Mahmud Parvez
Assistant Professor at Khulna University Of Engineering And Technology
Based in Louisville, United States
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Seniority
Staff
Department
Education
Location
Louisville
Industry
Higher Education
Company size
973
Contact information
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m•••••••@kuet.ac.bd
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Background
About Mahmud Parvez
As an Industrial Engineering PhD candidate at the University of Louisville with a focus on Data Analytics and Operations Research, my journey has been driven by a passion for optimizing manufacturing processes and enhancing operational efficiency through innovative research and practical applications. My expertise spans across developing optimization models for the computer server manufacturing industry to maximize order assignments while minimizing energy consumption, and crafting simulation models for effective production line and warehouse layout optimization. My journey into academia was bolstered by my M.Sc. in Industrial and Systems Engineering from North Carolina A&T State University, where I conducted a significant project on a Simulation Study of Hurricane Evacuations in Eastern North Carolina. My academic and industry backgrounds merge seamlessly, highlighted by my tenure at Green Textile Limited as an Industrial Engineer, where I enhanced productivity and quality through Lean and Six Sigma methodologies and optimized supply chain processes for operational excellence. My tenure as an Assistant Professor/Lecturer at Khulna University of Engineering & Technology further honed my ability to impart knowledge and foster innovation among future engineers. Technical proficiency in programming languages like C, Python, and Java, alongside advanced skills in simulation and optimization software such as CPLEX and Simio, empowers me to tackle complex industrial challenges. My analytical prowess is matched by a creative mindset and the ability to adapt seamlessly to both independent and collaborative work environments, underscored by strong time management skills. I'm not just an engineer but a problem solver at heart, dedicated to leveraging data analytics and optimization to drive sustainable improvements in manufacturing and supply chain processes. Let's connect and explore how we can innovate and optimize the future of engineering together.
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