• Dates? On-Campus Hackathon runs from October 16 @ 3 PM to October 17 @ 3 PM EST.
  • On-Campus Hackathon Submission Deadline:
    • due at October 17, 1 PM EST sharp.
    • Presentation Session: October 17, 2-3 PM.
  • Distance Learning Hackathon Submission Deadline:
    • due October 23, 3 PM

• Who can participate? All team members must be (1) enrolled Cornell students and (2a) in the Systems Engineering MEng program OR (2b) enrolled in SYSEN 5300 / MAE 5390.

  • Team members must all be competing in the same hackathon (eg. all in on-campus hackathon or all in DL challenge.)

• Do I need Six Sigma experience? No. Trainings are provided during the event, and many of the analyses can be learned in a few minutes. The course textbook is open to everyone.

• Do I have to be a coding wizard? No. Some prior experience in R or Python is enough, and AI assistants close a lot of the gap. A winning project is a smart, correct solution to a quality-control problem — not fancy code.

• What if I can't find team members? Sign up anyway; We will match you with a team. It's a good way to meet people in the program.

• What do I need to make? A working prototype you can demo at the end.

• What software do I need? Install R or Python and at least one coding interface (RStudio, VSCode, Cursor, Positron, ...) before you arrive. If you plan to use an AI assistant, set it up beforehand too.

• How do we share our final product? A public GitHub repository, submitted through Devpost. At least one team member needs a working (non-Cornell) GitHub account.

• What language should I use? R, Python, or both. Code must be fully reproducible and public.

• What skills help? Writing functions, building a package, using GitHub, statistical analysis, reliability analysis, Six Sigma techniques, building or querying an API, building a dashboard.

• How are products evaluated? See the criteria: tool implementation (50), tool design (15), documentation (35).

On-Campus Hackathon Questions

• Do I have to participate the whole 24 hours? You do you — a successful team works most of it. Stagger breaks across team members.

• Can I step out? Sleep? Work from a coffee shop? Yes, yes, and yes. Try to keep someone on the team present. You can of course work as a team elsewhere, but space is provided in Upson Hall.

• Can a teammate join remotely? No. All team members attend in person.

All projects will receive a 🏅 score of 0 to 100 from the event staff, based on the following criteria:

🧱 Tool Implementation (50 pts)

How well does this tool perform its intended function?

• (25 pts) 🧰 An effective, working tool - eg. does it run?
• (25 pts) 📊 Performs valid analyses relevant to quality control in R or Python --> eg. does it make sense?

🧭 Tool Design (25 pts)

How well does this tool meet the needs of stakeholders?

• (5 pts) 🔍 Scope of tool/product closely matches one of the prompts.
• (5 pts) 💡 The product should have a clear user and use case in mind.
• (5 pts) 🔢 Requires a minimal, reasonable number of inputs or requirements from the user/customer. For example, requiring the customer to know traits and values about their product that they are unlikely to be able to measure is not helpful and should be avoided.
• (10 pts) A clear demonstration of the tool, using test datasets.

📑 Tool Documentation (25 pts)

How polished and ready is this tool for public use?

• (10 pts) Excellent, easy-to-follow documentation for the tool - how does each function work, what are the inputs, parameters, etc.
• (5 pts) 2-3 accurate, working test datasets
• (5 pts) A codebook and README for your datasets, describing what each file and variable means, and any other background information necessary for collecting this data.
• (5 pts) Fully reproducible code, posted publicly to a Github Repository,