- The paper 'Adversarial Domain Adaptation for Improved Part-to-Part Generalization of Deep Learning Segmentation Models in Aerosol Jet Printing' was accepted by the Journal of Manufacturing Sciences and Engineering.
- The paper 'Robotizing GTAW through Learning Human Response' was accepted by Welding in the World.
- The paper 'Data Quality Improvement and Geometric Information Recovery for Resistance Spot Welding with Spatial-Temporal Fast Fourier Transform' was accepted by Quality Engineering.
- The paper 'CLUMM: Contrastive Learning for Unobtrusive Motion Monitoring' was accepted by MDPI Sensors.
- The paper 'MPS-GAN: A Multi-Conditional Generative Adversarial Network for Simulating Input Parameters’ Impact on Manufacturing Processes' was accepted by the Journal of Manufacturing Processes.
- The paper 'Machine Learning–Enabled Direct Ink Writing of Conductive Polymer Composites for Enhanced Performance in Thermal Management and Current Protection' was accepted by Energy Storage Materials.
- The paper '3D X-ray Computed Tomography Image Segmentation and Point Cloud Reconstruction for Internal Defect Identification in Laser Powder Bed Fused Parts' was accepted by the Journal of Manufacturing.
Research Experience
Leads the DAIM (Data Analytics & Insights in Manufacturing) research group; involved in multiple research projects related to smart manufacturing.
Background
Research interests include developing AI and data-driven solutions to enable human-centric smart manufacturing.
Miscellany
Photo taken with Hasnaa and Pius in the lobby of ASU Technology Center (Mesa AZ, Fall 2023).