Sahar Ghatrehsamani | Engineering | Best Scholar Award

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Dr. Sahar Ghatrehsamani | Engineering | Best Scholar Award

Postdoctoral at Isfahan University of Technology, Iran

Dr. Sahar Ghatrehsamani is a passionate mechanical engineer specializing in tribology, with a strong background in machine learning and surface engineering. She earned her Ph.D. in Mechanical Engineering from Isfahan University of Technology (IUT), Iran (2022) and is currently a postdoctoral researcher at IUT, applying AI techniques to predict the tribological behavior of agricultural machinery. With expertise in CAD, FEA, and statistical analysis, she has contributed significantly to teaching, research, and mentoring students. Her work intersects materials science, additive manufacturing, and precision agriculture, making her a versatile and innovative researcher. πŸŒπŸ”¬

Professional Profile:

Scopus

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Education & Experience

πŸ“š Education:

  • πŸŽ“ Ph.D. in Mechanical Engineering (Tribology) – Isfahan University of Technology, Iran (2017-2022)

  • πŸŽ“ M.Sc. in Mechanical Engineering (Tribology) – Isfahan University of Technology, Iran (2015-2017)

  • πŸŽ“ B.Sc. in Mechanical Engineering (Biosystem) – Shahrekord University, Iran (2009-2013)

πŸ”¬ Experience:

  • πŸ” Postdoctoral Researcher – Isfahan University of Technology, Iran (2024-Present)

  • πŸ‘©β€πŸ« Teaching Experience – Multiple undergraduate courses in mechanical engineering at IUT (2018-Present)

  • 🀝 Co-Advisor – 2 Master’s & 6 Bachelor’s students

Professional Development

Dr. Sahar Ghatrehsamani is dedicated to research, teaching, and innovation in mechanical engineering, particularly in tribology, surface engineering, and AI-driven modeling. She has actively mentored students, guided research projects, and developed expertise in CAD, numerical simulation, and data analysis. Her teaching career at Isfahan University of Technology spans multiple engineering courses, and she has consistently ranked highly in teaching evaluations. Passionate about bridging the gap between mechanical engineering and materials science, she explores new technologies in additive manufacturing and precision agriculture to enhance sustainability and performance. πŸšœπŸ› οΈ

Research Focus

Dr. Sahar Ghatrehsamani’s research spans multiple engineering domains, focusing on:

  • 🏎️ Tribology – Studying friction, wear, and lubrication for various applications

  • 🏭 Surface Engineering – Enhancing material properties for durability and efficiency

  • πŸ€– Machine Learning & AI – Applying predictive modeling in tribological behavior and material design

  • πŸ— Mechanical Behavior of Materials – Understanding stress, strain, and failure mechanics

  • 🚜 Precision Agriculture – Developing efficient and smart agricultural machinery

  • πŸ–¨οΈ Additive Manufacturing – Investigating 3D printing & advanced manufacturing

  • πŸ“Š Data Analysis & Numerical Modeling – Integrating simulation techniques for engineering solutions

Awards & Honors

Teaching Excellence:

  • πŸŽ–οΈ Ranked 1st in Mechanical Engineering Group (2021)

  • πŸ… Ranked 2nd in College of Engineering (2021)

  • πŸ† Ranked 13th among 569 faculty members at IUT (2021)

Research Contributions:

  • πŸ“œ Published multiple high-impact research papers in tribology and AI modeling

  • 🌍 Contributed to international collaborations in mechanical engineering research

πŸš€ Her dedication to education, research, and innovation has established her as a rising expert in tribology and machine learning!

Publication Top Notes

  1. On the running-in nature of metallic tribo-components: A review

    • Authors: M.M. Khonsari, S. Ghatrehsamani, S. Akbarzadeh

    • Journal: Wear (Vol. 474, 2021)

    • Citations: 113

    • Summary: A comprehensive review of the running-in phase in metallic tribo-systems, examining the changes in friction, wear, and surface topography over time.

  2. Experimentally verified prediction of friction coefficient and wear rate during running-in dry contact

    • Authors: S. Ghatrehsamani, S. Akbarzadeh, M.M. Khonsari

    • Journal: Tribology International (Vol. 170, 2022)

    • Citations: 41

    • Summary: Experimental validation of predictive models for friction and wear rate during the running-in phase under dry contact conditions.

  3. Experimental and numerical study of the running-in wear coefficient during dry sliding contact

    • Authors: S. Ghatrehsamani, S. Akbarzadeh, M.M. Khonsari

    • Journal: Surface Topography: Metrology and Properties (Vol. 9, Issue 1, 2021)

    • Citations: 25

    • Summary: Investigates the wear coefficient during dry sliding contact using both experimental methods and numerical simulations.

  4. Predicting the wear coefficient and friction coefficient in dry point contact using continuum damage mechanics

    • Authors: S. Ghatrehsamani, S. Akbarzadeh

    • Journal: Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology (2019)

    • Citations: 23

    • Summary: Develops a predictive framework for wear and friction coefficients in dry point contact using continuum damage mechanics.

  5. Application of continuum damage mechanics to predict wear in systems subjected to variable loading

    • Authors: S. Ghatrehsamani, S. Akbarzadeh, M.M. Khonsari

    • Journal: Tribology Letters (Vol. 69, 2021)

    • Citations: 15

    • Summary: Extends continuum damage mechanics principles to predict wear in tribological systems under varying load conditions.

Conclusion

Sahar Ghatrehsamani is a strong candidate for the Best Scholar Award. Her contributions to tribology, AI-driven material predictions, and mechanical behavior research are significant. She excels in both academic and applied research, making notable interdisciplinary advancements. Given her teaching excellence, mentorship, and research output, she is highly deserving of recognition as a leading researcher in her field.