The Curiosity Cup

The Curiosity Cup
A Global SAS Student Competition

Round 1 of the 2026 SAS Curiosity Cup is complete!

We received high-quality paper submissions from 138 teams from around the globe. Those papers were reviewed and scored by 37 industry consultants. Each paper was scored three times, and 13 teams move on to round two.

Congratulations to our finalist teams! We look forward to the creativity of your video presentations.

All teams who submitted papers will be contacted soon with their scores, rank and comments (if provided by the judges), and instructions to claim participant badges.

Team Name	Academic Institution	Country	Title of the paper
Benchmark	Roskilde University	Denmark	From Auction Demand to Benchmark Credibility: An Ex‑Ante Diagnostic for Sovereign Funding
BotBusters	Alma Mater Studiorum - University of Bologna	Italy	Ghost in the Machine: Identifying Bots and Humans through Tweet‑Based Features
ColdChain Predictors	Bucharest University of Economic Studies	Romania	Refrigerator Price Prediction Using Ensemble Learning in SAS®: A Feature Engineering and Multi‑Model Benchmarking Study
Machine Still Learning	University of Malaya	Malaysia	Predicting Customer Churn Trends in the Telecommunications Industry
Nasi Lemak Tambah Nasi	IMU University	Malaysia	Predicting Fatigue Level of Nurses in Hospital to Enhance Staff Optimisation Using SAS Viya for Learners
ORSOL Forecasting	Purdue University	United States	Forecasting Electricity Price Volatility for EV Charging Operations in the SP15 Market
Resonance Analytics	Instituto Tecnológico de Durango	Mexico	The Resistance Threshold: Modeling Financial Literacy as a Defense Against Digital Impulse Buying in LATAM Using SAS® Viya®
Statistix & Chill	Bratislava University of Economics and Business	Slovakia	The Effect of Social Media on Mental Health and Academic Performance of Students
STATYX	FEU Institute of Technology	Philippines	Threshold of Urban Biodiversity Collapse: Forecasting Ecological Tipping Points Under Artificial Light at Night and Other Environmental Covariates Using Avian Indicators
Strategy Stormers	Mukesh Patel School of Technology Management and Engineering	India	Predicting High‑Risk Villages for Infrastructure Investment: A Data‑Driven Analysis of Rural Infrastructure in India
The Data Fusionist	Lamar University	United States	Mapping America’s Chronic Disease Burden: A GIS‑Integrated Machine Learning Framework for Predicting High‑Risk Chronic Disease Communities Using CDC PLACES Data and SAS® Viya
The Tea Test	Swinburne University of Technology, Sarawak	Malaysia	Analyzing and Predicting Global Healthcare Resilience with World Bank Demographic Data
UCCU	New York University	United States	Evaluating a Residual‑Based Hybrid Volatility Framework: Cross‑Market Evidence from U.S. VIX Data

Team Name • Academic Institution • Country • Title of the paper
Benchmark • Roskilde University • Denmark • From Auction Demand to Benchmark Credibility: An Ex‑Ante Diagnostic for Sovereign Funding
BotBusters • Alma Mater Studiorum - University of Bologna • Italy • Ghost in the Machine: Identifying Bots and Humans through Tweet‑Based Features
ColdChain Predictors • Bucharest University of Economic Studies • Romania • Refrigerator Price Prediction Using Ensemble Learning in SAS®: A Feature Engineering and Multi‑Model Benchmarking Study
Machine Still Learning • University of Malaya • Malaysia • Predicting Customer Churn Trends in the Telecommunications Industry
Nasi Lemak Tambah Nasi • IMU University • Malaysia • Predicting Fatigue Level of Nurses in Hospital to Enhance Staff Optimisation Using SAS Viya for Learners
ORSOL Forecasting • Purdue University • United States • Forecasting Electricity Price Volatility for EV Charging Operations in the SP15 Market
Resonance Analytics • Instituto Tecnológico de Durango • Mexico • The Resistance Threshold: Modeling Financial Literacy as a Defense Against Digital Impulse Buying in LATAM Using SAS® Viya®
Statistix & Chill • Bratislava University of Economics and Business • Slovakia • The Effect of Social Media on Mental Health and Academic Performance of Students
STATYX • FEU Institute of Technology • Philippines • Threshold of Urban Biodiversity Collapse: Forecasting Ecological Tipping Points Under Artificial Light at Night and Other Environmental Covariates Using Avian Indicators
Strategy Stormers • Mukesh Patel School of Technology Management and Engineering • India • Predicting High‑Risk Villages for Infrastructure Investment: A Data‑Driven Analysis of Rural Infrastructure in India
The Data Fusionist • Lamar University • United States • Mapping America’s Chronic Disease Burden: A GIS‑Integrated Machine Learning Framework for Predicting High‑Risk Chronic Disease Communities Using CDC PLACES Data and SAS® Viya
The Tea Test • Swinburne University of Technology, Sarawak • Malaysia • Analyzing and Predicting Global Healthcare Resilience with World Bank Demographic Data
UCCU • New York University • United States • Evaluating a Residual‑Based Hybrid Volatility Framework: Cross‑Market Evidence from U.S. VIX Data

Curiosity Cup 2026 at a glance

138 teams

20 countries

452 students

37 industry consultants

I’m curious. Tell me more.

Teams of two to four students and a faculty advisor will choose an analytics topic that ignites their curiosity and use SAS software to learn from the data and answer big questions. Teams will submit papers during the first round and will describe their analysis in video presentations during the second round. Industry experts judge entries based on data preparation, analysis and presentation, organization, use of visuals, and subject matter knowledge.

The 2025 Curiosity Cup Results

Fifteen teams from around the world advanced past the first round and submitted video presentations for the second.

