13 citations · 13 across the 6 of their papers we have counts for
6 papers
Linking heterogeneous microstructure informatics with expert characterization knowledge through customized and hybrid vision-language representations for industrial qualification
Mutahar Safdar, Gentry Wood, Max Zimmermann +3
Rapid and reliable qualification of advanced materials remains a bottleneck in industrial manufacturing, particularly for heterogeneous structures produced via non-conventional add…
Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing
Jiarui Xie, Mutahar Safdar, Lequn Chen +2
Various machine learning (ML)-based in-situ monitoring systems have been developed to detect anomalies and defects in laser additive manufacturing (LAM) processes. While multimodal…
Human-artificial intelligence teaming for scientific information extraction from data-driven additive manufacturing research using large language models
Mutahar Safdar, Jiarui Xie, Andrei Mircea +1
Data-driven research in Additive Manufacturing (AM) has gained significant success in recent years. This has led to a plethora of scientific literature to emerge. The knowledge in…
Towards reproducible machine learning-based process monitoring and quality prediction research for additive manufacturing
Jiarui Xie, Mutahar Safdar, Andrei Mircea +5
Machine learning (ML)-based cyber-physical systems (CPSs) have been extensively developed to improve the print quality of additive manufacturing (AM). However, the reproducibility…
Transferability analysis of data-driven additive manufacturing knowledge: a case study between powder bed fusion and directed energy deposition
Mutahar Safdar, Jiarui Xie, Hyunwoong Ko +3
Data-driven research in Additive Manufacturing (AM) has gained significant success in recent years. This has led to a plethora of scientific literature to emerge. The knowledge in…
Evaluation of Key Spatiotemporal Learners for Print Track Anomaly Classification Using Melt Pool Image Streams
Lynn Cherif, Mutahar Safdar, Guy Lamouche +6
Recent applications of machine learning in metal additive manufacturing (MAM) have demonstrated significant potential in addressing critical barriers to the widespread adoption of…