AI.Data Lab Research Showcase - Fall 2024

December 10, 2024

6 PM - 8 PM

Goizueta Business School, Rooms 130, 208 and Commons

Thank you so much for attending the Research Showcase for AI.Data Lab this Fall! Our student cohort has worked tirelessly all semester, and we all are excited to learn from and celebrate their findings and successes over the semester. AI.Data Lab started as a department-specific experiential learning program with about 10 students 2 years ago, and we are thankful for the support we've received to grow this program to be university-wide, serving 140 students this Fall. 

Students were placed in teams based on their preferences and skills at the start of the semester. Each team received a short presentation on behalf of the project sponsor explaining the context of the problem and goal of this partnership. From there, students met weekly to conduct research and development, setting their own project's direction and methodology.

This is program runs every semester on campus. If you are interested in participating in the future, regardless of if you'd be a student participant, student helper, or project sponsor (faculty or external), please contact Tommy Ottolin at tottoli@emory.edu.

Invest Atlanta

investatlanta.com

Project Goals:

• Visualize Atlanta's current business landscape geographically to identify over or under-represented industries throughout the city​
• Synthesize data visualizations, socioeconomic factors, and historical context to develop and defend a compelling narrative about industry clustering

Invest Atlanta 2: College Demographics and Business Location Decisions

RQ: How do variations in Atlanta-based college demographics influence the type of businesses that develop nearby?

Annie He annie.he2@emory.edu

Sophie Hurwitz sophie.hurwitz@emory.edu

Alice Kim alice.kim@emory.edu

Kaavya Muthuganesan kaavya.muthuganesan@emory.edu

Caitlyn Ye caitlyn.ye@emory.edu

Invest Atlanta 4: Predicting Economic Prosperity in Atlanta: Using Industrial Business Clusters and Home Ownership

RQ: To what extent do categories and numbers of businesses in NPUs correlate with home ownership from Invest Atlanta?

Stephanie Ma stephanie.ma@emory.edu

Henry Ning henry.ning@emory.edu

Ada Jiang sjia236@emory.edu

Joy Cheng jiuyi.cheng@emory.edu

Joshua Han joshua.han@emory.edu

Invest Atlanta 5: 

RQ: How do economic mobility scores and their subdivisions correlate with key economic indicators such as job value, land value, and number of registered business, and how can Atlanta's neighborhood divisions be redefined to better reflect current economic realities based on these scores and population data?

Shiqi Hu shu87@emory.edu

Caleb Kim ckim658@emory.edu

Boqiang Li bli262@emory.edu

Jichun Zhao jzh2449@emory.edu

Invest Atlanta 6: Atlanta as the next Silicon Valley? Mobility Scores vs. Industry Mapping

RQ: How does Atlanta, as a growing tech hub, compare to Silicon Valley, an established "Tech Headquarters", in terms of mobility sores and industry concentration?

Katherine Vonder Haar kcvonde@emory.edu

Laura Zang laura.zang@emory.edu

Rohan Agrawal rohan.agrawal@emory.edu

Minjoo Kim minjoo.kim@emory.edu

Coralynn Yang coralynn.yang@emory.edu

Hansen Xu hansen.xu@emory.edu

TechBridge

techbridge.org

Project Goals:

• Establish increased visibility into all tiers of their food insecurity “ecosystem”, from distributors to food banks to customers, and their product’s automation infrastructure​
• Improve base distribution algorithm by determining factors that should impact how food banks/pantries/distributors interact with the TechBridge platform(s)

TechBridge 1: Dashboard Development: Evaluating Donation Aspect Performance Metrics to Increase Donor Volume

RQ: How might we construct a performance metrics dashboard to monitor timely donations and derive insights to improve donor volume performance?

Nate Hu nate.hu@emory.edu

Suhayb Ahmedin suhayb.ahmedin@emory.edu

Grace Petrov grace.petrov@emory.edu

Yafen Chen yafen.chen@emory.edu

TechBridge 2: Impact of Environmental Factors on TechBridge Food Bank Transactions

RQ: How do natural disasters and temperature affect the transaction success between donors, food banks, and food pantries?

Yushu Fan yushu.fan@emory.edu

Yiran Tao yiran.tao@emory.edu

Athena Tian athena.tian@emory.edu

Max Jiang zeyang.jiang@emory.edu

Jackson Fang jifang2emory.edu

TechBridge 3: Predicting Food Bank Demand in Georgia Using Food Weight and Economic Indicators

RQ: How can historical food weight data and economic indicators be used to predict future food demand in Georgia's food banks?

