Abdullah Mamun
211 C KAUFMAN HALL
NORFOLK, 23529
Research Interests
My research domain focuses on advanced manufacturing systems, with applications in smart manufacturing, data-driven artificial intelligence, and sustainable manufacturing.
Cyber-Physical Systems (CPS) in smart manufacturing systems integrate the Industrial Internet of Things (IIoTs), industrial control and monitoring systems, and Big Data analytics into manufacturing operations. The resilience of CPS enhances the safety, security, and reliability of advanced manufacturing processes.
The rapid evolution of IIoTs and advanced sensor technologies, coupled with data-driven AI, is revolutionizing smart manufacturing by moving beyond basic shop floor automation toward systems characterized by autonomous, interconnected machines enabled through advanced sensor fusion.
These objectives align with various research initiatives and funding organizations, including NSF (via CMMI), DOE-AMO, and ARO.
To enable successful on-demand smart manufacturing systems, my research focuses on:
integrating cost-effective smart sensors into existing machinery for digital transformation.
employing data-driven AI methodologies for process monitoring and optimization.
enhancing the cyber-physical resiliency of advanced manufacturing operations.