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INTRODUCTION

New York University Shanghai Digital Innovation Challenge (NYUSHDIC) is a tech-based innovation competition hosted by a student organization NYUSH Digital Innovation Community. Students from NYUSH and other universities are welcome to form cross-disciplinary teams, utilize cutting-edge digital technology, and pitch innovative ideas to address real-world problems. This year, with the competition theme ā€œDigital Innovation Empowering Personalized Educationā€, NYUSHDIC collaborates with NYUSH Computer Science, Data Science and Engineering, and Frontiers Science Center of Artificial Intelligence and Deep Learning.

Different from previous years, we hope to use the mode of participation of enterprises in some selected groups to make the studentsā€™ projects closer to industrial reality, so that the studentsā€™ projects are not only restricted to the competition, but also a project that can allow them to continue to internship or other forms of in-depth cooperation with enterprises after the competition, and to make the project a project that can be landed and can produce social value. We aim to empower our participants to explore the vast creative possibilities in some tracks designed by some enterprises, apply their computer science skills to develop impactful solutions, and acquire invaluable insights and skills to navigate future challenges in the digital era, benefiting both participants themselves and society.

COLLABORATORS

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TEAM REQUIREMENT

Profile: Undergraduate students from both NYU Shanghai and other universities who are interested in Artificial intelligence and the application of digital technology in the education field.

Team size: Up to 4 innovators, a multidisciplinary team profile is recommended (After the Qualifier Announcement, every qualified team will be allowed to extend to 8 innovators, allowing a more productive environment.)

Language

English

THEME OF THE YEAR

Digital Innovation Empowering Personalized Education

CASE ANNOUNCEMENT

Each team needs to choose a specific track assigned by our collaborators, analyze the existing problems or potential improvement in that track, and design a creative project using AI tools as a means of solution. By engaging in real-world projects, participants will apply AI-driven technologies to tackle pressing educational challenges, gaining hands-on experience in developing practical, impactful solutions. Through mentorship and collaboration with industry experts, students will not only deepen their understanding of how AI can transform education but also complete tangible projects that have the potential to be implemented in real-world educational settings. The challenge aims to inspire critical thinking, creativity, and practical execution in shaping the future of education through AI.

EVENT TIMELINE

2024.11.24 Kick-Off Day (Stage 1 start)

2024.12.21 Stage 1 Submission Deadline

2025.01 Qualifier Announcement (Stage 2 starts)

  • Qualifiers receive help from the corresponding enterprises to develop their proposal

2025.01 - 2025.4 Spring Semester Finalist One-to-One Enterprise Development

2025 April Innovation Day

  • Opening Speech
  • Guest Sharing
  • Project Showcase
  • Awarding Ceremony

COMPETITION STAGES

Stage One: Up to 4 collaborating problem owners will each be providing a theme or project in a certain track, and the participants in a team with a maximum number of 4 are expected to choose one track to innovate on. During this phase, participants have full freedom to develop their proposals. The submission will be due one month after Kick-Off Day. The submission should include:

  1. A presentation video. (3 - 5 mins)
  2. A well-designed proposal (showcasing the understanding of the track problem, the unique solution from the team member. And the feasibility of the idea).
  3. The CVs of the team members.

Stage Two: The three winners for each track will continue their journey during the winter break and the next semester. They will be working closely with the corresponding enterprise to thoroughly explore their idea and develop a well-constructed and practical product. At the closing event, experts will participate in the final evaluation and an overall champion will be chosen.

Recruitment Session: The three winners for each track will have a chance to expand their team to a maximum member of 8. This session will be held both online and offline, the specific form will be decided later.

POLICIES

Registration Policy

  • Registration Method:

    Qualtrics

  • Registration Form Link

  • Team Size:

    Each team consists of up to 4 participants, with a recommendation for multidisciplinary team composition. After advancing through the announcement stage, each qualified team can expand to 8-10 participants to facilitate the completion of large-scale projects.

  • Dynamic Team Member:

    After the first registration, the team member is changeable by resubmitting the Registration Form by using the same team name. Team members are determined by the last commitment.

  • Registration Deadline:

    Dec 1st, 2024

Submission Policy

Stage One Submission should contain two parts.

The GitHub Repository Submission Part Should Contain

  • Proposal (in PDF format)
  • Presentation Video (3-5 minutes, within 100MB)
  • Project Prototype (optional, not mandatory)

Qualtrics Submission Part Should Contain

  • Team Member Resumes
  • GitHub Repository Link

Stage One Submission Deadline: 2024.12.21 2024.12.23 8AM (GMT+8)

In Stage 2 , contestants should continue to refine the project using the GitHub repository from the first stage. The deadline for Stage 2 submission will be announced with stage 1 winners.

Note:

  • The contestantā€™s GitHub repository should remain private. After the competition begins, DIC will release the official GitHub account, and contestants need to set it as a collaborator so we can access the repo.

  • The name of the GitHub repository should be in the form below: 
      DIC[Track Number]-[Project Name]

    For example, if the team is choosing track one and the project is named APEX, the name should be

      DIC01-APEX

    The track correspondence is as follows

    Track 01 AI Center Track - "Kiwi + X"
Track 02 Duolingo Track
Track 03 ShinyTest Track - "Learning by Living: AR + LLM = Immersive Language Learning"
Track 04 AI Center Track - Self Designed Theme

  • Contestantsā€™ personal information will only be shared with our collaborators.

  • Official GitHub Account: shanghai.dic@nyu.edu

Stage 1 Selected Teams/Projects:

Kiwi:

  1. Kiwi_Plus
  2. Dynamic_Kiwi
  3. BetterKiwi
  4. Plumber

Self-designed Track

  1. The-ARtists
  2. Curistro-Learning-by-Teaching
  3. FocusFlow
  4. Read-at-Ease

ShinyTest Track

  1. 711
  2. HIL-VLM
  3. TalkTandem

Duolingo

  1. Optimus
  2. AI-powered-lmprovements-for-DET
  3. DETNexus