Busuyi Akeredolu | Machine Learning | Best Researcher Award

Busuyi Akeredolu | Machine Learning | Best Researcher Award

Lecturer at Lagos State University of Education, Nigeria

Busuyi E. Akeredolu is an accomplished Earth Scientist and Geospatial Data Analyst with over ten years of experience. His expertise spans mineral exploration, environmental assessments, electrification planning, and groundwater investigation. Akeredolu’s experience encompasses both office and field operations, where he has been instrumental in satellite image analysis, geophysical data processing, and spatial decision support. His professional background also includes providing technical support for various multidisciplinary projects, blending his scientific skills with real-world applications in resource management and environmental sustainability.

Profile

Orcid

Education

Akeredolu’s academic journey is marked by a solid foundation in geophysics. He is currently pursuing a Ph.D. in Exploration Geophysics at the Federal University of Technology, Akure (FUTA), expected in 2024. He holds an M.Tech. in Exploration Geophysics, also from FUTA (2017), and a B.Sc. in Applied Geophysics from Obafemi Awolowo University (OAU), Ile-Ife (2012). Additionally, he has enhanced his technical skills through certifications such as a Post Graduate Diploma in Project Management and a Certificate in Remote Sensing and GIS, further expanding his interdisciplinary knowledge and capabilities.

Experience

Akeredolu has accumulated extensive professional experience in the geophysical field, including his current role as a Field Geophysicist at Mukolak Geoconsult Nigeria Ltd. Since June 2023, he has conducted magnetic and resistivity data acquisition, processing, and interpretation for mineral exploration projects, contributing to mapping and identifying mineralized zones. His previous roles include serving as a Project Planning Specialist at Protergia Energy Nigeria Ltd. (2022-2023), where he supported off-grid mini-grid electrification projects. Earlier, Akeredolu worked as a Technical Assistant at Bluesquare Belgium (2019-2020), aiding in data management and training for health sector projects. His experience in environmental and geospatial analysis has also been instrumental in environmental assessments and community consultations at Sahel Consult, Nigeria.

Research Interest

Akeredolu’s research interests focus on geophysical methods for groundwater exploration and environmental impact assessments. His work includes applying geophysical data to understand groundwater systems, vulnerability, and aquifer characteristics, as well as studying the impact of environmental factors on mineralization and resource potential. Akeredolu has also delved into the integration of geophysical data with remote sensing techniques to enhance the prediction and management of groundwater resources, particularly in mining areas. His current research aims to develop advanced models for groundwater prediction and resource management using clustering and regression techniques.

Awards

Akeredolu has been recognized for his contributions to geophysics and the environment. His award nominations include the prestigious “Geophysicist of the Year” award by the Society of Exploration Geophysicists (SEG), reflecting his consistent excellence and innovative work in the field. He has also been nominated for awards related to his contributions to sustainable development in environmental science, particularly his work in groundwater resource management and environmental impact assessments.

Publications

Akeredolu, B. E., Adiat, K. A. N., Akinlalu, A. A., Olayanju, G. M., & Afolabi, D.O. (2024). Spatial characterisation of groundwater systems using fuzzy c-mean clustering: A multiparameter approach in crystalline aquifers. Resources, Conservation and Recycling, 100051, ISSN 2211-148, https://doi.org/10.1016/j.rines.2024.100051.

Adegbola, R.B., Whetode, J., Adeogun, O., Akeredolu, B., & Lateef, O. (2023). Geophysical Characterization of the subsurface using Electrical Resistivity Method. Journal of Research and Review in Science, 10, 14-20, DOI: 10.36108/jrrslasu/2202.90.0250.

Akeredolu, B. E., Adiat, K. A. N., Akinlalu, A. A., & Olayanju, G. M. (2022). The Relationship Between Morpho-Structural Features and Borehole Yield in Ilesha Schist Belt, Southwestern Nigeria: Results from Geophysical Studies. Earth Sciences, 11(1), 16-28, doi: 10.11648/j.earth.20221101.13.

Adiat, K. A. N., Akeredolu, B. E., Akinlalu, A. A., & Olayanju, G. M. (2020). Application of logistic regression analysis in prediction of groundwater vulnerability in gold mining environment: a case of Ilesa gold mining area, southwestern, Nigeria. Environmental Monitoring and Assessment, 192(9), doi:10.1007/s10661-020-08532-7.

Adiat, K. A. N., Adegoroye, A. A., Akeredolu, B. E., & Akinlalu, A. A. (2019). Comparative assessment of aquifer susceptibilities to contaminant from dumpsites in different geological locations. Heliyon, 5(5), e01499.

Bawallah, M. A., Akeredolu, B. E., et al. (2019). Integrated Geophysical Investigation of Aquifer and its Groundwater Potential in Camic Garden Estate, Ilorin Metropolis North-Central Basement Complex of Nigeria. IOSR Journal of Applied Geology and Geophysics, 7(2), 01-08.

