World's Best Scientists 2026 revealed!
Mohammadreza Koopialipoor

Mohammadreza Koopialipoor

Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
41
Citations
4235
World Ranking
630
National Ranking
29

Engineering and Technology

D-Index
43
Citations
4930
World Ranking
6341
National Ranking
89

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Mohammadreza Koopialipoor is affiliated with Amirkabir University of Technology in Iran and has contributed to research predominantly within the field of engineering, with a focus on civil and structural engineering, ocean engineering, mechanics of materials, mechanical engineering, and safety, risk, reliability, and quality.

Their recent publications include work on machine learning applications in geotechnical and structural contexts. Notable papers include:

  • Prediction of cement-based mortars compressive strength using machine learning techniques, 2021, published in Neural Computing and Applications
  • Introducing stacking machine learning approaches for the prediction of rock deformation, 2022, published in Transportation Geotechnics
  • A novel approach for classification of soils based on laboratory tests using Adaboost, Tree and ANN modeling, 2020, published in Transportation Geotechnics
  • A Novel Feature Selection Approach Based on Tree Models for Evaluating the Punching Shear Capacity of Steel Fiber-Reinforced Concrete Flat Slabs, 2020, published in Materials
  • Slope Stability Classification under Seismic Conditions Using Several Tree-Based Intelligent Techniques, 2022, published in Applied Sciences

The topics addressed in their research often revolve around:

  • Rock mechanics and modeling
  • Tunneling and rock mechanics
  • Drilling and well engineering
  • Landslides and related hazards
  • Mineral processing and grinding
  • Geotechnical engineering and analysis
  • Dam engineering and safety

Mohammadreza Koopialipoor regularly publishes in the following venues:

  • Applied Sciences
  • Transportation Geotechnics
  • Bulletin of Engineering Geology and the Environment
  • Natural Resources Research
  • Engineering With Computers

Their frequent coauthors include:

  • Danial Jahed Armaghani
  • Panagiotis G. Asteris
  • Jian Zhou
  • Binh Thai Pham
  • Ahmed Salih Mohammed

Overall, the scientist's work integrates computational techniques such as stacking machine learning, Adaboost, decision trees, and artificial neural networks to address complex problems in materials science and geotechnical engineering. Their research outputs reflect multidisciplinary approaches within engineering, focusing on the application of advanced modeling for structural and geotechnical analysis.

Best Publications

  • Prediction of cement-based mortars compressive strength using machine learning techniques

    Panagiotis G. Asteris;Mohammadreza Koopialipoor;Danial Jahed Armaghani;Evgenios A. Kotsonis

  • Application of several optimization techniques for estimating TBM advance rate in granitic rocks

    Danial Jahed Armaghani;Mohammadreza Koopialipoor;Aminaton Marto;Saffet Yagiz

  • Applying various hybrid intelligent systems to evaluate and predict slope stability under static and dynamic conditions

    Mohammadreza Koopialipoor;Danial Jahed Armaghani;Danial Jahed Armaghani;Ahmadreza Hedayat;Aminaton Marto

  • Introducing stacking machine learning approaches for the prediction of rock deformation

    Unknown

  • Three hybrid intelligent models in estimating flyrock distance resulting from blasting

    Mohammadreza Koopialipoor;Ali Fallah;Danial Jahed Armaghani;Aydin Azizi

  • Development of a new hybrid ANN for solving a geotechnical problem related to tunnel boring machine performance

    Mohammadreza Koopialipoor;Ahmad Fahimifar;Ebrahim Noroozi Ghaleini;Mohammadreza Momenzadeh

  • Predicting tunnel boring machine performance through a new model based on the group method of data handling

    Mohammadreza Koopialipoor;Sayed Sepehr Nikouei;Aminaton Marto;Ahmad Fahimifar

  • A neuro-genetic predictive model to approximate overbreak induced by drilling and blasting operation in tunnels

    Mohammadreza Koopialipoor;Danial Jahed Armaghani;Mojtaba Haghighi;Ebrahim Noroozi Ghaleini

  • Deep neural network and whale optimization algorithm to assess flyrock induced by blasting

    Hongquan Guo;Jian Zhou;Mohammadreza Koopialipoor;Danial Jahed Armaghani

  • Application of deep neural networks in predicting the penetration rate of tunnel boring machines

