The Synaptic Building is a theoretical project of a student of Harvard Graduate School of Design, inspired by the Japanese Metabolist movement of the 20th century; seeking to incorporate spatial flexibility into the building.

Armed with data science capability and semi automated robotic technology suited to standard Factory Settings across the world, the mixed use facility building will rearrange itself as per the requirements of its community during different parts of the day.

Current resources like New York City’s open data platform and Google’s Popular Times feature show how traffic and occupancy trends can be accurately monitored, and this information can be used to predict how demand for different types of spaces changes on an hour-by-hour basis.

In the Synaptic Building, machine learning algorithms use this occupancy data to create a schedule for how the building arranges its spaces: on the ground floor, motorized retail units organize themselves to a grid in time for business hours to begin, spread themselves out to make room for restaurant seating during mealtimes, and then retract to a compact arrangement for overnight storage after the building closes. This capability is currently being used by Amazon to maximize efficiency by moving shelving units autonomously around their warehouses.

In this proposed scheme, retail stores, conference rooms and other contained spatial units are free to scurry into new positions throughout the day thanks to the open, column free floor plans created by The Synaptic Building’s unique structure. Designed to have a minimal footprint while containing vertical circulation areas and all fixed services (like plumbing, wiring, HVAC and LED lighting), the structure relies on steel vaults that rise and expand like branches of a tree to support each subsequent stacked floor plate. This design will allow new floors to be added to the top of the building over time as demand requires.

Project Lead: Stanislas Chaillou, Harvard GSD