Akinlalu, A. A., Akeredolu, B. E., & Olayanju, G. M. (2018). Aeromagnetic mapping of basement structures and mineralisation characterisation of Ilesa Schist Belt, Southwestern Nigeria. Journal of African Earth Sciences, 138, 383-389.

Conclusion

Busuyi E. Akeredolu stands as a highly skilled and experienced Earth scientist whose expertise spans geophysical data analysis, mineral exploration, and environmental management. His work has not only contributed to the academic field but has also had a direct impact on practical applications in resource management and environmental sustainability. Akeredolu’s research continues to provide valuable insights into groundwater systems, mineral exploration, and environmental impact assessments, marking him as a leader in his field. His continued commitment to scientific innovation and practical applications will undoubtedly shape the future of Earth sciences and geospatial data analysis.

Mohsen Saroughi | Machine Learning | Best Scholar Award

Mr. Mohsen Saroughi | Machine Learning | Best Scholar Award

Researcher | university of tehran | Iran

Mohsen Saroughi is an accomplished water resource management professional with a passion for research and innovation. With expertise in machine learning, groundwater modeling, and hydrology, Mohsen has established himself as a leading figure in applying artificial intelligence and optimization techniques to water resource challenges.

Profile

Google scholar

Education 🎓

  • Master’s in Water Resource Management (2018–2021): University of Tehran, Tehran, Iran (CGPA: 3.5/4)
  • Bachelor’s in Water Engineering (2014–2018): University of Bu-Ali Sina, Hamedan, Iran (CGPA: 3.1/4)

Experience 💼

Mohsen has served as a teaching assistant and research mentor, guiding students on projects in hydrology and groundwater management. His professional experience includes roles as a language editor, GIS consultant, and intern, where he demonstrated expertise in modeling, remote sensing, and IT solutions.

Research Interests 🔬

Mohsen’s research spans groundwater management, machine learning, climate change, and systems dynamics. He excels in applying artificial intelligence to water resource optimization and hydrological modeling.

Publications 📚

“A novel hybrid algorithms for groundwater level prediction”

  • Authors: M Saroughi, E Mirzania, DK Vishwakarma, S Nivesh, KC Panda, …
  • Journal: Iranian Journal of Science and Technology, Transactions of Civil Engineering
  • Year: 2023
  • Citations: 31

“Hybrid COOT-ANN: a novel optimization algorithm for prediction of daily crop reference evapotranspiration in Australia”

  • Authors: E Mirzania, MH Kashani, G Golmohammadi, OR Ibrahim, M Saroughi
  • Journal: Theoretical and Applied Climatology 154 (1), 201-218
  • Year: 2023
  • Citations: 7

“Shannon entropy of performance metrics to choose the best novel hybrid algorithm to predict groundwater level (case study: Tabriz plain, Iran)”

  • Authors: M Saroughi, E Mirzania, M Achite, OM Katipoğlu, M Ehteram
  • Journal: Environmental Monitoring and Assessment 196 (3), 227
  • Year: 2024
  • Citations: 5

“Prediction of monthly groundwater level using a new hybrid intelligent approach in the Tabriz plain, Iran”

  • Authors: E Mirzania, M Achite, N Elshaboury, OM Katipoğlu, M Saroughi
  • Journal: Neural Computing and Applications, 1-16
  • Year: 2024
  • Citations: 1

“Evaluate effect of 126 pre-processing methods on various artificial intelligence models accuracy versus normal mode to predict groundwater level (case study: Hamedan-Bahar …”

  • Authors: M Saroughi, E Mirzania, M Achite, OM Katipoğlu, N Al-Ansari, …
  • Journal: Heliyon 10 (7)
  • Year: 2024
  • Citations: 0

Awards 🏆

  • Ranked 1% in Official Judicial Experts Water Exam (2024)
  • 6th in Iranian University Entrance Master Exam (2018)
  • 2nd in Provincial Chemistry Competition (2012)

Conclusion 🌍

Mohsen Saroughi is a highly competent and accomplished researcher with strengths in advanced modeling, machine learning applications, and groundwater management. His technical expertise, leadership in mentoring students, and significant contributions to both academic literature and practical tools position him as a strong candidate for the Best Researcher Award. To further enhance his impact, expanding his international collaborations and engaging in projects that directly affect societal challenges could bolster his already impressive academic and professional trajectory.

