Jan 21, 2018

Commencement Awards Honor Graduates

The School of Information’s January 2018 commencement ceremony presented an opportunity to honor both faculty and student achievements.

Dean AnnaLee Saxenian presented awards for outstanding capstone projects from the Master of Information & Data Science program, and students in the MIDS program voted for their most outstanding instructor.

Hal R. Varian MIDS Capstone Award (Summer 2017)

Machine Learning For All
Arvin Sahni, Jacky Zhang, Jason Sanchez, Nandu Menon
An easy-to-use platform for organizations to harness the power of machine learning.

Hal R. Varian MIDS Capstone Award (Fall 2017)

DeepJams: Machine Intelligence Meets Music Composition
Saif Ahmed, Andrea Pope, Byron Tang
DeepJams allows users to augment traditional music compositions with model-generated extensions. We use a neural network trained on a genre corpus to extend the gist of the user’s composition with the inspiration of a thousand others.

FlexCheck
Annie Lee, Jason Blauvelt, Motasem Salem
FlexCheck uses computer vision to help you track your progress in injury recovery or performance training. All you have to do is upload an image: FlexCheck instantly calculates, displays, and records the exact angles of your position.

Faculty Award

Distinguished Faculty Award (MIDS program):
D. Alex Hughes

This was Alex Hughes’ third consecutive MIDS Distinguished Faculty Award. He was also honored at the January 2017 and Spring 2017 commencement ceremonies.

Related

Winter Commencement: A Family Affair

The School of Information Winter Commencement ceremony on Sunday, January 21, 2018 was an emotional celebration of the 101 Summer and Fall 2017 graduates of the Master of Information and Data Science program.

DeepJams allows users to augment traditional music compositions with model-generated extensions. We use a neural network trained on a genre corpus to extend the gist of the user’s composition with the inspiration of a thousand others.
DeepJams allows users to augment traditional music compositions with model-generated extensions. We use a neural network trained on a genre corpus to extend the gist of the user’s composition with the inspiration of a thousand others.
FlexCheck uses computer vision to help you track your progress in injury recovery or performance training. All you have to do is upload an image: FlexCheck instantly calculates, displays, and records the exact angles of your position.
FlexCheck uses computer vision to help you track your progress in injury recovery or performance training. All you have to do is upload an image: FlexCheck instantly calculates, displays, and records the exact angles of your position.
Machine Learning For All is an easy-to-use platform for organizations to harness the power of machine learning.
Machine Learning For All is an easy-to-use platform for organizations to harness the power of machine learning.
Last updated: January 22, 2018