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
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)