Published on by Global Scholar Awards

🌟Dr. Roohollah Shirani, Mining Engineering, Best Researcher Award🏆

  •  Doctorate at Faradonbeh Curtin University, Australia

Roohollah Shirani Faradonbeh is a highly accomplished lecturer in Mining Engineering at the WA School of Mines, Curtin University, Australia. He holds a PhD, MSc, and BSc in Mining Engineering from prestigious universities in Australia and Iran. With extensive experience in academia and industry, he has made significant contributions to the field through his research, teaching, and supervision activities. Shirani Faradonbeh’s expertise spans various areas of mining engineering, including rock mechanics, automation, sustainable mining practices, and innovative technologies.

Author Metrics

Shirani Faradonbeh’s research impact is reflected in his author metrics, including Google Scholar and Scopus citations and h-index. With a substantial number of citations and a strong h-index, he has established himself as a prominent researcher in mining engineering. His publications are widely recognized and cited within the academic community, underscoring the significance of his contributions to the field.

Scopus Profile

ORCID Profile

Google Scholar Profile

Roohollah Shirani Faradonbeh is affiliated with the WA School of Mines: Minerals, Energy and Chemical Engineering in Kalgoorlie, Australia. His Scopus Author Identifier is 56598081500. He has an ORCID profile with the identifier 0000-0002-1518-3597. As of the latest information available, he has amassed 2,216 citations from 1,296 documents. He has authored 46 documents, resulting in a h-index of 30. These metrics demonstrate his significant impact and contributions to the field of mining engineering.

Education

Roohollah Shirani Faradonbeh’s educational journey includes a Doctor of Philosophy in Mining Engineering from the University of Adelaide, Australia, where he conducted research on rock burst phenomenon prediction. He also holds a Master of Science in Mining Engineering from Tarbiat Modares University, Iran, and a Bachelor of Science in Mining Engineering from the University of Kashan, Iran. His academic achievements demonstrate a strong foundation in mining engineering and research methodology.

Research Focus

Shirani Faradonbeh’s research interests encompass a wide range of topics within mining engineering. He specializes in areas such as automation, robotics, sustainable mining practices, rock mechanics, and alternative mining methods. His work focuses on addressing challenges in deep underground mining, including rock burst prediction, ground vibration control, and sustainable mine rehabilitation. He employs experimental, numerical, and data-driven approaches to advance understanding and develop solutions for complex mining engineering problems.

Professional Journey

Throughout his career, Roohollah Shirani Faradonbeh has held various academic and industry positions. He has served as a lecturer and associate lecturer at the WA School of Mines, Curtin University, Australia, where he teaches courses on mine automation, rock mechanics, and slope engineering. Additionally, he has worked as a research and teaching assistant at several universities, including the University of Adelaide and Tarbiat Modares University. His professional journey reflects a commitment to both education and research excellence in mining engineering.

Honors & Awards

Shirani Faradonbeh’s contributions to the field of mining engineering have been recognized with several honors and awards. He has received the Dean’s Commendation for Doctoral Thesis Excellence and has been acknowledged as an outstanding reviewer for prestigious journals. He has also been the recipient of scholarships for his graduate studies and has won awards for the best conference papers. These accolades highlight his dedication to academic excellence and research impact.

Publications Top Noted & Contributions

Roohollah Shirani Faradonbeh has made significant contributions to the mining engineering literature through his research publications. He has authored numerous peer-reviewed journal papers and conference papers on topics such as rock mechanics, ground vibration prediction, and sustainable mining practices. His work has been published in reputable journals and has contributed to advancing knowledge and innovation in the field.

Forecasting blast-induced ground vibration developing a CART model

Authors: M Hasanipanah, RS Faradonbeh, HB Amnieh, DJ Armaghani, M Monjezi
Published in: Engineering with Computers, 2017
Summary: This paper introduces a CART (Classification and Regression Trees) model designed to forecast blast-induced ground vibration. By utilizing this model, the study aims to enhance understanding and prediction of the effects of quarry blasting on ground vibration. The insights provided are crucial for mitigating potential hazards associated with such activities, thereby improving safety measures in mining and quarrying operations.

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Authors: R Shirani Faradonbeh, D Jahed Armaghani, MZ Abd Majid, M Md Tahir, …
Published in: International Journal of Environmental Science and Technology, 2016
Summary: This research presents a novel model utilizing gene expression programming (GEP) to predict ground vibration resulting from quarry blasting. The model offers a robust tool for estimating peak particle velocity, thereby facilitating improved safety measures and environmental management in quarry operations. By providing accurate predictions, this model contributes significantly to minimizing the environmental impact of quarry blasting activities.

Prediction of the uniaxial compressive strength of sandstone using various modeling techniques

Authors: DJ Armaghani, MFM Amin, S Yagiz, RS Faradonbeh, RA Abdullah
Published in: International Journal of Rock Mechanics and Mining Sciences, 2016
Summary: This study investigates multiple modeling techniques for predicting the uniaxial compressive strength (UCS) of sandstone. By comparing different methods, the research offers valuable insights into the strength properties of sandstone formations. Understanding UCS is critical for various engineering and construction applications, and the findings of this study provide essential information for optimizing design and construction processes in sandstone-rich regions.

Combination of neural network and ant colony optimization algorithms for prediction and optimization of flyrock and back-break induced by blasting

Authors: A Saghatforoush, M Monjezi, R Shirani Faradonbeh, D Jahed Armaghani
Published in: Engineering with Computers, 2016
Summary: This paper proposes a hybrid model that integrates neural network and ant colony optimization algorithms to predict and optimize flyrock and back-break induced by blasting activities. By combining these advanced computational techniques, the model offers a sophisticated approach to enhance blasting efficiency while minimizing adverse effects on the surrounding environment. The findings provide valuable insights for optimizing blasting operations in mining and construction projects.

Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques

Authors: R Shirani Faradonbeh, A Taheri
Published in: Engineering with Computers, 2019
Summary: This study employs three robust data mining techniques for the long-term prediction of rockburst hazards in deep underground openings. Leveraging advanced computational methods, the research contributes to improved safety measures and risk management strategies in underground mining operations. By providing reliable predictions of rockburst hazards, this study aids in enhancing safety protocols and mitigating the risks associated with underground mining activities.

Research Timeline

Shirani Faradonbeh’s research timeline illustrates his progression and achievements throughout his academic and professional career. From his doctoral studies to his current role as a lecturer, he has been actively engaged in research, teaching, and supervision activities. His timeline reflects a continuous commitment to advancing knowledge and addressing key challenges in mining engineering through rigorous research and academic excellence.

Roohollah Shirani | Mining Engineering | Best Researcher Award

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