Perform computationally-intensive research

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.

Explore Immersion Lab computational processing tools using the buttons below.


Return to the capabilities page. | See all the tools.

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)