Mr. Mohammad Matin Rouhani
Mr. Mohammad Matin Rouhani
Mohammad Matin Rouhani is a geotechnical researcher and PhD student at Monash University, specialising in the intersection of rock mechanics and advanced computational intelligence. His work focuses on enhancing the efficiency and safety of underground construction and mining operations, particularly through the use of Tunnel Boring Machines (TBM).
Before joining Monash, he completed my MSc in Mining Engineering (Tunnel & Underground Spaces Engineering) at Amirkabir University of Technology (Tehran Polytechnic). There, he developed expertise in TBM performance prediction, cutter wear modelling, and cutting tool design.
Qualifications
- BSc in Mining Engineering, University of Zanjan, 2021
- MSc in Tunnel and Underground Spaces Engineering, Tehran Polytechnic, 2023
Expertise
- Programming Language
Python
- Numerical Modeling
LS-DYNA
FLAC (2D-3D)
PLAXIS (2D-3D)
Research Interests
Machine Learning and AI-related topics
Numerical Modeling (SPH, FEM, and SPG)
Laboratory Investigation of Rock Properties
Mechanized tunneling
Fracture mechanics (experimental and numerical)
Lining design and support systems
- Rouhani, M. M., Rostami, J., “Predicting disc cutter forces for hard rock TBM cutterhead modeling: a comparative analysis of modified CSM semi-theoretical model and hybrid deep learning approach”, Tunnelling and Underground Space Technology, 107448, 2026.
- Rouhani, M. M., Samimi Namin, F., Chakeri, H., “Screw Conveyor Speed Prediction for EPB-TBM Excavations Using Hybrid Deep Learning Models”, Results in Engineering, 108064, 2025.
- Rouhani, M. M., Dolatshahi, A., “Advanced Hybrid Models for Predicting Dynamic Compressive Strength of Rocks: Exploring Various Input Scenarios and Introducing Novel Empirical Approaches” , Results in Engineering, 107947, 2025.
- Rouhani, M. M., Dolatshahi, A., Hasanipanah, M., “Cerchar Abrasiveness Index Prediction Based on Rock Properties: Leveraging Hybrid Gradient Boosting Models Combined with Advanced Metaheuristic Algorithms”, Scientific Reports, 15 (1), 37499, 2025.
- Rouhani, M. M., Dolatshahi, A., “New models for estimating PTS specimen pure shear fracture toughness under confining pressure: Empirical and Machine Learning Framework” , Results in Engineering, 107418, 2025.
- Hasanipanah, M., Rouhani, M. M., Yin, X., Rezaei, M., “Prediction of Rock Blastability Index Using Rock Mechanics Properties and Advanced Machine Learning Techniques”, Rock Mechanics and Rock Engineering, 1-21, 2025.
- Rouhani, M. M., Hasanipanah, M., Dehghani, H., “Intelligent Prediction of Flyrock Hazards in Surface Mining Using Optimized Gradient Boosting Models”, Natural Resources Research, 1-23, 2025.
- Rouhani, M. M., Farrokh, E., “TBM performance prediction based on cutting forces; A case Study: Qomroud water conveyance Tunnel (Lots 3 and 4)”, Bulletin of Engineering Geology and the Environment, 84, 304, 2025.
- Rouhani, M. M., Dolatshahi, A., “Predicting Mode I Fracture Toughness of CCNBD Quasi-brittle Specimens Using Hybrid Gradient Boosting Algorithms” Theoretical and Applied Fracture Mechanics, 104966, 2025.
- Ding, X., Hasanipanah, M., Rouhani, M. M., Nguyen, T., “Hybrid CatBoost Models Optimized with Metaheuristics for Predicting Shear Strength in Rock Joints” Bulletin of Engineering Geology and the Environment, 84, 150, 2025.
- Rouhani, M. M., Farrokh, E., “ chisel bits Cutting force estimation using XGBoost and different optimization algorithms.” Computers and Geotechnics, 172, 106465, 2024.
- Samimi Namin, F., Rouhani, M. M., A review: Applications of fuzzy theory in rock Engineering,” Indian Geotechnical Journal, 2024.
- Rouhani, M. M., Samimi Namin, F., “Investigate the potential of using fuzzy similarity in decision making under uncertainty for mining projects,” Resources Policy, 86, 104087, 2023.
- Amjadi, R., Samimi Namin, F., Chakeri, H., Rouhani, M. M., “Evaluation of the effect of injection pressure on Surface Settlement in Excavation with Earth Pressure Balanced Shield Machine (Case study: Tabriz Metro Line 2)” Journal of Tunneling and Underground Space Engineering, 10(2), 167-182, 2022.