Assoc. Prof. Dr. Nasrollah Bani Mostafa Arab | manufacturing processes | Best Faculty Award

Assoc.Prof. at Shahid Rajaee Teacher Training University , Iran.

Nasrollah Bani Mostafa Arab is an esteemed Associate Professor at the Faculty of Mechanical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran 📚. With over 30 years of teaching experience and a strong research background in welding processes, manufacturing processes, and composite materials, he has established himself as a leading expert in his field 🔩.

Professional Profile

scholar

🎓 Education

– *PhD in Mechanical Engineering*: IIT Delhi, India (1993) 🎓– M.Tech. in Mechanical Engineering (Production): B.H.U., India (1988) 🎓– B.E. in Mechanical Engineering: R.E.C., Srinagar, India (1985) 🎓

💼 Experience

– *Associate Professor*: Faculty of Mechanical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran 📚– *Teaching Experience*: Over 30 years of experience in teaching mechanical engineering courses 📚– *Research Experience*: Extensive research experience in welding processes, manufacturing processes, and composite materials

🔬 Research Interests

Nasrollah Bani Mostafa Arab’s research focuses on welding processes, manufacturing processes, and composite materials 🔩. His work involves investigating the properties and applications of various materials and developing new manufacturing techniques.

🏅 Awards

– *Published over 60 journal and conference papers*: Demonstrating his expertise and contributions to the field of mechanical engineering 📄– *Translated book*: “Advanced machining processes” from English to Persian 📚– *Authored book*: “Technical English for students of production and manufactur

📚Top Noted Publications

1. Effects of friction stir welding process parameters on appearance and strength of polypropylene composite welds 📄
GH Payganeh, NBM Arab, YD Asl, FA Ghasemi, MS Boroujeni
Int. J. Phys. Sci 6 (19), 4595-4601, 2011

2. Optimization of process parameters for friction stir lap welding of carbon fibre reinforced thermoplastic composites by Taguchi method 📊
H Ahmadi, NB Mostafa Arab, FA Ghasemi
Journal of Mechanical Science and Technology 28, 279-284, 2014

3. Optimization of welding parameters for weld penetration in FCAW 🔩
NB Mostafa, MN Khajavi
Journal of achievements in materials and manufacturing engineering 16 (1-2), 2006

4. Influence of pin profile on quality of friction stir lap welds in carbon fiber reinforced polypropylene composite 🔍
H Ahmadi, NBM Arab, FA Ghasemi, RE Farsani
International Journal of Mechanics and Applications 2 (3), 24-28, 2012

5. Effects of drilling parameters on delamination of glass-epoxy composites 🌀
FA Ghasemi, A Hyvadi, G Payganeh, NBM Arab
Australian Journal of Basic and Applied Sciences 5 (12), 1433-1440, 2011

6. Mechanical and metallurgical properties of pulsed neodymium-doped yttrium aluminum garnet laser welding of dual phase steels 🔩
M Hazratinezhad, NBM Arab, AR Sufizadeh, MJ Torkamany
Materials & Design 33, 83-87, 2012

7. The systematic parameter optimization in the Nd: YAG laser beam welding of Inconel 625 🔍
MR Jelokhani-Niaraki, N B. Mostafa Arab, H Naffakh-Moosavy, …
The International Journal of Advanced Manufacturing Technology 84, 2537-2546, 2016

8. Application of response surface methodology for weld strength prediction in laser welding of polypropylene/clay nanocomposite 📊
MR Nakhaei, NB Mostafa Arab, G Naderi
Iranian Polymer Journal 22, 351-360, 2013

9. Numerical and experimental investigation of defects formation during friction stir processing on AZ91 🔍
H Agha Amini Fashami, N Bani Mostafa Arab, M Hoseinpour Gollo, …
SN Applied Sciences 3, 1-13, 2021

10. Experimental study on optimization of CO2 laser welding parameters for polypropylene-clay nanocomposite welds 🔩
MR Nakhaei, NB Mostafa Arab, G Naderi, M Hoseinpour Gollo
Journal of Mechanical Science and Technology 27, 843-848, 2013

Conclusion

Dr. Nasrollah Bani Mostafa Arab’s research experience, publication record, teaching experience, and book publications make him a strong candidate for the Best Researcher Award. With some further emphasis on international collaboration and interdisciplinary research, Dr. Arab could further solidify his position as a leading researcher in his field.

Mr. Sabum Jung | Smart factory | Best Researcher Award

Research engineer, Lg energy solution,South Korea

Sabum Jung is a seasoned Data Scientist and Machine Learning Engineer with over 23 years of expertise in predictive modeling, deep learning, and AI-driven optimization. His career spans LG Energy Solution, SK Holdings, and LG Production Engineering Research Institute, where he pioneered AI applications in high-tech manufacturing, including semiconductor, battery, and display industries. A former Military Intelligence Analyst for the U.S. Army, he has authored research papers and books on AI, machine learning, and Industry 4.0. Fluent in English, Korean, and Japanese, he continues to drive AI innovations in industrial applications.

Profile

scopus

🎓 Education

Sabum Jung holds a B.A. (3.9/4.5) and an M.S. (4.2/4.5) in Industrial Engineering from Sung Kyun Kwan University, South Korea. His academic journey focused on advanced analytics, AI-driven optimization, and industrial process improvements. His research contributions in artificial intelligence, reliability engineering, and digital transformation have shaped his expertise in machine learning, deep learning, and predictive modeling, positioning him as a leader in AI applications for manufacturing and industrial systems.

💼 Experience

Currently a Data Scientist at LG Energy Solution, Sabum Jung leads AI-driven innovations in virtual metrology, predictive maintenance, and defect analysis. Previously at SK Holdings, he optimized renewable energy predictions, semiconductor material discovery, and AI-powered industrial operations. His 20-year tenure at LG Production Engineering Research Institute saw groundbreaking work in machine learning for smart appliances, battery systems, and industrial automation. His early career as a Military Intelligence Analyst in the U.S. Army honed his analytical prowess, setting the foundation for his AI-driven problem-solving approach.

🏆 Awards & Honors

Sabum Jung has been recognized for his contributions to AI, machine learning, and industrial automation. His accolades include leadership in AI-driven manufacturing optimization, predictive maintenance, and reinforcement learning applications. He has received industry recognition for his research and innovation in deep learning, active learning, and process optimization in high-tech sectors, further cementing his influence in AI-driven industrial advancements.

🔬 Research Focus:

Sabum Jung specializes in AI applications for high-tech manufacturing, focusing on predictive maintenance, virtual metrology, and defect detection. His research spans deep learning, reinforcement learning, and AI-driven industrial process optimization. Notable contributions include renewable energy prediction, semiconductor material discovery, and advanced statistical modeling. His expertise in machine learning has been instrumental in developing AI solutions for smart manufacturing, Industry 4.0, and digital transformation.

Conclusion

Sabum Jung is a strong candidate for the Best Researcher Award, given his vast industry experience, research excellence, and technological contributions to AI and machine learning in manufacturing. Enhancing academic collaborations and increasing research dissemination could further elevate his impact and recognition.