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Interdisciplinary AI Challenge

Bring Different Minds Together. Solve a Real Problem.

What happens when people from different disciplines come together to tackle the same problem?

Express Your Interest

About the Challenge

The CARE conference 2026 Interdisciplinary AI Challenge brings students and early-career researchers together to work on real-world problem statements using AI. You will form a team, bring different perspectives to the table, build and test a solution, and present your work to a panel of experts.

You don't need to come from a particular discipline, and you don't need to be an experienced AI practitioner. What matters is your willingness to collaborate, experiment and solve problems together.

Find your team. Take on the problem. Build something that matters.

Why Take the Challenge?

The most interesting AI problems rarely belong to one discipline. The Challenge gives you an opportunity to:

  • Work on a real-world problem rather than a purely theoretical exercise.
  • Build a multidisciplinary team and learn how different perspectives can lead to better solutions.
  • Put AI into practice, from understanding the problem through to designing, testing and refining your solution.
  • Learn from mentors and researchers who can help you question assumptions and strengthen your approach.
  • Work alongside peers from different backgrounds, expanding both your technical and problem-solving perspective.
  • Present your solution to experts and explain not just what you built, but why it works and where it could go next.
  • Be recognised for outstanding work, with awards and prizes for standout teams.

Whether you are an experienced AI practitioner or exploring AI for the first time, the Challenge is designed to reward curiosity, creativity and collaboration.

Who Can Participate?

The Challenge is open to students and early-career researchers. We particularly encourage teams that bring together people from different disciplines, backgrounds and areas of expertise.

You might be a data science, AI, or computer science student working with someone from engineering, healthcare, design, mathematics, social sciences or another field. Your different perspectives are part of the advantage.

New to AI? You are welcome. Experienced? Bring your expertise.

The strongest teams won't necessarily be the ones with the most technical experience. They'll be the ones that can understand the problem, work well together and turn different ideas into a practical solution.

How It Works

1

Get the Problem

Challenge problem statements will be released in September 2026. Each will focus on a real-world problem that can benefit from an AI-driven approach.

2

Build Your Team

Form a team of students and early-career researchers. We encourage teams to bring together people with multidisciplinary skills and perspectives.

3

Build & Test

Work together to understand the problem, develop your approach and test your solution, with opportunities to learn from mentors and researchers connected with CARE.

4

Present Your Solution

The challenge culminates at CARE conference 2026, where selected teams present their solutions to a panel of experts and respond to questions.

What Are We Looking For?

There is no single formula for a successful solution. We will be looking for teams that can demonstrate:

  • Problem understanding — Have you understood the challenge and the people or context behind it?
  • Technical thinking — Is your AI approach appropriate, thoughtful and well implemented?
  • Creativity — Have you found an interesting or innovative way to approach the problem?
  • Practical impact — Could your solution make a meaningful difference if developed further?
  • Teamwork — Have you made effective use of the different skills and perspectives within your team?

Ready to Take on the Challenge?

You don't have to solve the problem alone. Find people who think differently from you. Bring your skills, your questions and your ideas. Then see what you can build together. Form your team. Take on the challenge. Build something worth talking about.