Mechanical Engineering Student’s Research Shines in Seattle
Mechanical Engineering Ph.D. student, Israt Dola, who is completing her research under supervision of Dr. Robert Taylor, recently presented her technical paper entitled Evaluation of Deep Learning Architectures for Defect Detection in Fused Filament Fabrication at the Society for the Advancement of Material and Process Engineering Conference (SAMPE) in Seattle, Washington.
The presentation focused on applying deep learning models such as YOLO, Mask R-CNN, and DeepLab to detect multiple defect types within a unified framework, including cracking, warping, stringing, layer shifting, and off-platform defects.
One of the most meaningful aspects of the conference for Dola was the engagement during and after the presentation.
“I received insightful questions from attendees regarding the ongoing work and possible extensions of my research, particularly related to improving real-time implementation, expanding the dataset, and developing a predictive monitoring framework for additive manufacturing,” said Dola. “These discussions helped me think more critically about the scalability and practical application of my work in smart manufacturing environments.”
Dola also had the opportunity to connect with several peer presenters with related research, which may lead to future collaboration. Attending other technical sessions broadened her understanding of current developments in advanced manufacturing, composite materials, and defect detection techniques.
“Overall, the experience at the conference strengthened my confidence in presenting technical research, expanded my professional network, and reinforced my long-term goal of developing robust, real-time defect detection systems for additive manufacturing applications.”
