Marco Scoffier

With Yann LeCun and the Computational and Biological Learning Lab at NYU, at NetScale Technologies in Northern NJ and with other Professors at the Courant Institute at NYU including Leslie Greengard and Paolo Barbano, I have worked on several projects which apply machine-learning techniques to real world data -- from paint samples from the Metropolitan Museum to biological images of worms and mouse dendrites to 3D point-clouds of entire cities. Most recently I am working in a collaboration between the Computer Science and Economics Departments at NYU and the NY Fed on real-estate transaction data.

Real-Estate Price Prediction

Large Datasets, Ensemble Methods, Machine Learning

@ NYU

A project run by Andrew Caplin, Professor of Economics at NYU. We build a price surface which can predict the price of any house at any time. Currently we are only looking at LA County in a project about Mortgage defaults sponsored by the NY Fed

Collaborators

DARPA URGENT

Large Datasets, 3D point-clouds, LIDAR, Sensor Fusion, Machine Learning

@ Net-Scale Technologies

I was the main programmer for Net-Scale in the Net-Scale/HRL participation in the DARPA URGENT challenge. We built a stand-alone end-to-end system to which were input raw-point clouds and which produced polygonal classifications of large objects : trees, lawns, buildings, streets. The code was a C library which was linked from HRL's code base.

LAGR Program :: Videos

Autonomous Robotics, Vision, Machine Learning

@ Net-Scale/NYU

Pierre Sermanet put together this video of some clips from the last few months which aims to explain most of the elements of the system which were working together in a pretty efficient end to end system

Get the Flash Player to see this player.