New Machine Learning Examples with LunchBoxML

Last year, we introduced LunchBoxML - a machine learning (ML) plugin for Grasshopper and Dynamo that uses the Accord framework. LunchBoxML introduces several generalized supervised and unsupervised learning tools to visual programming including regression analysis, neural networks, and mixture models. We have published a few new examples to the Bitbucket repository to demonstrate the application … Continue reading New Machine Learning Examples with LunchBoxML

Transform your Building Information into a Big Data Resource

We have recently created a database framework called Minecart which harvests data from building information sources such as Revit and IFC formats. Our database is designed to represent building information as a scalable relational structure connecting data across multiple projects, documents, elements, and parameters.

LunchBoxML for Dynamo

This past summer, we released LunchBoxML for Grasshopper. Many have asked if we would publish a version for Dynamo. Ask no more! As of the last update, we have included the first version of LunchBoxML for Dynamo! By having this capability in Dynamo, users are able to start leveraging data from Revit to feed the … Continue reading LunchBoxML for Dynamo

We’re Presenting New Research at ACADIA!

I am happy to announce that our paper "A Novel Mesh-based Workflow for Complex Geometry in BIM" has been accepted to ACADIA's 2017 conference: "Disciplines and Disruptions." hosted by MIT! The paper, co-authored by Dave Stasiuk and I, will be included in the peer-reviewed research proceedings. The research builds upon our recent work in utilizing … Continue reading We’re Presenting New Research at ACADIA!