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David M

Computer vision researcher at MIT.

My previous work includes

  • Visual Reasoning, where I applied modular neural networks to achieve state-of-the-art accuracy on the CLEVR dataset, while providing interpretable model outputs.

  • Clustering by compression, where I applied computational tools approximating Kolmogorov complexity to the problem of clustering images of cosmological data for classification.

  • Semantic segmentation, where I developed a neural network architecture similar to that of U-Net to improve segmentation performance on thin objects and very large objects.

  • The Mahali Space Weater Monitoring Project, where I developed a mobile application and scientific computing framework to enable real-time data processing and collection on mobile devices.

  • Indoor Localization, where I leveraged some machine learning techniques to enable indoor localization on mobile devices.

  • Automated NMR assignment, where I applied machine learning techniques to reduce the search space of an algorithm for automatically assigning backbone protein sequences. Read the paper

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