Cracking the Code of Non-Profits

Invent:YU provides a unique forum for computer science and data science students, many whom are Jewish, to connect, brainstorm and partner together over a 24-hour period. Unlike other Hackathons, the YU Hackathon does not take place on Saturday, allowing Shabbat observing students to participate in an exciting event that generally would not be open to them.

The theme for this year's program is “Giving Back”, focusing on solving problems that non-profit organizations may face in their day to day operations.

Our Hackathon has two dual tracks: a standard Hackathon track, featuring CS/Engineering projects, and a Data Science track.

Students do not necessarily need a coding background to participate or enjoy. We are just looking for students who have an interest in science, technology, and using their minds to create.

Please see the Rules tab for more details.

View full rules

Prizes

$2,318 in prizes

Best Domain Name Registered With Domain.com

Raspberry Pi & PiHut Essential Kit

Best Use of Amazon Web Services

$250 Amazon Web Services Credit (US ONLY)

First Place Prize

$2,000 towards a Charidy Campaign

Second Place Team

1 LiteCoin (to split between team members)

Devpost Achievements

Submitting to this hackathon could earn you:

Eligibility

The event is open to students between the ages of 16-26.

Judges

Joshua Waxman

Joshua Waxman
Professor at Yeshiva University

Naomi Klamen

Naomi Klamen
Master Principal Enterprise Cloud Architect at Oracle

Dan Hazony

Dan Hazony
Director of Data and Evaluation at NCSY

Kelly Mahone

Kelly Mahone
Major League Hacking

Judging Criteria

  • Hacking Track: Problem Definition
    How precise and relevant is the real world problem or opportunity? How interesting or difficult to resolve - functionally or technically - is the problem being challenged?
  • Hacking Track: Solution Design & Innovation
    Does the application approach a new problem, or look at an old problem in a new way? Is the solution innovative or does it rely on an existing tech? To what degree does the application actually solve the problem?
  • Hacking Track: Idea Viability
    Is the application marketable? Would people use this product? Is this solution only theoretical or does it have a realistic application for commercial purposes?
  • Hacking Track: Functionality
    Does the prototype work? Is it user-friendly? Is the design visually appealing?
  • Data Analysis Track: Relevance
    How precise and relevant is the real world problem or opportunity?
  • Data Analysis Track: Value of Insight
    How valuable and relevant is the insight presented?
  • Data Analysis Track: Quality of Analysis
    How incisive is the analysis? What is the level of quality of the analysis? Does the code follow both programming and statistical rigor?
  • Data Analysis Track: Creativity