Minch University, Ethiopia 2013 ā€“ 2015. BSc in Civil Engineering, Arba Minch University, Ethiopia 2011 ā€“ 2015 Bed in Physics, Dilla University, Ethiopia 2003 – 2007 Certificate on 3rd Regional Climate Impact Modelling Workshop for Eastern Africa, Addis Ababa University, Ethiopia 2013 Higher Educational Institute Teaching Methodology Certificate, Arba Minch University 2012 Computer Diploma, Durame Isaac Computer and Language Training Center, Ethiopia 2002. High School Level, Arba Minch Comprehensive High School 1998 ā€“ 2000 Junior Level, Arba Minch Junior School 1996 ā€“ 1997 Elementary Level, Arba Minch Elementary School 1994 ā€“ 1995

šŸŒŸ Personal Skills

Communication Skills: Strong communication abilities developed through extensive teaching and research. Job-Related Skills: Proficient in quality control processes and faculty teaching.. Computer Skills: Expertise in SNAP tool, ArcGIS, ENVI, MATLAB, SMARG, all MS applications, ORANGE 8, GrADS, and Fortran. Other Skills: Drawing.

 

šŸ† Assessment for the Research for Best Researcher Award šŸ†

Strengths for the Award:

  1. Extensive Research Experience: Alemachew Kebede Yimer’s role as a researcher and lecturer in irrigation and drainage engineering, GIS, and remote sensing demonstrates a strong background in critical areas related to water management and environmental science. His work with the International Water Management Institute (IWMI) on remote sensing-based irrigation mapping and water abstraction evaluation highlights his expertise and contributions to the field.
  2. Specialized Knowledge: His specialization in remote sensing and model-based approaches for evaluating water resources is highly relevant to current global challenges in water management and climate change. This niche expertise aligns well with the criteria for the Research for Best Researcher Award.
  3. Academic and Professional Qualifications: Alemachew holds a Ph.D. in Irrigation and Drainage Engineering and has additional qualifications in climate change and development, civil engineering, and teaching methodology. This diverse educational background supports his in-depth understanding and capability in his research domain.
  4. Proven Impact and Contributions: His consultancy work with IWMI and his involvement in high-impact research projects reflect his ability to influence and advance the field. His contributions to model-based evaluations and remote sensing applications are notable achievements.
  5. Strong Language and Communication Skills: Alemachewā€™s excellent proficiency in English and Amharic, along with his good communication skills, enhance his ability to collaborate, present, and disseminate research findings effectively.

Areas for Improvement:

Expand Research Scope: While Alemachewā€™s specialization is impressive, expanding his research to include more interdisciplinary approaches or emerging technologies could further enhance his impact. Engaging with new methodologies or broader topics in environmental science and engineering might provide additional opportunities for groundbreaking work.. Increase International Collaboration: Strengthening international collaborations could provide new perspectives and opportunities for joint research initiatives. Participating in more global conferences and projects could enhance his visibility and influence within the global research community.. Enhance Publication Record: Increasing the number of publications in high-impact journals and presenting at international conferences could further solidify his reputation as a leading researcher. Focus on publishing innovative findings and high-quality research outputs.

Publications:

  1. Title: Seasonal effect on the accuracy of Land use/Land cover classification in the Bilate Sub-basin, Abaya-Chamo Basin, Rift valley Lakes Basin of Ethiopia
    Authors: A.K. Yimer, A.T. Haile, S.D. Hatiye, A.G. Azeref
    Journal: Ethiopian Journal of Water Science and Technology
    Year: 2020
    Volume: 3
    Pages: 23-50
    Citations: 6

 

  1. Title: Implications of uncontrolled water withdrawal and climate change on the water supply and demand gap in the Lake Tana sub-basin
    Authors: M. Ferede, A. Haile, A. Gedle, A. Kebede, S.D. Amare, M. Taye
    Journal: Ethiopian Journal of Water Science and Technology
    Year: 2022
    Volume: 5
    Pages: 74-101
    Citations: 2

 

  1. Title: Comparative Evaluation of the Accuracy of Mapping Irrigated Areas using Sentinel 1 Images in the Bilate and Gumara Watersheds, Ethiopia
    Authors: A.K. Yimer, A.T. Haile, S.D. Hatiye, S. Ragettli, M.T. Taye
    Journal: Cogent Engineering
    Year: 2024
    Volume: 11
    Pages: 1-19
    ISSN: 2331-1983

Conclusion:

Muhammad Javed Ramzan is a strong candidate for the Research for Young Scientist Award. His expertise in XR and AI, combined with a solid academic background, innovative research contributions, and notable achievements, position him well for this recognition. By broadening his research focus, increasing international exposure, and enhancing industry collaborations, Muhammad could further elevate his standing as a leading young scientist. His innovative approach and commitment to advancing technology make him a deserving candidate for this award.