Undergraduate Research Showcase Showdown

Join us in highlighting and celebrating Spring 2024 Carnegie Mellon Statistics & Data Science undergraduate research and capstone projects! Students in CMU's Statistics & Data Science have multiple opportunites to engage in team research projects from the time that they are sophomores through graduation. Click on each class's tab in the navigation bar to the left to learn more about this semester's class projects. The bar also allows you to access projects from previous semesters.

36-315: Statistical Graphics & Visualization (groups)
36-460/660: Special Topics: Sports Analytics (groups)
36-490: Undergraduate Research (groups)
36-497: Corporate Capstone Project (groups)

Click on the appropriate link to see projects from a previous semester:

Spring 2020 Fall 2020
Spring 2021 Fall 2021
Spring 2022 Fall 2022
Spring 2023 Fall 2023

Each spring, we, in association with Meeting of the Minds, run the Statistics Poster Competition. The winners for the 2023-24 academic year are:

1st Place Detecting Redundancy in Reported CGM Device Issues
by Iris Dai, Chuangji Li, Srihita Nangunuri, Nandini Neralagi
2nd Place Analyzing the Evolution of Children's Literature: A Comparative Study of Lists by Caroline Hewins and Anne Carroll Moore
by Vernon Luk, Yasemin Rees, Patrick Phelan
3rd Place Racial Identity Profiling: Quantifying Disparities in Police Stops in California
by Lingruo Pan, Noelani Phillips, Eileen Xiao

36-315 Statistical Graphics & Visualization

As part of their final project, students develop their own research study featuring a variety of statistical graphics and visualizations. See this spring's project reports below.

Spring 2024: Ron Yurko

Halloween Candy
Meher Kaky, Sreekar Kunaparaju, Alex Chen, Mike Zhou
Sleep-time and GPA
Alva He, Jialing Deng, Ruonan Sun, Vincent Huai
Spotify Top 200
Aanika Schueler, Kina Paguyo, Fritz Sanger
A Comprehensive Analysis of Young People’s Attainment in English Towns and Cities
Joyce Qiu, Yifan Sun, Daniel Zhou
NHL Shots
Grant Allvin, Melos Bekaj, Lay Len Ching, Silas Wang
The Bark Report: Analyzing Dog Breed Popularity and Traits
Laura Canseco, Dhruv Chokshi, Jennifer Lee
Factors Influencing the Popularity of Animes
Aiwen Chen, Evanna Yang, Dexter Wei
Analyzing Customer Spending Patterns: The Role of Demographics, Purchase Types, and Promotion Strategies in Consumer Behavior
Xinfei Cen, Lucia Fang, Yuting Wang, Camellia Wang
Admissions Data
Nanditha Annapureddy, Josiah Smith, Karishma Kulshrestha
A Comprehensive Analysis of Purchasing Patterns to Enhance E-Commerce Strategies
Steffi Chern, Lucy Hu, Sizhe Zhang
World Development Indicators
Christina Ding, Amit Bhattacharjya, Justin Oeni, Aditi Mannem
Uncovering Socioeconomic Patterns Through Census Data
Angelina Ohlinger, Nathan Barretto, Noah Gonzalez
Video Game Sales
Patrick Zhu, Ethan Xu, Pai Yang
Analysis of USA Police Killings in 2015
Jack Lenga, Parth Harish, Vardaan Shah, Brian Kim
Exploring Sleep Patterns and Academic Performance
Purva Bommireddy, Sahaja Danthurthy, Bhargav Hadya, Anahita Hassan
NBA Player Statistics
John Crawshaw, Victor Crawshaw, Audrey Simon, Morgan Hawkins
Exploring Sleep Data
Amelia Wang, Emma Chen, Eric Li, Joyce Lam
Exploring the Drivers of Credit Card Usage
Bhavya Jain, Christian Angelov, Raka Mazumder, Christina Kim
Online Food Dataset
Dennis Chau, Lucas Yi, Jai Shah, TJ Patel
Air Quality and Housing Price Trends in the U.S.
Ali Shakir, Vernon Luk, Alex Lewis, Jianna Brewer
Energy Consumption Across the World
Baron Niu, Vinay Samuel, Darien Yang, Kevin Zheng
University Data
Karen Gonzalez-Cifuentes, Dominic Blum, Sonja Michaluk, Kyumin Park
US Movies Throughout the Decades
Alyssa Beeching, Arrshia Kumar, Nicole Tavoussi, Sibyl Yu
A Statistical Analysis of Sleep and GPA in University First-Years
Hannah He, Max Fang, Nathaniel Scanlon, Tom Fest
Technology Mergers and Acquisitions Analytics
Harshdeep Kaur, Danny Nguyen, Harry Huang, David Lessure
Navigating the Real Estate Maze: The Confluence of Zoning, Condition, Size, and Historical Trends on Property Values
Dhruv Krishnan, Jiayi Chen, Pratham Lakhani, Winston Kwon, Yongmin Lee

36-460/660 Special Topics: Sports Analytics

36-460/660 Special Topics: Sports Analytics is a methods course for juniors, seniors, and masters students that covers fundamental topics and techniques in sports analytics. Students develop their own research projects in the course across a wide variety of sports and research questions, with written reports that you can view below.