    Mohammadreza Koopialipoor;Hossein Tootoonchi;Danial Jahed Armaghani;Edy Tonnizam Mohamad

  • A Monte Carlo simulation approach for effective assessment of flyrock based on intelligent system of neural network

    Jian Zhou;Nasim Aghili;Nasim Aghili;Ebrahim Noroozi Ghaleini;Dieu Tien Bui

  • A combination of artificial bee colony and neural network for approximating the safety factor of retaining walls

    Ebrahim Noroozi Ghaleini;Mohammadreza Koopialipoor;Mohammadreza Momenzadeh;Mehdi Esfandi Sarafraz

  • Invasive Weed Optimization Technique-Based ANN to the Prediction of Rock Tensile Strength

    Lei Huang;Panagiotis G. Asteris;Mohammadreza Koopialipoor;Danial Jahed Armaghani

  • A Novel Feature Selection Approach Based on Tree Models for Evaluating the Punching Shear Capacity of Steel Fiber-Reinforced Concrete Flat Slabs

    Shasha Lu;Mohammadreza Koopialipoor;Panagiotis G. Asteris;Maziyar Bahri

  • A novel approach for classification of soils based on laboratory tests using Adaboost, Tree and ANN modeling

    Binh Thai Pham;Manh Duc Nguyen;Trung Nguyen-Thoi;Lanh Si Ho

  • Soft computing based closed form equations correlating L and N-type Schmidt hammer rebound numbers of rocks

    Panagiotis G. Asteris;Anna Mamou;Mohsen Hajihassani;Mahdi Hasanipanah

  • A new methodology for optimization and prediction of rate of penetration during drilling operations

    Yanru Zhao;Amin Noorbakhsh;Mohammadreza Koopialipoor;Aydin Azizi

  • Investigating the effective parameters on the risk levels of rockburst phenomena by developing a hybrid heuristic algorithm

    Jian Zhou;Hongquan Guo;Mohammadreza Koopialipoor;Danial Jahed Armaghani

  • Overbreak prediction and optimization in tunnel using neural network and bee colony techniques

    Mohammadreza Koopialipoor;Ebrahim Noroozi Ghaleini;Mojtaba Haghighi;Sujith Kanagarajan

  • Prediction of rockburst risk in underground projects developing a neuro-bee intelligent system

    Jian Zhou;Mohammadreza Koopialipoor;Enming Li;Danial Jahed Armaghani

  • Estimating and optimizing safety factors of retaining wall through neural network and bee colony techniques

    Behrouz Gordan;Mohammadreza Koopialipoor;A. Clementking;Hossein Tootoonchi

Frequent Co-Authors

Danial Jahed Armaghani
Danial Jahed Armaghani University of Technology Sydney
Mahmood Md. Tahir
Mahmood Md. Tahir University of Technology Malaysia
Edy Tonnizam Mohamad
Edy Tonnizam Mohamad University of Technology Malaysia
Panagiotis G. Asteris
Panagiotis G. Asteris School of Pedagogical and Technological Education
Aminaton Marto
Aminaton Marto University of Technology Malaysia
Mahdi Hasanipanah
Mahdi Hasanipanah Duy Tan University
Mohsen Hajihassani
Mohsen Hajihassani Urmia University
Paulo B. Lourenço
Paulo B. Lourenço University of Minho
Manoj Khandelwal
Manoj Khandelwal Federation University Australia
Dieu Tien Bui
Dieu Tien Bui University of South-Eastern Norway

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degrees in Engineering and Technology opens many diverse and flexible career options. Today’s online learning landscape covers everything from specialized technology programs to interdisciplinary degrees blending management, planning, and technical expertise.

Those interested in combining a love for sports with technical skills may find a sports management degree online appealing. It offers foundational business and leadership knowledge tailored to the world of sports, and is often available in accelerated formats.

For students drawn to optimizing and designing urban spaces, urban planning masters programs online provide affordable, flexible ways to enter this in-demand field without sacrificing work or family commitments.

Time is often a key concern—many learners seek fast-track options like a master degree in 6 months, ideal for professionals aiming to boost credentials quickly and efficiently.

Finally, students pursuing technical or engineering fields can greatly benefit from short-term certifications that pay well, supporting immediate entry into high-paying, specialized roles.

Best Scientists Citing Mohammadreza Koopialipoor

Trending Scientists