RAISE 2024

Student Data Science / Informatics Competition

  • RAISE 2024 is a public informatics, data science and analytics competition for students.
  • Hosted by Rutgers Bloustein School’s Master of Public Informatics (MPI) program, the inaugural competition challenge “Does News Media Spread Fear of AI?” will aim to discover dominant themes in media coverage of AI by analyzing news headlines.
  • RAISE 2024 is a great opportunity for talented students to showcase their informatics, data science, analytics, and problem-solving skills.

Important Dates

Priority team registrations
Feb 15 2024
Submission deadline
March 10 2024
Finalists announced
March 14 2024
Final materials submission
April 14 2024

Final in-person round at the Bloustein School, New Brunswick, NJ April 19 2024

Eligibility

  • Teams of 2-5 members can register for either the undergraduate or graduate track. Upon confirmation of registration, the team will receive the RAISE-24 AI news headlines dataset and further instructions.
  • The competition is open to currently enrolled undergraduate and graduate students from accredited US institutions. Participants must be legally residing in the US for the entire duration of the competition.

Prizes and Awards

  • A first prize winner will be awarded from each of the graduate and undergraduate tracks. A maximum of $5,000 will be awarded to the first prize team.
  • Up to two second prize winners from each of the graduate and undergraduate cohorts will be awarded. A maximum of $1,250 will be awarded to each second prize team.

Judging Criteria

  • Submissions will be evaluated based on overall excellence, creativity, breadth of analysis, accuracy of models, clarity, ethical considerations and recommendations.
  • Judges’ decisions are final and binding. There is no provision for appeals or review.

Competition Guidelines and Details*

The RAISE-2024 competition is a platform to discover and analyze dominant themes from AI related news headlines.

  • Analyze news headlines (text) data on Artificial Intelligence (AI), generate insights, assess ethics, and make recommendations for shared empowerment.
  • Any/all of these could be addressed:
    • Embedded topics and themes?
    • Sentiment Analysis?
    • Abstractive and extractive summaries?
  • Participants will be expected to use data science, analytics, and informatics approaches to discover dominant and hidden narratives woven by the news articles.
  • Participants may use exploratory analyses, data visualizations, statistics, computational linguistics, quantitative modeling or machine learning or other analytical methods.
  • Each team is free to define their own strategy – teams can also use LLMs and tools like Claude, Bard or ChatGPT. However, the use of any AI tool/s MUST be explicitly declared along with a list of prompts submitted as an appendix. Any use of AI without explicit declaration of specific prompts is disallowed. References for all sources must be cited using APA 6 or higher.
  • Tools and languages allowed:
    • Python – Colab or Jupyter Notebooks only
    • R – .R or .RMD only
    • Tableau, Excel
    • For any other tool – please confirm with organizers
  • Shortlisted finalists will be provided with additional instructions and invited to attend (required) the final round of the competition to be held on 4/19/24 at Rutgers University.

 *Read detailed guidelines and Terms and Conditions that apply to all participants

About the Hosts

The Bloustein School’s Master of Public Informatics is a distinguished program for educating highly talented professional student cohorts in the competencies needed in public informatics, advanced data science and analytics, which includes topics such as: machine learning, global data analytics, artificial intelligence, textual analytics and natural language processing, statistics, programming, data management, GIS, visualization, spatial analysis, domain applications, and the application of these skills for domain-specific value creation. The MPI program at Rutgers provides excellent state-of-the-art research driven project opportunities. Graduates of the MPI program will provide a deep understanding of advanced data science and analytics methods, context and public benefit perspectives to this fast growing and high demand domain.

Contact Us

RAISE-24 Coordinator: Julia Esguerra | Undergraduate Teams Coordinator: Vidhi Gala

Please use this email for all correspondence: informatics@ejb.rutgers.edu

Faculty Advisor: Jim Samuel

Code of Conduct

Participants must adhere to a strict code of ethical conduct, and agree to abide by all the rules and requirements of Bloustein, Rutgers and the State of New Jersey.

Updates and Changes

Rutgers University and the Edward J. Bloustein School of Planning and Public Policy reserve the right to modify the competition rules, schedule, or any other aspect of the competition. Registered participants will be notified of such changes via email.

Upcoming Events

Rutgers Disability Coming Out Day

Gov. James J. Florio Special Events Forum, CSB 33 Livingston Avenue, New Brunswick, NJ, United States

A panel of disability activists will discuss building a society that works for all of us. Future leaders in planning, policy, healthcare, and education are encouraged to join to learn […]

Event Series Research Seminar

Bloustein Research Day

Gov. James J. Florio Special Events Forum, CSB 33 Livingston Avenue, New Brunswick, NJ, United States

You are invited to our third annual Bloustein Research Day! It will be an in-person event. Anyone may register to attend. Faculty and staff may sign up to deliver lightning talks. Graduate and undergraduate students may sign up to present posters and potentially win a Best Poster Award. We strongly encourage participation by all members of the Bloustein community. Sign up today!

RAISE 2024: Student Data Science / Informatics Competition

Bloustein School, Civic Square Building 33 Livingston Avenue, New Brunswick, NJ, United States

Rethinking AI for Shared Empowerment (RAISE) 2024 is a public informatics data science competition that will test skills in data analysis and problem-solving while highlighting the importance of data analysis […]