Undergraduate Research Showcase Showdown

Join us in highlighting and celebrating Spring 2023 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)
36-490: Undergraduate Research (groups)
36-493: Sports Analytics Capstone (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

Each spring, we, in association with Meeting of the Minds, run the Statistics Poster Competition. The winners for the 2022-23 academic year are:

1st Place Use of Language to Identify Stages of Dementia
by Xander Brick, Sophia Hill, Gbenuola Olaiya
2nd Place Exploring Golf Analytics From Trackman System: Consistency and Clustering Analysis
by Jackson Meehan, Emily Feng, Rohan Patel
3rd Place Applying NFL Statistical Models to CMU Football
by Eli Cohen, Jordan Gilbert, Marion Haney, Sarah Tandean

36-315 Statistical Graphics & Visualization

As part of their final project, teams of students build and use interactive statistical graphics and visualizations in a research study. See this spring's project posters below.

Spring 2023: Ron Yurko

Projects
Airbnb Prices in European Cities
Zubair Akram, Bhaayva Manikinda, Dhruva Reddy, Supriya Shingade 		Project
Exploring Earthquake Data
Abigail Kessler, Andrew Wu, Varshaa Sekar Jayanthi, Robert Wetten 		Project
Analysis of Pirated Movie Preferences
Xinyi Ke, Lehan Xu, Tianyi Zhang 		Project
Analysis of Ultra-Marathon Runners and Races
Srinivasan Sathiamurthy, Rebecca Derham, Nihaar Gupta, Cameron Casey 		Project
Statistical Analysis of Airbnb Listings in Major European Cities
Jackson Meehan, Jacob Coffey, Esha Gupta, Stotra Pandya 		Project
HR Analytics on Employee Attrition & Performance
Suin Jung, Emily Pan, Jolie Ma 		Project
Top 250 Anime
Leona Du, Alex Hu, Kate Huang 		Project
NBA Performance Stats Data Visualization
Nayana Balusu, Brandon Yi, Rishika Gogineni, Zand Gorji 		Project
Exploring Shark Tank Data
Darin Chaoui, Jett Hays, Emily Huang 		Project
Google Play Store Mobile Application Analysis
Inho Kang, Andy Jeong, Hailey Kwon, Grace Yim 		Project
Squirrel Population Data Analysis - New York City
Claer Jestin, Elliot Buera, Brian Hu, Idris Wardere 		Project
Property Sales in Melbourne City: A Guide for Real-Estate Agents
Xinran (Pax) Pan, Zixuan (Chloe) Zhou, Hanyue (Helen) Zhang 		Project
Analysis of College Majors Post Graduate Employment
Megha Korpol, Grisham Vazirani, Jacob Helm 		Project
Exploring University Fight Songs Data
Zhuyun Jin, Tianyi Zhang, Yixin Pan 		Project
Exploring NYC Crime Data
Jade Huang, Peile Li, Ruiwen Liu, Jiashen Wang 		Project
Analyzing Shark Tank Data
Grace Liao, Minjoo Kim, Chris Lee, April Wang 		Project
Cats in the UK
Pranay Gundam, Angela Fan, Angela Zhu, Guanda Chen 		Project
Bay Area Rental Market Analysis
Abigail Khieu, Amelia Boose, Logan Saito, Zoe Thorpe 		Project
Gender Wage Gap - Expect Laughs, Not Equality
Aisha Drisdom, Daniel Yi, Mudita Sai, Tiffany Ko 		Project
Super Bowl Commercials
Jeff Mi, Arianna Rosario, Malek Shafei, Adrian Yao 		Project
What Do College Majors Reveal on Employment and Wages?
Xuchao Zhou, Anthony Jiang, William Murrell, Haokun Wu 		Project
Airline Passenger Satisfaction
Hannah Shane, Samuel Yarger, Tishyaa Chaudhry, Sabrina Rodriguez 		Project
Exploration of Spotify Songs
Yasemin Rees, Farida Abdelmoneum, Ike Cai, Diego Ortiz-Miskimen 		Project
Visualizing Gun Violence in the United States
Ishgun Singh, Peter Heo, Juny Kim 		Project
An Analysis of the Hollywood Dataset
Armaan Sahni, Zachary Gelman, Xiaofeng Gan 		Project
Investigating Data Breaches in Washington State
Gwen Li, Sammi Yang, Yueqi Song, Jisoo (Rachel) Han 		Project

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 2023: Joel Greenhouse, Zach Branson

Projects
Predicting Annual Stock Price
(with Lars-Alexander Kuehn - Tepper Business School)
Tianyou Zheng, Roochi Shah, Tiffany Shiu, Tony Hwang (with Joel Greenhouse - Statistics & Data Science) 		Poster Presentation
Speech Fluency Measurement for Aphasia Patients
(with Davida Fromm - Psychology)
Mason Kim, Steffi Chern, Zihan Geng (with Joel Greenhouse - Statistics & Data Science) 		Poster Presentation
Use of Language to Identify Stages of Dementia
(with Davida Fromm - Psychology)
Xander Brick, Sophia Hill, Gbenuola Olaiya (with Joel Greenhouse - Statistics & Data Science) 		Poster Presentation
Investigating Government Bias and Militia Interference in the Minha Casa Minha Vida Housing Program in Brazil
(with Dani Nedal - Political Science, University of Toronto)
Yu-An Chen, Ysabel Li, Arleen Liu (with Joel Greenhouse - Statistics & Data Science) 		Poster Presentation

36-493 Sports Analytics Capstone

Carnegie Mellon and the Department of Statistics & Data Science is actively involved in sports analytics from cutting-edge research to conferences to student clubs to summer programs to outreach initiatives. In 36-493: Sports Analytics Capstone, we partner with the Carnegie Mellon Athletics Department on a set of ground-breaking projects that integrate previously unlinked, disparate data sets to build interactive applications and statistical models that can be used by coaches and staff to better understand and predict student-athlete performance. To learn more about our general Carnegie Mellon Sports Analytics work, please visit the CMSAC site.


Spring 2023: Ron Yurko

Projects
Exploring Golf Analytics From Trackman System: Consistency and Clustering Analysis
(with Dan Rodgers - CMU Athletics)
Jackson Meehan, Emily Feng, Rohan Patel (with Ron Yurko - Statistics & Data Science) 		Poster Presentation
Predicting Division III Softball Outcomes
(with Monica Harrison - CMU Athletics)
Malcolm Ehlers, Gustavo Garcia-Franceschini, Lawrence Jang, Bin Zheng (with Ron Yurko - Statistics & Data Science) 		Poster Presentation
Applying NFL Statistical Models to CMU Football
(with Ryan Larsen - CMU Athletics)
Eli Cohen, Jordan Gilbert, Marion Haney, Sarah Tandean (with Ron Yurko - Statistics & Data Science) 		Poster Presentation

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 2023: Joel Greenhouse, Zach Branson

Projects
Investigation of US Drug Overdose Death Rates
Optum
Jintong Chang, Wenxin Lan, Li Li, Henry Wu, Angela Zhu (with Peter Freeman - Statistics & Data Science) 		Poster Presentation



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