Physical Computing Design Tools
Interactive Demo 1: Assembler Control Interactive Demo 2: Voxel Simuation Interactive Demo 3: Convolutional Neural Network The Physical Computing Design tool is an integrated design tool for the design, simulation, optimization and fabrication of reconfigurable computing systems. Traditional electronics design workflows follow a sequential linear process that starts with design, then analysis and simulation, and finally system fabrication and testing. Often these stages are executed independently from each other, using different tools, making it hard to translate the feedback from the simulation or testing stages into viable design amendments. This adds considerable inefficiency to an inherently iterative design workflow. As an alternative, I developed an integrated, closed loop DICE design tool where one can design, simulate, optimize and fabricate re-configurable computing systems. This novel integrated design workflow paves the way for the design of discrete integrated circuits but also reconfigurable computing systems that can change and evolve while execution as needed. CBA | Under Development | Individual Physical Computing Design Tools Graduate, PhD MetaVoxels Graduate, PhD
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MetaVoxels
Tools for the design and simulation of metavoxels (mechanical meta-material/voxel lattice structures). Interactive Demo 1: Tendons Modeling Interactive Demo 2: Rover Interactive Demo 3: Chiral Voxel Interactive Demo 4: 5*5 Voxel Lattice CBA | Currently under development | Individual Physical Computing Design Tools Graduate, PhD MetaVoxels Graduate, PhD
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Swarm Assembly
Link to MIT News Article: Assembler robots make large structures from little pieces Link to Paper: Material-Robot System for Assembly of Discrete Cellular Structures Link to Detailed Documentation and Interactive Demo Research on the inverse kinematics, path planning and control of a swarm of relative robots to assemble discrete digital material. CBA | Spring 2019 | Individual Physical Computing Design Tools Graduate, PhD MetaVoxels Graduate, PhD
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COVID Paticle Simulator
Link for Online Interactive Demo. This is an interactive visualization to help people understand how different parameters affect the spread of COVID 19. The simulation has 100,000 particles moving either randomly (or only going to central location), and using the GPU to massively parallelized the computation and visualization of the spread of the disease. On the top left, one could change some parameters like the percentage of people infected at the start of the pandemic, the infection probability given you are at close distance with an infected person, radius where the disease can be transmitted as well as how much time it takes until the symptoms appear. One can also change policies like being quarantined (only a small percentage of the population can move around). At the bottom of the screen a SIR (susceptible-infected-removed) model is calculated to see the total infected vs time and see the efficacy of different strategies when dealing with the pandemic. CBA| Spring 2020 | Individual Physical Computing Design Tools Graduate, PhD MetaVoxels Graduate, PhD
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