I am interested in 3D generative models, self-supervised learning, score-based models, graph neural networks, multi-task learning, and leveraging sparse priors for 3D reconstruction. I draw inspiration from intelligence in humans and nature while I attempt to solve multidisciplinary problems using machine learning. My goal is to develop advanced design tools, allowing intelligent agents to understand and improve existing 2D and 3D designs made by humans.

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    Data Augmentation of Engineering Drawings for Data-Driven Component Segmentation
    IDETC-CIE, 2022
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    Flaw Detection in Metal Additive Manufacturing Using Deep Learned Acoustic Features
    ML4Eng @ NeurIPS, 2020