Bangladeshi researcher Nadia Islam Tanha is conducting research on supply chain disruption and industrial resilience in the United States. She is pursuing a Doctor of Engineering in Industrial Engineering at Lamar University in Beaumont, Texas, where her work examines how manufacturers can identify hidden vulnerabilities in their supplier networks before those vulnerabilities become production failures.
Her published research primarily focuses on lean manufacturing, supply chain optimization, and the application of blockchain and Industry 4.0 technologies. Her studies examine process waste reduction, traceability across multi-tier supplier networks, and cybersecurity considerations in blockchain-enabled supply chain systems.
Nadia’s current research extends this work toward semiconductor supply chains, where she applies machine learning and network analysis to disruption prediction and recovery planning. Her doctoral research investigates how disruptions travel through interconnected supplier networks and how organizations can measure and compare mitigation strategies.
Semiconductor supply chains depend on specialized materials, fabrication capacity, substrates, and assembly and packaging operations distributed across many countries. Most organizations have limited visibility beyond their immediate suppliers, which makes deeper dependencies difficult to detect until an interruption occurs. Her research interests include multi-tier supplier visibility, critical-node identification, resilience measurement, and lean process methods.
Recent global shortages have shown how a disruption affecting a small number of facilities can reach automotive manufacturing, medical devices, telecommunications, and energy systems. Through her doctoral work, Nadia hopes to contribute analytical methods that manufacturers and researchers can adapt and reuse.
Her academic background includes degrees in Leather Engineering from the University of Dhaka and a Master of Engineering in Industrial Engineering from Lamar University. She has contributed to peer-reviewed journal and conference publications on lean manufacturing, blockchain, and human–AI interaction, and has served as a peer reviewer for an academic journal.
Nadia Islam Tanha believes that combining industrial-engineering methods with machine learning and advanced analytical techniques can support the development of smarter, more transparent, and more resilient supply chains — systems that recover faster and fail less often.