Twenty-five judges provided feedback and each presentation was scored three times to reveal the winners and runners-up in three categories.

Congratulations to the winners and thank you to all the participating teams! We hope you enjoyed applying your skills to uncover insights through data.

All winners and runners up will get an email with the final score, comments from the jury and instructions to claim your digital badge and prizes.

DATA PREPARATION

Rank	Team Name	Academic Institution	Country	Title of the paper
Winner	Data ACES	University of Santo Tomas	Philippines	Predictive Model Trends: Predicting Early Detection of Alzheimer's Disease
Runner-up	DataMind	University of Padua	Italy	Social Media use Among Italian Older Adults: A Weighted Analysis of Facebook Survey Data

DATA ANALYSIS

Rank	Team Name	Academic Institution	Country	Title of the paper
Winner	Machine Learning Dynamite	Anglia Ruskin University	UK	Development of Breast Cancer Detection Tool
Runner-up	DataMind	University of Padua	Italy	Social Media use Among Italian Older Adults: A Weighted Analysis of Facebook Survey Data

DATA PRESENTATION

Rank	Team Name	Academic Institution	Country	Title of the paper
Winner	DataMind	University of Padua	Italy	Social Media use Among Italian Older Adults: A Weighted Analysis of Facebook Survey Data
Runner-up	Machine Learning Dynamite	Anglia Ruskin University	UK	Development of Breast Cancer Detection Tool

Team Requirements

Teams must consist of two to four students.
Participants must be at least 18 years of age and enrolled as a part-time or full-time student at the time the round one paper entry is submitted (or have graduated no earlier than Oct. 1, 2025).
Teams must have a faculty or educator advisor.

Important Dates

Registration opens Dec. 1, 2025.

Registrations must be submitted no later than Feb. 1, 2026.

Papers can be submitted between Dec. 15 and Feb. 22.
- Finalists moving on to round 2 will be selected and notified on or around March 6, 2026.
- Click here to see the papers submitted by the 2025 finalists.

Video presentations for round 2 participants are due by March 25.

Winners will be announced around April 16.

Competition Guidelines

Teams can choose their own SAS learning software, data and analytical question(s) for the competition.

SAS software allowed:
- SAS^® Viya^® for Learners
- SAS Viya Workbench for Learners*
- SAS OnDemand for Academics
- University-licensed SAS software

Data and analytical question(s):
- Student teams may choose their own data set and pose their own analytical question(s).
- Data sets must be publicly available, and entries must include a link to the data. See the FAQ for examples of data set sources.
- As part of the registration process, each team must select one category under which their entry will be judged. The categories are:
  - Business and Economy (ex: banking, insurance, stock markets, startups, risk and fraud).
  - Health, Science and Engineering (ex: disease prevention, climate and environmental impact, transportation, societal good).
  - Culture, Lifestyle and Entertainment (ex: language and communication, consumer behavior, sports and gaming, fun).
Teams must select the category that best fits their project when registering – this choice is final and can't be changed later. Entries will be judged only within the selected category, so choosing the right one is important. Be sure to review the category descriptions carefully before making your selection.

* SAS Viya Workbench for Learners is a development environment that supports SAS, Python and R. Curiosity Cup participants who use Viya Workbench for Learners may use Python and R but are encouraged to also show how SAS code or SAS Viya were used to advance their analysis or to visualize their results.

Judging

Teams have two rounds to highlight their skills:

Round 1: Teams submit a two-to-five-page paper that conducts a data analysis using SAS technology and describes results to a general audience.
- Judging is based on data preparation, data analysis, data presentation and overall paper structure.
- Up to 15 teams will be chosen to compete as finalists in round 2.
- All papers must be submitted using the approved paper template, which teams will be emailed following registration. Only papers using that template will be accepted..

Round 2: Teams selected for round 2 will submit a video presentation describing their data analysis as if given to an audience of analytical stakeholders.
- Judging is based on presentation organization, demonstrated subject knowledge, use of visuals, presentation mechanics and message.

Complete judging information is available in the terms and conditions and FAQs.

Awards

All finalist teams will receive a SAS digital badge acknowledging Finalist status.

A winning and runner-up team will be declared in each of the three categories:
- Business and Economy (ex: banking, insurance, stock markets, startups, risk and fraud).
- Health, Science and Engineering (ex: disease prevention, climate and environmental impact, transportation, societal good).
- Culture, Lifestyle and Entertainment (ex: language and communication, consumer behavior, sports and gaming, fun).

Each student member of the top team in each category may select one of the following prizes:
- Apple iPad (approximate MSRP: US$449).
- Beats Studio Pro Wireless Headphones (approximate MSRP: $349).
* Prizes are subject to availability. In the event of a supply shortage, a comparable prize option of similar value will be offered. Only one first-place prize will be given to an individual winner.

Additionally, each student from a winning team will receive:
- Twelve months of access to the SAS content subscription of their choice.
- SAS digital badge acknowledging finalist status.

Each student member of the runner-up teams in each domain will receive:
- Twelve months of access to the SAS content subscription of their choice.
- SAS digital badge acknowledging finalist status.

Complete judging information is available in the terms and conditions and FAQs.

Check out the top three Curiosity Cup winners from 2025

Data Preparation:
Data Aces
University of Santo Tomas
Philippines

Predictive Model Trends: Predicting Early Detection of Alzheimer's Disease

Read paper

Data Analysis:
Machine Learning Dynamite
Anglia Ruskin University
UK

Development of Breast Cancer Detection Tool

Read paper

Data Presentation:
DataMind
University of Padua
Italy

Social Media Use Among Italian Older Adults: A Weighted Analysis of Facebook Survey Data

Read paper

Please contact us with any questions at curiositycup@sas.com.

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