Undergraduate Research Showcase Showdown

Join us in highlighting and celebrating Fall 2021 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.

36-290: Introduction to Statistical Research Methodology (groups)
36-315: Statistical Graphics & Visualization (groups; website interaction only)
36-490: Advanced Undergraduate Research (groups)
36-497: Corporate Capstone/Data Science Experiential Learning (groups)
36-600: Overview of Statistical Learning and Modeling (groups; website interaction only)

On Wednesday, December 8th from 9am-10am EST, students from 290, 490, and 497 will be available on-line to answer questions about their projects, via the Zoom links that will be provided below.
Note: the Zoom sessions will be moderated, and any participants using inappropriate language or creating an unprofessional or unsafe environment will be removed and blocked at the discretion of the moderator.

36-290 Early Undergraduate Research

36-290 Early Undergraduate Research is a fall course targeted to sophomores. Each student carries out a semester-long project, analyzing a particular astronomical dataset, while utilizing methods of exploratory data analysis and supervised statistical learning. At semester's end, students who have individually analyzed the same data come together to create the posters shown below.


Fall 2021: Peter Freeman

Projects
Classification of Active Galaxies Observed by SDSS
Christina Choi, Sonal Suralikal 		Poster Presentation Zoom
Classifying BL Lacs with FERMI Data
Saaniya Bhushan, Malcolm Ehlers, Cindy Xiong 		Poster Presentation Zoom
Predicting Redshift Using SDSS and GALEX Data
Esha Gupta, Joyce Huang, David Lurie, Mengrou Shou 		Poster Presentation Zoom
Is it a Planet? Classifying TESS Observations
Maya Farhadi, Kay Nam, Hannah Shane, Steven Tang 		Poster Presentation Zoom
Classification of White Dwarfs Observed by SDSS
Kaylin Li, Roochi Shah, Carmen Wu, Xavier Xia 		Poster Presentation Zoom

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 fall's project posters below.

Fall 2021: Zach Branson

Projects
Cirrhosis Patients Analysis
Ike Chu, Gisele Wu, Jason Zhan 		Project
Airbnb in New York City: A Traveler and Host's Guide
Isabella Fons, Liliana Hendrix, Valerie Volodin, Shannon Werntz 		Project
Analysis of 2020 MLB Season
Matthew Poh, Amanda Schwartz, Kunpeng Wang, Bin Zheng 		Project
World Happiness
Shahin Choudhury, Jordan Gilbert, Michelle Koo, Joao Vitor MacHado Pereira 		Project
Hate Crimes in the United States
Zoe Li, Heidi Si, Ginny Zhao 		Project
MLB Batting Stats by Game 1901-2021
Suzanne Nie, Megha Raavicharla, Tiffany Shiu, Victoria Zang 		Project
London Shared Bike Usage
Sohini Gupta, Tina Luo, Zeke Rong, Lakshmi Tumati 		Project
Analysis of Factors that Influence Hotel Reviews
Rudrakshi Dasika, Sanjana Jobalia, Parth Maheshwari, Aramya Trivedi 		Project
Data Science and STEM Salaries
Neel Bhatia, Joong "Joshua" Ho Choi, Edric Eun, Zun Wang 		Project
Exploring Factors That Influence Student's Development of Portuguese
Zihan Geng, Yuenni Ho, Judie Yu, Boyang "Helena" Zhou 		Project
Customer Personality Analysis
Lingjie Feng, Yifan Wang, Yilin Wang, Olivia Wu 		Project
Sean Lahman's Baseball Database
Deepro Hoque, Larry Jang, Jaemin Lee 		Project
Boston Bike Share
Yirui Deng, Keltin Grimes, Charly Jin 		Project
College Graduate Major and Employment Analysis
Sayak Bagchi, Sean Hough, Nitin Sivamurugan 		Project
Statistical Visualization of Sephora Dataset
Na Yeon Hong, Jae Hoon "Leo" Jung, Tae Han Lee 		Project
League of Legends Dataset
Wonseok Kang, Jamie Kim, Joan Lee, Justin Psaris 		Project
A Deep Dive Into The Tokyo Olympics in 2021
Edwin Baik, Subin "Hannah" Kim, Yenlin "Ian" Kuo, Richard Yan 		Project
College Majors and Employment
Etan Cohn, Von Ivy, Bryan Nowlan 		Project
Zomato Bangalore Restaurant Reviews
Jonathan Choi, Andy Park, Sean Tavares 		Project
Examining the Scope and Impact of Natural Disaster in the US
Tong Hu, Xuci Mei, Wenjing Shan 		Project
An Analysis of Wind Farms in the Contiguous United States
Sean Birch, Kenneth Huang, Xiaohan Liu, Alan Zhu 		Project
Netflix Movies and TV Shows
Caitlyn Clendenin, Marissa Dones, Danny Maya, Zach Schieffer 		Project
An Examination of the Movie Industry over the Past Four Decades
Kexin Bian, Jason Mei, Tomas Moore, Rohit Roy 		Project
Analysis of Capital Bikeshare in Washington D.C.
Santiago Brusseau, Eric Chen, Cherie Hua, Adrienne Wang 		Project
Customer Personality Analysis
Jonathan Huang, Philip Kaufholz, Janice Lee, Meera Ray 		Project
NBA Players 1996-2021
Grace Chen, Justin Lipton, Jean Park, Kris Perez 		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 2021: Peter Freeman, Jamie McGovern, Zach Branson, Nicole Goodman, Rebecca Nugent