Shaojin Ma | Predictive Analytics | Best Researcher Award

Dr. Shaojin Ma | Predictive Analytics | Best Researcher Award

China Agriculture University | China

Dr. Shaojin Ma is a prominent researcher at China Agricultural University, specializing in food quality, safety, and non-destructive testing technologies. With a focus on innovative techniques like spectroscopy and laser-induced fluorescence, Ma has significantly contributed to the field of agricultural engineering. His work aims to improve food safety, quality monitoring, and processing, with particular attention to non-invasive analysis methods for food products such as grains, legumes, and peppers. He has published extensively in top-tier journals, establishing himself as a key figure in food science and agricultural engineering.

Profile

Scopus

Education

Shaojin Ma completed his higher education at China Agricultural University, where he earned his degrees in agricultural engineering. His academic background laid a solid foundation for his career in food quality control and non-destructive testing. During his studies, he developed a strong interest in the application of optical and imaging technologies for food safety and quality monitoring, which has been the core of his subsequent research and academic contributions.

Experience

Dr. Ma’s professional career includes significant research work in agricultural engineering and food science. He is currently affiliated with China Agricultural University, where he collaborates with various academic and industry experts to advance food safety technologies. Over the years, he has worked on multiple projects focused on food quality, precision agriculture, and the development of portable devices for food testing. His research has led to the development of innovative non-invasive techniques for assessing food quality, particularly in the processing and storage of fruits, vegetables, and grains.

Research Interests

Shaojin Ma’s research interests primarily revolve around the application of advanced optical and imaging technologies in the food industry. He is particularly focused on non-destructive testing methods such as LED and laser-induced fluorescence for quality control in agricultural products. Ma’s work also explores the use of spectroscopy, computer vision, and deep learning to monitor food safety and detect contaminants. His research extends to improving the efficiency and accuracy of food analysis techniques, offering practical solutions for the food processing industry.

Awards

Shaojin Ma has been recognized for his contributions to food science and engineering, receiving several awards for his innovative research. His work in non-destructive testing and food quality monitoring has earned him acclaim in both academic and industrial circles. Although specific awards are not listed, his research excellence and influential publications have positioned him as a leader in his field.

Publications

Shaojin Ma has published a selection of impactful articles in prestigious journals related to food science and agricultural engineering. His notable publications include:

Fusion of visible and fluorescence imaging through deep neural network for color value prediction of pelletized red peppers

    • Authors: Ma, S., Li, Y., Peng, Y., Wang, W., Zhang, Y.
    • Publication Year: 2024
    • Citations: 0

A portable dual-gear device for non-destructive testing on multi-quality of citrus

    • Authors: Li, Y., Wu, J., Wang, W., Ma, S.
    • Publication Year: 2023
    • Citations: 3

Rapid detection of lactic acid bacteria in yogurt based on laser-induced fluorescence

    • Authors: Ma, S., Li, Y., Peng, Y., Wang, Q.
    • Publication Year: 2023
    • Citations: 0

Toward commercial applications of LED and laser-induced fluorescence techniques for food identity, quality, and safety monitoring: A review

    • Authors: Ma, S., Li, Y., Peng, Y., Wang, W.
    • Publication Year: 2023
    • Citations: 8

Spectroscopy and computer vision techniques for noninvasive analysis of legumes: A review

    • Authors: Ma, S., Li, Y., Peng, Y.
    • Publication Year: 2023
    • Citations: 15

Design and Experiment of a Handheld Multi-Channel Discrete Spectrum Detection Device for Potato Processing Quality

    • Authors: Wang, W., Li, Y.-Y., Peng, Y.-K., Yan, S., Ma, S.-J.
    • Publication Year: 2022
    • Citations: 1

Research Progress of Rapid Optical Detection Technology and Equipment for Grain Quality

    • Authors: Nie, S., Ma, S., Peng, Y., Wang, W., Li, Y.
    • Publication Year: 2022
    • Citations: 3

Predicting ASTA color values of peppers via LED-induced fluorescence

    • Authors: Ma, S., Li, Y., Peng, Y., Yan, S., Wang, W.
    • Publication Year: 2022
    • Citations: 8

Detection of nitrofurans residues in honey using surface-enhanced Raman spectroscopy

    • Authors: Yan, S., Li, Y., Peng, Y., Ma, S., Han, D.
    • Publication Year: 2022
    • Citations: 14

An intelligent and vision-based system for Baijiu brewing-sorghum discrimination

    • Authors: Ma, S., Li, Y., Peng, Y., Yan, S., Zhao, X.
    • Publication Year: 2022
    • Citations: 8

These publications have been cited by numerous articles, reflecting their impact in the scientific community.

Conclusion

Shaojin Ma has established himself as a leading researcher in the field of agricultural engineering and food science. His work on non-destructive testing techniques has enhanced the monitoring and improvement of food quality and safety. Through his publications, he has made significant strides in the application of advanced technologies for food analysis, benefiting both the scientific community and the food industry. With a career focused on innovation and practical solutions, Dr. Ma continues to contribute to the advancement of food safety technologies, setting a high standard for future research in this domain.