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Atlantis 2024 Datathon Dives Deep into Data Challenges

 

Group of students holding certificates and prizes.
Atlantis 2024 datathon winners. (Photo courtesy: Data @ UCI)

Data @ UCI held Atlantis 2024, UC Irvine’s second annual datathon, on April 13-14. The theme of this year’s datathon was “diving into the depths of data,” inspiring participants to uncover hidden insights and solve complex challenges across 29 projects.

Here are the winners of Atlantis 2024.

Best Overall

The ReBrick team used the Rebrickable API to create a dataset that identifies Lego “supersets” — sets that can construct other sets with 90% similarity — and determines how much of a smaller set can be built from a larger set.

ReBrick was built by:

  • Nathan Chau – computer science major, UCI
  • Billy Li – data science major, UCI
  • Arun Malani – political science major, UCI
  • Ayush Mishra – computer science major, UCI

Runner Up Data for Good Award

Vulnerability in Infrastructure analyzes data from a 7.8 magnitude earthquake in Nepal to understand the correlation between building factors and collapse rates to provide insights for improving infrastructure resilience in seismic regions such as California.

Vulnerability in Infrastructure was built by:

  • Veronic Trinh – second-year computer science major, UCI
  • Brianna Chizhevsky – third-year computer science major, UCI
  • Ge Gao – third-year data science major, UCI
  • Eric Pham – third-year oceanic & atmospheric science and data science double major, UCSD

Best Visualization: Happiness in the Haze

The Happiness in the Haze team sought to explore the relationship between happiness and environmental harm such as CO2 emissions across 150 countries from 2005 to the present. They discovered that while initial increases in CO2 emissions were associated with rising happiness levels, this effect eventually leveled off as CO2 emissions continued to rise

Happiness in the Haze was built by:

  • Timothy Pham – third-year computer science major, UCI
  • Jenna Pham – fourth-year business administration major, UCI
  • Aldriech Villamor – fourth-year computer science major, CSU Long Beach
  • Shanni Wu – fourth-year computer science and business economics double major, UCI

Best Presentation: Predicting Home Prices

Predicting Home Prices uses neural networks to predict property assessment values in Orange County based on various characteristics of the property, aiming to understand the factors driving housing prices and highlight broader social issues surrounding increased property values.

Predicting Home Prices was built by:

People’s Choice & Best Use of Melissa API or Data Sets: GEOdle

GEOdle combines the fun of Wordle with the geospatial challenge of GeoGuessr, providing players five chances to guess a random city based on hints derived from Melissa Data datasets.

Best Automotive Bill of Materials Analysis: Quick Release Pit Stop

Quick Release Pit Stop analyzes production data for electric vehicle manufacturing to identify and correct issues with parts validation, yielding benefits such as decreased production costs and increased build quality.

Quick Release Pit Stop was built by:

  • Gordon Ma – first-year computer science major, UCI
  • Mikaiya Philip – first-year applied mathematics major, UCI
  • Emilio Sanchez – first-year mathematics and quantitative economics double major, UCI
  • Lex Truong – first-year computer science and political science double major, UCI

Best Analysis of Market Data in Dublin: DUBLIN DISCOVERIES

DUBLIN DISCOVERIES explores the Airbnb market in Dublin using the “StrataScratch: Market Analysis in Dublin” dataset to identify trends in guest and host behaviors, providing recommendations to drive successful bookings.

DUBLIN DISCOVERIES was built by:

  • Alex Ngo – first-year computer science major, UCI
  • Rahul Joshi – first-year computer science major, UCI
  • Rohan Mistry – third-year computer science major, UCI
  • Colin Yee – third-year data science major, UCI

View all the projects on the Atlantis 2024 Devpost.

— Karen Phan

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