Work around the clock to discover and share insights about large, rich, and complex data sets with a team of other undergraduates! Hosted by Brown Data Science.

Datathon is a celebration of data in which teams of undergraduates work around the clock to discover and share insights about large, rich, and complex data sets.

The event is sponsored by the Computer Science Department and the recently launched Data Science Initiative at Brown University. The Data Science Initiative is a cross-departmental program that aims to develop and promote data-driven research and education on campus.

Apart from the competition itself, which is the core of the event, there will be many other supporting activities ranging from educational workshops to opportunities to network with peers and industry representatives.

View full rules

Prizes

$21,200 in prizes

Grand Prize: Sponsored by Goldman Sachs (2)

A tote bag with a hoodie, a water bottle, ***an iPhone X***, and an invitation to present your winning findings to senior staff in Engineering at Goldman Sachs HQ in New York—all expenses paid for each team member.

Second Prize

Neo smartpen + Notebook for each team member

Third Prize

Google Home for each team member

First Prize

Devpost Achievements

Submitting to this hackathon could earn you:

Eligibility

We welcome students from anywhere, and will do our best to reimburse you for transport. Amtrak or MBTA will get you to Providence Station, just a ten minute walk from Brown’s Campus.

 

Judges

Matthew Rothman

Matthew Rothman
Goldman Sachs

Zachary Hamed

Zachary Hamed
Goldman Sachs

Dan Potter

Dan Potter
Director at Brown Data Science Initiative; Brown Computer Science Professor

Jeff Mayse

Jeff Mayse
Data Scientist at Upserve

Serdar Kadioglu

Serdar Kadioglu
Brown Computer Science Professor, Fidelity

Simon Freyaldenhoven

Simon Freyaldenhoven
Brown Economics Professor; Brown Data Science Initiative

Meenakshi Narain

Meenakshi Narain
Brown Physics Professor

Daniel Sanz-Alonso

Daniel Sanz-Alonso
Postdoctoral Research Assistant at Brown University

Zhijin Wu

Zhijin Wu
Brown Statistics Professor

Zheng Zhang

Zheng Zhang
Brown Statistics Professor

Judging Criteria

  • Quality
    Quality of the overall approach will be prioritized irrespective of which dataset is chosen or product created (result, visualization, tool, etc.). Marks of quality could include robust features, versatile and readable code, and polished presentation.
  • Creativity
    Datasets do not come with explicit problem statements. Creativity will be rewarded where it provides new insights or unique applications while still being tied to one or more datasets and is grounded in reality.
  • Team Composition
    The composition of a team will be taken into account when judging a project. A project completed by undergraduates is more impressive than a similar project done by a team of PhD candidates. We encourage diversity of experience and background in teams.
  • Completion
    Complete projects will be held in higher regard than incomplete projects; however, the potential that an insight or application shows will be taken into account, including if it is not complete. Submit your project, anything counts!