The School of Information’s 2016 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 the Master of Information Management & Systems program.
Students voted on their most outstanding instructors in both the MIMS & MIDS programs, and MIDS students also gave awards to their classmates.
In addition, awards for the best videos of 2016 MIMS Final Projects were presented at Thursday evening’s project showcase.
James R. Chen Award for Outstanding MIMS Final Project
Track 1: User-Centered Design
Pi-Tan Hu, Wenqin Chen
Advisor: John Chuang
Through user research we observed many blind smartphone users experienced difficulties navigating their phones and a voice user interface (VUI) could make navigation easier. We created two VUI mobile applications that explored blind user friendly designs and built a web-based development tool that help people create VUIs with ease.
Track 2: Online Sharing & Collaboration
Mohammad Hossein Ghasemzadeh, Samudra Bhuyan
Advisor: Steven Weber
CardStak bridges your offline network to your online network. Create Staks for various engagements (events, projects, classes) and allow people to know one-another and communicate.
Track 3: Platforms & Connections
Et al. Health
Ricky Holtz, John Semerdjian, Ellen Van Wyk, Bill Chambers
Advisor: Marti Hearst
People diagnosed with a rare diseases often have a lot of trouble finding a doctor who can effectively care for them. Et al. Health solves this problem by providing honest, accurate, and friendly information about physicians who study rare diseases, and other associated information.
Hal R. Varian MIDS Capstone Award
Fantasy Football Waiver Coach
Ross Boberg, Kevin Allen, Shelly Stanley, Younghak Jang
We use advanced statistical methods based on extensive historical data to predict player performance. Using probability distributions, we show how likely a player is to exceed or fall short of expectations.
Tom Kunicki, Ryan Chamberlain, Janak Mayer, Charles Maalouf
Tomographica is an artificial intelligence tool for radiologists. With higher sensitivity and fewer false-positives than any offering currently on the market, we can automatically detect lung nodules in thoracic CT scans.
Soybean Yield Prediction: Using Satellite Imagery to Predict Commodity Yields
Amitava Das, Zhengyu (Taylor) Ma, Marguerite Oneto, Sheraz Shere, Jasmine Tianjiao Qi
Assess the power of satellite images combined with weather data to predict yields and to do a comparative analysis of modeling strategies.
Distinguished Faculty Award (MIMS program):
Distinguished Faculty Award (MIDS program):
MIMS Student Awards
(Presented by the Information Management Student Association)
Student with the Most Spirit: