Undergraduate Research Showcase Showdown

Join us in highlighting and celebrating Fall 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
36-490: Undergraduate Research
36-497: Corporate Capstone Project
36-600: Overview of Statistical Learning and Modeling

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
Spring 2024

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 fall's project reports below.

Fall 2024: Spencer Koerner

Projects
Crime Patterns across Los Angeles' LAPD Divisions
T. Adjagbodjou, I. Alarape, E. Dagnachew 		Project
Impact of Remote Work on Employees
S. Alli, A. Iyer, P. R. Low, K. Weng 		Project
How Effectively is Pittsburgh's Public Transit Utilized? A Statistical Health Check on PRT's Transit
E. Amspoker, R. Kim, J. Winick 		Project
Uncorking Insights: A Data-Driven Exploration of Global Wine Quality, Pricing, Taster Bias, and Regional Variation
K. Baryeh, A. Hemlani, A. Mantro, J. Park 		Project
Analyzing Student Performance Factors
S. Bhargava, A. Kommineni, S. Pfingsten 		Project
Breaking Down the Play: Exploring Factors Impacting NFL Team Win/Loss Percentages
B. Bottonari, A. Campbell, S. Gibbs, Y. Rhee 		Project
Balancing Books and Bedtimes: How Sleep Patterns, Course Load, and GPA Are Connected
E. Brusseau, K. Rock, J. Yang 		Project
Unlocking the Chemistry Behind Exceptional Wine Quality
S. Chen, L. Cheng, J. Peng 		Project
An Analysis of 2024 Data Science Salaries
T. Chen, C. Moe, O. Zheng 		Project
Evolving Gender Representation in Cinema: Analyzing the Bechdel Test's Trends and Relationships with Movie Performance throughout History
M. Cheong, A. Geng, R. Vetere Jones, J. You 		Project
Exploring Patterns and Predictors in UFC Fight Outcomes
J. Chin, J. Nichols, J. Wang 		Project
Time to Leave the BMI Behind? A Study of BMI and Health Outcomes
M. Chityala, M. Sudhakar, V. Vegesna 		Project
Understanding Health Exam Behavior: The Impact of Personal, Social, and Experiential Factors
I. Dai, Y. Du, S. Yu 		Project
Unveiling Patterns in Spotify's Top Tracks
C. Davidson, A. Du, N. Sakharuk, N. Schmid 		Project
Exploring Terrorism Trends: Declining Success Rates, Geopolitical Casualty Variations, and the Impact of Attack Types
J. Dong, A. Zhang, J. Zheng 		Project
Personality and Sex, but Not Education, Is Associated with Hard Drug Use
K. Dunkerley, M. Kapur, M. Park, C. Weng 		Project
Analyzing Factors Influencing Cricket Match Outcomes in the Asia Cup
P. Figueira De Mello Rodrigues, A. Koul, R. Patel, P. Srinivas 		Project
Breaking Down Disparities in Global Development
S. Glick, L. Lee, Y. Luo, E. Wang 		Project
Gridiron Greatness: Analyzing NFL Player Performance
P. Guduri, E. Jang, R. Patel, M. Tozzi 		Project
Your Life Impacts Your Night: Breaking Down Sleep Quality by Factors in Life
M. Hernandez, V. Khong, P. Spivack 		Project
Investigating Technical Characteristics of Electric Vehicles in WA
W. Jiang, Z. Lin, K. Yang 		Project
Exploring the Characteristics of Homicides in Los Angeles through Victim Demographics, Case Status, Weapons Used, and Location of Crime
L. Klucinec, C. Niu, K. Quinones, E. Wang 		Project
Exploring the Housing Market in Ames, Iowa by Looking at Amenities, Sales, and Quality of Houses
K. Komma, A. Menon, J. Yagoda 		Project
House Asking Prices in Portugal: Regional Trends, House Features, Energy Efficiency, and Time-Series Analyses
M. Krishnasamy, J. Liu, G. Tan, W. Zhou 		Project
Understand Customer Behavior and Attrition: Analyzing Credit Card Usage Patterns
L. Lei, M. Ren, E. Shi 		Project
NBA Player Performance over the Seasons
J. Li, H. Zheng, Z. Zheng 		Project
Cracking the Code to the Rolling Stone Top 500 Rankings
A. Lin, G. Lin, J. Zhao 		Project
Exploring Mortality, Nutrition, and Population across Countries by Economic Development
J. Morin, J. Wang, D. Zhu 		Project
Understanding Maternal Health Risks: Insights from Health Indicators
D. Si, T Wu, L. Yang, S. Yao 		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.

Fall 2024: Gonzalo Mena & Aaditya Ramdas

Projects
Predicting Homicide Rates from Census Tracts in Brazil
(with Dani Nedal - University of Toronto)
A. Hassan, P. Doshi, E. Szeto, A. Joshi (with Gonzalo Mena - Statistics & Data Science) 		Poster Presentation
Was It Always "Happily Ever After"?
(with Rebekah Fitzsimmons - Heinz College)
E. Buera, E. Shau, M. Zheng, P. Zhu (with Aaditya Ramdas - 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).

Fall 2024: Gonzalo Mena & Aaditya Ramdas

Projects
Rajasthan Royals Projects
Rajasthan Royals
S. Yu, A. Wang, J. Scharpf, N. Annapureddy
(with Ron Yurko - Statistics & Data Science and Krishnan Seshadrinathan - Rajasthan Royals) 		Poster Presentation
Optimizing Cloud Cost Management: Cost Forecasting and Anomaly Detection for Dexcom's GCP Infrastructure
Dexcom
D. Huang, F. Wang, H. Yu, P. Chen
(with Gonzalo Mena - Statistics & Data Science and John Rzeszotarski & Brian Fuller - Dexcom) 		Poster Presentation
Fashion Attribute Classification Using Deep Learning
Pendulum
E. Fu, A. Hioe, I. Wardere, L. Yang
(with Aaditya Ramdas - Statistics & Data Science and Miao Kang - Pendulum) 		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, Dexcom

36-600 Overview of Statistical Learning and Modeling

This course is targeted to non-statistics graduate students at CMU. In their final project, teams of students utilize methods of EDA and statistical learning to analyze datasets. Their posters are linked to below. If you have any questions or comments about these posters, please send them to Peter Freeman (at pfreeman@cmu.edu), who will forward them to the appropriate student teams.

Fall 2024: Peter Freeman

Projects
Predicting Genetic Richness Across Bird Species
J. Knot, R. Rock, J. Tones, E. Walsh, R. Zhao 		Poster
Predicting Civil Wars from Socioeconomic Indicators
M. Chen, T. Habienza, C. Jo, J. Li, A. Mekovsky, Z. Zeng 		Poster
Predicting COVID-19 Vaccine Acceptance Across U.S. States
D. Rogers, F. Valdes Navarro, B. Wang, Y. Wu, G. Zhang 		Poster
Predicting Diamond Prices: A Statistical Modeling Approach
C. Arora, J. Ezemba, S. Gokakkar, K. Kaur, H. Lee, S. K. Murthy 		Poster
Galaxy Mass Prediction from Emission Lines
H. Bie, D. Dimambro, X. Huang, C. Michel, H. Yu 		Poster
Data-Driven Prediction of Flight Delay Duration
G. Abdelhady, V. Khandelwal, I. Salas-Allende, K. Soldozy, E. Sutter, J. Waters 		Poster
Analyzing the Impact of Socioeconomic Factors on Hate-Crime Rates Post-2016 Election
A. Amin, S. Kurz, K. Love, A. Normandin, A. Shanmungam Marimuthus, A. Srikanth 		Poster
Classification of Hospital Ratings: Low vs High
A. Agrawal, A. Bouayad, A. Chembai, A. Nair, S. Narayanan 		Poster
Predicting Median House Values: Exploring Housing and Demographic Factors Through Machine Learning
R. Ashish, V. Discua Santos, A. Frake, K. Yu 		Poster
Predicting Median House Values Based on Demographic and Housing Characteristics
A. Mathkur 		Poster
Using NASA's Kepler Telescope Data to Identify Exoplanets
J. Abollado, E. Cohen, A. Gupta, M. Nwobi, A. Vittalam, S. Yalavarthy 		Poster