Projects
Connecting CMU Researchers to Current Grant Opportunities (UPDATED Spring 2022!)
(with Neelam Bharti, Huajin Wang, and Sarah Young -- CMU Libraries)
Divya Rao, Kan Sun, Lisa Zhang 		Poster Presentation Shiny App
Decoding Hewins' Books for the Young
(with Rebekah Fitzsimmons -- Heinz College)
Victoria Chang, Aaron Gong, Shelley Kim 		Poster Presentation Zoom
Mercuries and the Machine: London Newsbooks in 1649
(with Christopher Warren -- English)
Qiyun Chen, Brandon Fafata, Eric Huang, Anup Pokharel 		Poster Presentation Zoom
Understanding the Relationship Between Multilingualism and Executive Functions
(with Maureen Hilton and Erik Thiessen -- Psychology)
Zachary Leventhal, Michelle Wang, Clara Ye 		Poster Presentation Zoom
Mapping Sustainable Development Goals to CMU Course Offerings
(with Alexandra Hiniker -- CMU Sustainability Initiative)
Angela Chen, Logan Saito, Shannon Sun 		Poster Presentation Zoom
PHIGHT COVID: Effectiveness of State-Level Mask Mandates
(with Seema Lakdawala -- Pitt Microbiology & Molecular Genetics and Rebecca Nugent -- CMU Statistics & Data Science)
Athena Dai, Claire Kong, Jimmy Lederman, Sebastian Yang 		Poster Presentation Zoom

36-497 Corporate Capstone

36-497 Corporate Capstone 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@stat.cmu.edu) and/or Adam Causgrove (causgrove@cmu.edu).

Fall 2021: Rebecca Nugent, Jamie McGovern, Peter Freeman, Ron Yurko

Projects
US Olympic Team Pipeline Analysis
U.S. Olympic and Paralympic Committee
Pauline Qin, May Wang, Serena Wang, Ginny Zhao
Understanding Competition Depth at the Olympic Games
U.S. Olympic and Paralympic Committee
Isabel Brannan, Tzen-Hao Ng, Shelly Ren, Ananya Vasudev
Exploring Relationships Between Vaccinations, Hospitalizations, and Deaths During the Covid-19 Pandemic
Optum
Michael Lim, Sean Tavares, Ashley Wang, Hazel Zhang 		Poster Presentation Zoom



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

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 2021: Peter Freeman

Projects
Predicting Occurrence of Civil Wars
Edward Piechowicz, Hwankyu Song, Jonathan Taylor 		Poster
Predicting Vaccine Acceptance in the United States
Ellie Lai, Ana Maria Mafla Arcila, Eric Ricci, Xiantong Xin 		Poster
Predicting a Diamond's Price from its Properties
Deanna Badger, Dom Casalnuovo, Darren Cheng, Wendy Flores-Brito, Joshua Rasco 		Poster
Predicting U.S. Hospital Ratings
Jiayu Li, Ben Oppenheimer, Xueting Pu, Bowen Sun 		Poster
Identifying Misclassified Exoplanets
Leo Chen, Jane Hsieh, Srujana Yarasi 		Poster
Predicting Water Potability Using Statistical Algorithms
Abhishek Anand, Pratapaditya Ghosh, Devashri Karve, Tanay Kulkarni Kulkarni 		Poster