Minyang Li mingyang.li@emory.edu

Elamin Elayed elamin.elsayed@emory.edu

Evelyn Shi evelyn.shi@emory.edu

Erik Frenes erik.frenes@emory.edu

TechBridge 4: Automated Food Categorization and High-Waste Analysis

RQ: How might we automate food category label assignment and identify food categories with high proportions of waste?

Yunxiao Li yunxiao.li2@emory.edu

Ishaan Jain ishaan.jain@emory.edu

Jonathan Wang jonathan.wang2@emory.edu

Gabby Jones gtjone4@emory.edu

TechBridge 5: 

RQ: How do fluctuations in macroeconomic indicators impact food pantry demand?

Charlize Samuels

Kenneth He

Huan Nguyen

Molly Murphy

The Carter Center

cartercenter.org

Project Goals:

• Establish your own political/sociological/ideological research question that could be examined through social media posts, using Junkipedia and Logically.ai

The Carter Center 1: Shaping Voter Decisions: The Evolving Role of Economic Discourse in Election Years

RQ: How do discussions about the economy evolve among key political figures in the years leading up to and during an election cycle in the U.S.?

Zachary Etzoni zachary.etzioni@@emory.edu

Oscar Ni oscar.ni@emory.edu

Aashman Sirvastava aashman.srivastava@emory.edu

Phoebe Pan ziwen.pan@emory.edu

Nelly Rebollar Vergara nrebol2@emory.edu

The Carter Center 2: Is There A Sentiment Disparity Across Media-Linked Political Tweets?

Jillian Koenig jillian.koenig@emory.edu

Swati Rajwal swati.rajwal@emory.edu

Tina Piltner tina.piltner@emory.edu

Joseph Ukpong imeikan.ukpong@emory.edu

Tashfia Noor tashfia.noor@emory.edu

The Carter Center 3: Political Social Media: Sentiment, Current Issues vs. Public Engagement Levels

RQ: How does the public engage with this media? Are there key perspectives and issues that resonate with the public?

Lily Wang lwan478@emory.edu

Maanu Obalapuram mobalap@emory.edu

The Carter Center 4: The 2024 Presidential Election: An Analysis of Racially CHarged Sentiment Used by Donald Trump

RQ: How did the severity of racially charged sentiment in social media posts by Donald Trump change from before to after the election?

Winnie Lau winnie.lau@emory.edu

Innocent Mukoki innocent.mukoki@emory.edu

Zhiyi (Yolanda) Li zhiyi.li@emory.edu

Ronald Kanyepi ronald.kanyepi@emory.edu

Austin Beale, austin.beale@emory.edu

The Carter Center 6: Sentimental Analysis and Position Exploration of Social media

RQ: How do politician rhetoric on global conflicts, as reflected in media content and user engagement, influence public perception and policy discussions within the United States regarding those conflicts?

Nika Huang nika.huang@emory.edu

Aryn Xing aryn.xing@emory.edu

Shan Lu shan.lu@emory.edu

Nihal Khatwani nihal.khatwani@emory.edu

Michael C. Carlos Museum

carlos.emory.edu

Project Goals:

• Innovate or improve current technology pipeline focused on identifying, mitigating, and removing bias in the artifact database

Michael C. Carlos Museum 1: Art Bias Organization

RQ: How can we improve the performance of the BERT model in detecting language bias in art descriptions?

Santiago Vazquez santiago.vazquez@emory.edu

Vicente Martinez vicente.martinez@emory.edu

Satvik Elayavalli satvik.elayavalli@emory.edu

Charles Cook charles.cook@emory.edu

Caroline Zeipel caroline.zeipel@emory.edu

Raasikh Kanjiani raasikh.kanjiani@emory.edu

Michael C. Carlos Museum 3: Diffusion Model for Bias Verification

RQ: Could a diffusion model help verify the absence/presence of bias within an artifact description?

Molly Han jhan387@emory.edu

Justin Lim ylim52@emory.edu

Charlington Coulanges ccoulan@emory.edu

Lina Li rli338@emory.edu

Alix Morales amora38@emory.edu

Daniel Nickas dnickas@emory.edu

Leah Loukedis llouked@emory.edu

Michael C. Carlos Museum 4: Using Image Detection to Address Potential Bias in Artifact Descriptions

RQ: How might we harness the power of image detection to further automate and streamline the debiasing process?

Jessie Ni jessie.ni@emory.edu

Kultum Lhabaik klhabai@emory.edu

Mori Schacter mori.schacter@emory.edu

Hamza Alkadir hamaza.alkadir@emory.edu

Diana Duarte Salinas diana.duarte.salinas@emory.edu