The MIT.nano Immersion Lab has tools to help researchers process multi-dimensional and multi-modal data sets, machine learning algorithms, and more. Examples include atomic-level reconstruction of proteins imaged in cryo-electron microscopes, volumetric data processing with spatial and temporal data analysis, simulation of complex computational models, and processing photogrammetry images for 3D models.
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Sample projects and research
AI for designing usable virtual assets
EECS Associate Professor Justin Solomon seeks to democratize content creation in virtual worlds by developing AI tools for designing virtual assets. In a recent project that was awarded a 2020 MIT.nano Immersion Lab Gaming Program seed grant, Solomon explores designing algorithms that learn from existing datasets of expert-created 3D models to assist non-expert users in contributing objects to 3D environments. He envisions a flexible toolbox for producing assets from high-level user guidance, with varying part structure and detail.
Related MIT centers & labs
Cryo-EM facility
Institute for Medical Engineering & Science (IMES)