Spring 2024: Ron Yurko

The GOAT of the GOATs
Meher Kaky, Baishou Zhou, Alex Chen
A Model of Determining Who Gets A Second QB Contract and How Much They Would Get
Nihaar Gupta, Cam Casey, Taylor Zhou, Jessica Liu
NBA Late-Game Strategies: To Foul Or Not To Foul
Amor Ai, Minnie Ren, Yifan Sun
Hoops and Homework: Academic Rank and Game Day Impact on Wins in College Basketball
Andrew Huang, Monica Paz Parra, Eric Yao
The Greatest Bet in Baseball: Six Simple Outs
Devin Basley, Zachary Strennen, Vinay Maruri, Daven Lagu
Betting the Buzzer
Bhargav Hadya, Jason Huang, John Wang, Samuel Yu
Rhythm is a Footballer (Voted Best Presentation)
Shane Hauck, Jamie Kim, Sophia Gan, A.J. Vetturini
NFL Pay Day
Ben Pan, Roger Wang, Takshsheel Goswami
Drive for Show, Putt for Dough? Unveiling Golf’s Winning Formula
Aidan Booher, Esha Rao, Breana Valentovish, John Wang
Analyzing Consistency of Three-Point Defense by NBA Teams
Aristaeus Chang, Tyshanti Montgomery, Malcolm Ehlers, Malek Shafei
Soccer Penalty Kicks Analysis
Colin Yip, Dhruv Krishnan, Eunice Yang, Mudita Sai
Predicting the 2024 NFL Draft for Quarterbacks
Vineeth Madhavaram, Kevin Wu, Vincent Pi
Run, Run, then Run Again
Alex Cheng, Melody Wang, Liz Chu, Kevin Ren
A Shot in the Dark: Finding the Next Steph Curry
Matt Visco, Sydney Tallan, and Nanditha Annapureddy
The Run-Pass Conundrum: What’s The Better Play?
Arthur Jakobsson, Elin Jang, Prathik Guduri
Ultimate Frisbee Offensive Strategy Analysis
Keertana Narayanan, Aidan Powers, Mahith Edula, Rasika Dronamraju
Blue Team Wins in League of Legends
Claudia Lyu, Dhruv Chokshi, Leona Du, Summer Wang

36-490 Undergraduate Research

36-490 Undergraduate Research is an advanced research course for juniors and seniors. Groups of students collaborate with researchers and scientists in other disciplines and use advanced statistical methodology to tackle real-world challenges. The course heavily emphasizes professional skills development, including collaboration and both written and oral communication.

Spring 2024: Zach Branson & Joel Greenhouse

Detecting Horse Cardiac Arrhythmia with ECG Data
(with Katharyn Mitchell - College of Veterinary Medicine - Cornell University)
Monica Paz Parra, Jiashen Wang, Lillian Yin, Julia Zhang (with Ron Yurko - Statistics & Data Science)
Racial Identity Profiling: Quantifying Disparities in Police Stops in California
(with Leah Jacobs - School of Social Work - University of Pittsburgh)
Lingruo Pan, Noelani Phillips, Eileen Xiao (with Zach Branson - Statistics & Data Science)
Predicting Cognitive Impairment from Language
(with Davida Fromm - Psychology)
Xinfei Cen, Jin Yu Kim, Yuntian Shen, Ziyan Wang (with Joel Greenhouse - Statistics & Data Science)
Predicting Coup Attempts on the Interaction Between Economic Indicators and Political Polarization
(with John Chin - Institute for Strategy & Technology)
Lauren Chin, Claire Luo, Vardaan Shah, Pranav Srinivas (with Joel Greenhouse - Statistics & Data Science)
Saccade Analysis for Childhood Hemisherectomy Patients
(with Maria Chroneos - Psychology)
Cindy Chen, Daiyan Chen, Fuyang Lu (with Joel Greenhouse - Statistics & Data Science)

36-497 Corporate Capstone Project

36-497 Corporate Capstone Project is a course in which we closely collaborate with both commercial and non-profit partners on real data science problems through educational project agreements. These projects can vary in scope but most commonly center on data integration, visualizations, statistical machine learning algorithms, data analysis and modeling, and proof-of-concept prototypes. Professional development skills such as collaboration and written/oral communication are heavily emphasized.

To learn more about partnering opportunities with Carnegie Mellon and Statistics & Data Science, please feel free to contact Rebecca Nugent (rnugent AT stat.cmu.edu) and/or Jessie Albright (jfrund AT cmu.edu).

Spring 2024: Zach Branson & Joel Greenhouse

Detecting Redundancy in Reported CGM Device Issues
Iris Dai, Chuangji Li, Srihita Nangunuri, Nandini Neralagi
(with Peter Freeman - Statistics & Data Science and Hiren Gupta & George Chemers - Dexcom)

Previous Partners: C.H. Robinson Worldwide, Inc, Black & Veatch, The NPD Group, The Principal Financial Group, CivicScience, TruMedia, Steady (App), Giant Eagle, Penguin Random House, Pack Up + Go, IKOS, ThermoFisher Scientific, PNC/Numo, USOPC, Optum, Allegheny County Health Department, Pittsburgh Parks Conservancy, Dexcom