Md Abdul Quddus
Bio
Dr. Md Abdul Quddus is an Assistant Professor in the Department of Textile Engineering, Chemistry and Science at NC State University. He also serves as an Associate Faculty in the Operations Research Graduate Program at NC State University. He received his Ph.D. in industrial & systems engineering from Mississippi State University in Starkville, Mississippi. He pursued the master’s program in industrial engineering at Lamar University in Beaumont, Texas, and holds B.Sc. degree in industrial & production engineering from Khulna University of Engineering & Technology, Bangladesh. He served as an assistant professor in industrial & systems engineering in the Department of Engineering & Technology at Southeast Missouri State University. He also has over five years of experience at FedEx Express as a Senior Operations Research Advisor, where he worked on various logistics research projects.
His research focuses on supply chain and logistics, big data analytics, stochastic programming, geospatial analytics for optimization, and simulation. Furthermore, his specialties also include on the application of AI, deep learning, cloud computing, and operations research techniques to solve large scale supply chain network and risk management problems, and sustainable manufacturing.
Quddus’s publications have appeared in journals such as Transportation Research Part E, International Journal of Production Economics, Expert Systems with Applications, Applied Energy, Annals of Operations Research, and several conference proceedings. He is a member of the Institute for Operations Research and the Management Sciences (INFORMS) and the Institute of Industrial and Systems Engineers (IISE).
Research
- Supply chain and logistics
- Big data analytics and data science
- Cloud computing and high performance computing
- Operations research
- Geospatial analytics for optimization
- Simulation
Additional information on the Supply Chain Data Science Lab’s website.
Organizations
- Association for Supply Chain Management (ASCM)
- Institute for Operations Research and the Management Sciences (INFORMS)
- Institute of Industrial & Systems Engineers (IISE)
Teaching
- TT 486 – Supply Chain Management in the Textile Industry, Fall 2024, Spring 2026
- TT 480 – Operations Management Decisions for Textiles, Fall 2025
Education
Ph.D. Industrial & Systems Engineering Mississippi State University, MS, USA 2018
MS Industrial Engineering Lamar University, TX, USA 2015
BS Industrial & Production Engineering Khulna University of Engineering and Technology, Khulna, Bangladesh 2011
Grants
During continuous dyeing, the final shade does not match target shade. Looking to leverage AI/ML to predict adds to dyebath upstream to get final shade to CIE ��E2000 < 0.8. Factors that could affect final share: fabric properties (fiber properties, yarn properties, fabric construction), wet pickup, dye strength, machine parameters, and dye formulation. Machine Learning is heavily dependent on data to train and validate models. The first stage is to design a data acquisition system that will collate data from varies sensors in the continuous dyeing process. (See Figure 1) into a central relational database.
This proposal aims to investigate the economic viability and policy strategies for sustainable transportation in hemp supply chains, specifically focusing on hemp fibers for textiles and construction materials. By applying principles of industrial ecology, the study seeks to enhance cost-effectiveness and reduce environmental impacts. This research will use a lifecycle approach to examine hemp transportation, offering insights into optimized logistics, resource reuse, and policy recommendations for sustainable growth in the hemp industry.