MHacks is a hackathon hosted by the University of Michigan every year that brings together a diverse group of students to redefine the modern perception of hackers as criminals or programming experts and to make something amazing. At this year’s MHacks 6, Wolfram was proud to be a sponsor and see our technologies in action in several of the group projects.

Last year’s winners, Olivia Walch and Matt Jacobs, returned with new teammates Sam Oliver and David Renardy as Team Fusion Furniture. Their hack, which tied for first place in Best Use of Wolfram Technology, allows users to turn photos and pictures from their phones into custom, 3D-printed tables and chairs. Team Fusion Furniture used the Wolfram Language and Wolfram Development Platform (formerly known as Wolfram Programming Cloud) to “generate, export, and email the 3D model from the images” and for other back end needs.

Tying Fusion Furniture for first place in Best Use of Wolfram Technology was Team SpeakEasy. University of Michigan students Daniel Zhang, Sarthak Bhandari, Tharun Selvakumar, Jason Brown, and Apoorva Gupta created SpeakEasy to use audio analysis to aid public-speaking skills. Using Wolfram Language machine learning functions such as Classify and image analysis, SpeakEasy compares the tone fluctuation and speaking speed of an individual reading a text with the same individual reciting it as a speech. Once the analysis is complete, SpeakEasy outputs a description of the analysis as well as advice on how to improve the speech.

The members of winning teams Fusion Furniture and SpeakEasy were awarded passes to the 2015 Wolfram Technology Conference this coming October. Two other teams, Moooooodify! and FluxDuck, took second and third place in the Wolfram category, winning one-year, developer-level subscriptions to Wolfram Development Platform.

Team Moooooodify!, comprised of Tushita Gupta, Aishwarya Premremu, and Ridlu Ruana, created an Android app using the Wolfram Language that tracks moods by analyzing the user’s outgoing texts and Facebook posts for each 24-hour period. Although it currently only identifies “happy” and “sad,” the Moooooodify! team plans to expand the emotional range in the future.

Team members Mark Gee, Mitchell Lee, and Sai Naidu of FluxDuck built an app that determines worthy companies with which to seek employment based on their reputations in the news media. Information scraped from sites like CNN Money is processed with sentiment analysis using the Wolfram Cloud API and Python to rank companies and help job seekers choose employers they would like to work for.

At least five other teams at MHacks made use of Wolfram Development Platform, the Wolfram|Alpha API, and/or the Wolfram Language. A big thanks to the University of Michigan for hosting. This was another great hackathon to attend and sponsor, and we can’t wait for the next one!

Have a hackathon on the horizon? Contact Wolfram to request our participation, or check out the resources on our hackathon page.