INTRODUCTION
Shah Murtoza Morshed is a distinguished academic and researcher specializing in industrial engineering and machine learning. Currently serving as a Lecturer at Ahsanullah University of Science and Technology (AUST) in Dhaka, Bangladesh, he has made significant contributions to the fields of machine learning, sustainable supply chain management, and decision analysis.
EARLY ACADEMIC PURSUITS
Mr. Morshed completed his Bachelor of Science in Industrial and Production Engineering at AUST, where he graduated with honors, receiving the Dean’s Honor Award in 2022. His academic journey was marked by a strong focus on operations research, supply chain management, and quality control.
PROFESSIONAL ENDEAVORS
In May 2022, Mr. Morshed commenced his role as a Lecturer in the Department of Mechanical and Production Engineering at AUST. Prior to this, he served as an Adjunct Lecturer at the same institution from February to May 2022. His teaching portfolio includes courses such as Production Planning and Control, Ergonomics and Productivity Engineering, and Industrial Management.
CONTRIBUTIONS AND RESEARCH FOCUS ON Climate Change
In May 2022, Mr. Morshed commenced his role as a Lecturer in the Department of Mechanical and Production Engineering at AUST. Prior to this, he served as an Adjunct Lecturer at the same institution from February to May 2022. His teaching portfolio includes courses such as Production Planning and Control, Ergonomics and Productivity Engineering, and Industrial Management.
IMPACT AND INFLUENCE
Through his research, Mr. Morshed has significantly influenced the integration of machine learning techniques in industrial applications. His studies on lean manufacturing drivers to enhance circular economy performance in the pharmaceutical industry have provided valuable insights into sustainable industrial practices.
ACADEMIC CITATIONS AND PUBLICATIONS
Mr. Morshed has an impressive portfolio of publications, with his work being cited over 80 times. His research papers cover topics such as sustainable supply chain management, decision analysis, and the application of machine learning in industrial settings.
HONORS & AWARDS
- Dean’s Honor Award from AUST in 2022.
- Best Paper Award at the 17th Annual Paper Meet, Mechanical Engineering Division, Institution of Engineers, Bangladesh (IEB), in 2023
LEGACY AND FUTURE CONTRIBUTIONS
As he continues his career, Mr. Morshed is poised to further influence the fields of industrial engineering and machine learning. His ongoing research and commitment to education are expected to yield significant contributions to sustainable industrial practices and the integration of advanced analytics in engineering.
FINAL NOTE
Mr. Morshed’s dedication to advancing industrial engineering through innovative research and teaching has established him as a prominent figure in his field. His interdisciplinary approach bridges the gap between traditional industrial practices and modern technological advancements.
NOTABLE PUBLICATIONS
Environmental, Economical and Technological Analysis of MQL-Assisted Machining of Al-Mg-Zr Alloy Using PCD Tool
- Authors: M. Karim, J.B. Tariq, S.M. Morshed, S.H. Shawon, A. Hasan, C. Prakash, et al.
- Journal: Sustainability
- Year: 2021
Barriers to Achieving Sustainability in Pharmaceutical Supply Chains in the Post-COVID-19 Era
- Authors: S.A. Liza, N.R. Chowdhury, S.K. Paul, M. Morshed, S.M. Morshed, et al.
- Journal: International Journal of Emerging Markets
- Year: 2023
A Pythagorean Fuzzy Approach to Evaluate the Challenges to Implementing Circular Economy in the Glass Manufacturing Industry: Implications for Sustainable Development
- Authors: Z.N. Tushar, S.M. Morshed, A. Ahsan, S. Sarkar, A.B.M.M. Bari, A.R.M.T. Islam
- Journal: Results in Engineering
- Year: 2024
Exploring the Challenges to Cope with Ripple Effects in the Perishable Food Supply Chain Considering Recent Disruptions: Implications for Urban Supply Chain Resilience
- Authors: R. Al Aziz, M.H. Arman, C.L. Karmaker, S.M. Morshed, A.B.M.M. Bari, et al.
- Journal: Journal of Open Innovation: Technology, Market, and Complexity
- Year: 2025
Exploring Lean Manufacturing Drivers for Enhancing Circular Economy Performance in the Pharmaceutical Industry: A Bayesian Best–Worst Approach
- Authors: S. Salman, S.M. Morshed, M.R. Karim, R. Rahman, S. Hasanat, A. Ahsan
- Journal: International Journal of Industrial Engineering and Operations Management
- Year: 2024