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Hackathons

Hackathons are short, intense project-building events. They are useful for learning new tools, meeting teammates, creating resume projects, and practicing how to explain technical work.

Most of these are open to students from any school, not just the host university. Applications usually open one to two months before the event and close early, so the real skill is watching for them to open.

Dates last verified September 3, 2026. Hackathon dates move every year, so treat anything here as a starting point and confirm on the event's own site.

Applications for most of these are open or opening now.

Event Host Dates
HackRice Rice Sep 11-13, 2026
Hack the North Waterloo Sep 18-20, 2026
HopHacks Johns Hopkins Sep 18-20, 2026
VTHacks 14 Virginia Tech Sep 18-20, 2026
HackMIT MIT Sep 19-20, 2026
HackGT 13 Georgia Tech Sep 25-27, 2026
ShellHacks FIU Sep 25-27, 2026
BigRed//Hacks Cornell Oct 2-4, 2026
MHacks Michigan Oct 3-4, 2026
HackNC UNC Chapel Hill Oct 9-11, 2026
Knight Hacks IX UCF Oct 9-11, 2026
HackHarvard Harvard Oct 16-18, 2026
SwampHacks XII Florida Oct 16-18, 2026
Hack the Valley Toronto Scarborough Oct 16-18, 2026
DubHacks Washington Oct 17-18, 2026
LA Hacks AI Hackathon UCLA Oct 17-18, 2026
Cal Hacks 13.0 UC Berkeley Oct 23-25, 2026
HackTX 26 UT Austin Oct 24-25, 2026
HackPSU Fall Penn State Oct 24-25, 2026
SunHacks Arizona ASU November 2026, TBA
HackUTD UT Dallas Nov 7-8, 2026
HackRPI RPI Nov 7-8, 2026
HackPrinceton Fall Princeton Nov 13-15, 2026
HackUMass UMass Amherst Nov 13-15, 2026
Opportunity Hack Arizona ASU Nov 14-15, 2026
Hack Western 13 Western University Nov 20-22, 2026

Applications generally open between November and February.

Event Host Dates
DeltaHacks McMaster Jan 9-10, 2027
UofTHacks Toronto Jan 15-17, 2027
uOttaHack 9 Ottawa Jan 15-17, 2027
nwHacks UBC Jan 16-17, 2027
Hack@Brown Brown Feb 5-7, 2027
SpartaHack Michigan State Feb 6-7, 2027
TreeHacks Stanford mid-February 2027, TBA
HackNYU NYU February 2027, TBA
SF Hacks SF State Feb 19-21, 2027
HackIllinois UIUC Feb 26-28, 2027
Hacklytics Georgia Tech Feb 26-28, 2027
PennApps XXVII Penn spring 2027, TBA
Diamondhacks UC San Diego Apr 4-5, 2027
HackKU27 Kansas Apr 9-11, 2027
Bitcamp Maryland April 2027, TBA
WildHacks Northwestern April 2027, TBA
LA Hacks 27 UCLA Apr 16-18, 2027
HackDavis UC Davis spring 2027, TBA

This list is curated. MLH’s season page has the full slate of several hundred events if none of these fit your timing.

If you have never done one, start with SunHacks or Opportunity Hack here at ASU. No travel, no application stress, and the same skills transfer directly to the bigger ones. SoDA usually has people going to both — ask in the Discord.

  • Apply early. Many of the large hackathons admit on a rolling basis, so the same application is much stronger a week after it opens than a week before it closes.
  • Applications are short. Usually a resume, a link or two, and a couple of short answers about what you want to build. Write real answers rather than generic ones — organizers read a lot of these.
  • Apply as a team where allowed. Some events let you submit a team application, which can improve everyone’s odds and saves you from scrambling for teammates at the venue.
  • Ask about travel reimbursement. Big hackathons often reimburse part of the cost of getting there, sometimes only if you come with a group from the same school. Check before you book anything.
  • Being rejected means very little. Acceptance is heavily oversubscribed and partly random. Apply to several in the same season instead of pinning hopes on one.
  • Check the rules on prior work. Almost all of them require the project to be built during the event. Planning ahead is fine; pre-writing the code is not.

InnovationHacks was described as a two-day rapid software prototyping event with teams of two to four people and problem statements revealed at the event. Other hackathons vary, but the core pattern is similar: form a team, understand the prompt, build a prototype, and present it clearly.

Choosing the right teammates matters. A strong team is not just “four coders.”

Look for complementary strengths:

  • Backend or infrastructure
  • Frontend or mobile
  • Product design
  • User experience
  • Data, AI, or domain knowledge
  • Project management
  • Pitching and storytelling

Agree early on communication norms, roles, and how you will make decisions when time is short.

Do not jump straight into code. Use the 5Ws:

  • Who has the problem?
  • What job do they need done?
  • When does the problem happen?
  • Where does the solution need to work?
  • Why does this matter?

Then turn needs into requirements:

  • What must the solution do?
  • What constraints exist?
  • What would count as success?
  • What can be safely skipped for a demo?
  • What is novel, useful, or impressive about the approach?

A hackathon project should be scoped to finish. Define components and responsibilities before implementation.

Good design choices:

  • Use a stack your team can move quickly in.
  • Prefer simple architecture over clever architecture.
  • Use abstraction only where it reduces confusion.
  • Keep communication tight.
  • Pick a deployment plan early.
  • Decide what the demo path will be before building too much.

Vercel plus Supabase is a common quick stack for web apps, but use whatever your team knows well enough to ship.

  • Use version control from the start.
  • Prefer a monorepo unless there is a strong reason not to.
  • Document early so teammates and judges can understand the project.
  • Work in parallel, but integrate often.
  • Reserve time for the presentation.
  • Avoid scope creep.
  • Treat prototypes like experiments.

The presentation is part of the product. A polished pitch can beat a slightly more complete project that judges cannot understand.

For a demo, no one is usually going to use your product at production scale. Skip low-value complexity unless it is central to the prompt.

Usually skip:

  • Full authentication
  • Complex onboarding
  • Perfect settings pages
  • Overbuilt admin tools
  • Edge cases that will not appear in the demo
  • Infrastructure that does not support the story

AI tools can help with debugging, scaffolding, design ideas, and unfamiliar APIs. Treat them like fast but imperfect assistants.

Good AI use:

  • Ask for options, then choose intentionally.
  • Use AI to explain errors or unfamiliar libraries.
  • Generate boilerplate, then review it.
  • Use it to brainstorm edge cases.
  • Keep ownership of product direction and final code.

Risky AI use:

  • Letting generated code define the whole product.
  • Accepting code you cannot explain.
  • Spending more time prompting than building.
  • Shipping insecure or broken code because it looked plausible.

A good final presentation answers:

  • What problem did you choose?
  • Who is the user?
  • What did you build?
  • Why is it useful or interesting?
  • What is technically impressive?
  • What did you learn or validate?
  • What would you do next?

Show the happy path. If something is fragile, demo the part that works and explain the future plan honestly.