Jack Hidary


Jack Hidary is a technology researcher and entrepreneur. Hidary has collaborated with MIT on a series of papers focused on deep learning. In particular, the papers address the generalization of deep learning networks. Hidary is also the author of Quantum Computing: An Applied Approach.

Entrepreneurial career

Jack Hidary has been a vocal proponent of renewable energy. He is a trustee of the X Prize Foundation and the co-founder of the Auto X Prize, which inspired the development of highly fuel-efficient vehicles.
Hidary has served as a partner or trustee for numerous New York City groups, including the Partnership for New York City and the Citizens Budget Commission.
He has served on several boards including the advisory council for the National Renewable Energy Lab. He is on the board of the X Prize Foundation.
Hidary was born at the Brookdale Hospital in the Brownsville section of Brooklyn

Politics

On July 17, 2013, Hidary announced his intent to run as an independent on a new party line called the Jobs and Education Party for New York City Mayor and succeed Michael Bloomberg. The New York Times described his political leanings as "socially progressive, fiscally reserved, and digitally savvy," and his primary goals are to better education, foster small business growth and spur employment across all boroughs, and attract companies and investment to New York. One of his primary initiatives is to increase productivity by wiring all of the city’s schools, businesses and neighborhoods for broadband Internet service. Another focus is to increase the number of tech incubators and shared workspaces across the city.
On November 5, Jack Hidary lost to Bill de Blasio in the Mayoral Election.

Education

Hidary studied philosophy and neuroscience at Columbia University and was awarded a Stanley Fellowship in Clinical Neuroscience at the National Institutes of Health. At NIH, Hidary focused on functional MRI studies of brain function and the application of neural network technologies to the analysis and modelling of fMRI imaging data and brain function.