Hanan Samadi | Geotechnics | Excellence in Research Award

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Ms. Hanan Samadi | Geotechnics | Excellence in Research Award

Master of science in the filed of engineering geology, University of Tehran, Iran

Ms. Hanan Samadi is an emerging scholar in the field of geotechnical engineering, specializing in tunneling and underground structures. With a robust academic background and significant contributions to research in machine learning applications in geotechnics, she has established herself as a promising expert in her field.

🎓 Education:

Ms. Samadi obtained her M.Sc. in Engineering Geology from the University of Tehran in 2021, where she graduated with a stellar GPA of 4.0/4.0 for her major. Her thesis, supervised by Dr. Jafar Hassanpour and Dr. Jamal Rostami, focused on the use of artificial intelligence to investigate EPB operating parameters. She completed her B.Sc. in Geology Science from Payame Noor University in 2018.

👨‍🏫 Experience:

Ms. Samadi has served as a course mentor and workshop mentor at various prestigious institutions, including Amirkabir University, Shahid Beheshti University, and the Iranian Mining Engineering Organization. Her mentorship has covered topics such as machine learning in tunneling, mechanized excavation, and the application of artificial neural networks in construction.

🔬 Research Interests:

Her research interests encompass tunneling, mechanized excavation, rock mechanics, soil mechanics, and geotechnics. She is particularly focused on developing machine learning and deep learning algorithms to enhance geotechnical and tunneling processes.

🏆 Awards:

Ms. Samadi has received numerous accolades, including the Young Scientists Festival award for developing new tunneling software and multiple scholarships for her academic achievements. She was also recognized for her exceptional thesis at the University of Tehran.

📚 Publications Top Notes:

Estimation of settlement of pile group in clay using soft computing techniques, Geotechnical and Geological Engineering, 2024. Cited by 28.

Maximum surface settlement prediction in EPB TBM tunneling using soft computing techniques, Journal of Physics: Conference Series, 2021. Cited by 14.

Tunnel wall convergence prediction using optimized LSTM deep neural network, Geomech and Eng, 2022. Cited by 7.

Developing the empirical models for predicting the EPB operating parameters in strong Limestone, Iranian Journal of Engineering Geology, 2022. Cited by 6.

Soil Classification Modelling Using Machine Learning Methods, CCITAI, 2022. Cited by 5.

Utilization of rock mass parameters for performance prediction of rock TBMs using machine learning algorithms (publication details incomplete).

Hanan Samad | Geotechnics | Women Researcher Award

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Ms. Hanan Samad | Geotechnics | Women Researcher Award

Research assistant in the field of tunnelling and mechanized excavation, University of Tehran, Iran

 

Hanan Samadi is a distinguished researcher and engineer specializing in tunneling, mechanized excavation, and geotechnical engineering. With a robust academic background and numerous publications in leading journals, she has made significant contributions to the field of mining and geoscience. Currently, she serves as a Research Associate at Nazarbayev University in Astana, Kazakhstan, and continues to push the boundaries of her field with innovative research and practical solutions.

Profile

Google Scholar

Education 🎓

Hanan Samadi obtained her M.S. in Engineering Geology from the University of Tehran, where she graduated with an outstanding thesis on EPB Operating Parameters, achieving a perfect score of 4/4. She also holds a B.S. in Geology Science from Payame Noor University, Kurdistan, and a Diploma in Experimental Science from Sadegh Vaziri High School, where she excelled academically.

Experience 💼

Hanan has extensive experience in both academia and industry. She is currently a Research Associate at Nazarbayev University and a Senior Researcher at the University of Halabja. She has also held positions as a Research Assistant at the University of Tehran and Amirkabir University of Technology. Her professional journey is marked by significant contributions to the development and application of advanced tunneling technologies.

Research Interests 🔍

Hanan’s research interests include:

  • Tunneling and mechanized excavation (TBM)
  • Rock mechanics and rock engineering
  • Soil mechanics and geotechnics
  • Mechanics of tunnel boring machines (shield TBM, Slurry, EPB, Gripper TBM, etc.)

Awards 🏆

Hanan has been recognized for her exceptional contributions with several awards, including the 4th INNOMINE Festival Scholarship Award and Winner titles for her innovations in underground space utilization and tunneling software. She has also been honored as the Best Thesis Project Candidate at the University of Tehran and received numerous scholarships for her academic excellence.

Publications Top Notes📝

  1. Computing machinery techniques for performance prediction of TBM using rock geomechanical data in sedimentary and volcanic formations
  2. Prediction of Engineering Characteristics of Rock Masses Using Actual TBM Performance Data with Supervised and Unsupervised Learning Algorithms (a Case Study in Strong to Very Strong Igneous and Pyroclastic Rocks)
  3. In-depth exploration of machine learning algorithms for predicting sidewall displacement in underground caverns
  4. Application of several fuzzy-based techniques for estimating tunnel boring machine performance in metamorphic rocks
  5. Application of machine learning algorithms to predict the effective fracture toughness of several types of concrete
    • Published in Computers and Concrete, 2024.