Student Research Initiative (SRI)

*International Component - Projects with an international component are eligible for a one time $5,000 budget. Funding can be used to support international travel for the student or faculty member, if accompanied by the student. (This opportunity is made possible by a gift from Saunders MBA alum, Charlie Brown.)

Effects of Corporate Transparency and Risks on Capital Markets

Professor Hao Zhang

This project explores how corporate transparency and firm‑specific risks influence capital market outcomes. Students will support data collection and analysis using Python while examining how disclosure and transparency intersect with financial performance and investor decision-making.

Skills Required

1. Excellent Python programming skills
2. Experience using Python for data collection and analysis
3. Strong written and verbal communication skills

Project Duration

Summer, with a likely continuation into Fall

Impact of Credit Rating Agency Closures on Firms’ Credit Terms

Professor Sriniwas Mahapatro

This project studies how the exit or shutdown of a credit rating agency affects the borrowing costs, loan conditions, and financing access of firms that previously relied on that agency. The work includes building large‑scale datasets and conducting empirical analysis using structured financial data and textual information from rating reports and disclosures.

Skills Required

1. Working knowledge of R and/or Python
2. Experience with large, messy datasets and attention to data integrity
3. Basic statistics or econometrics
4. Basic finance or accounting knowledge
5. Interest in text analytics/NLP (preferred)

Project Duration

One or two semesters

Stock Price Bubbles Detection via Large Language Models

Professor Soon Hyeok Choi

This project develops methods to detect stock price bubbles using large language models (LLMs). Students will apply statistical techniques, coding skills, and basic economic theory to build models that identify speculative patterns in financial markets.

Skills Required

1. Basic understanding of statistics and economics
2. Intermediate/advanced Python or R coding
3. Interest in large language models
4. Interest in economics and finance

Project Duration

Summer 2026, Fall 2026, Spring 2026

Bridging the Promise–Experience Gap: Multimodal Similarity in Customer Feedback

Professor Ali Tosyali

This project develops a multimodal similarity metric comparing business‑provided information (descriptions, images, amenities) with customer-generated inputs (reviews, photos, ratings). Using NLP and computer vision, the study identifies gaps between promised and actual customer experiences—applied first in the hospitality industry.

Skills Required

1. Python
2. Use of APIs and web scraping
3. Basic understanding of LLMs; willingness to learn more

Project Duration

Two semesters

AI Disclosure Risk Management

Professor Rong Yang

As AI becomes integral to business operations, companies increasingly report AI as a material business risk. This project examines how firms disclose AI‑related risks, the socio‑technical challenges they face, and the evolving governance standards required to manage them. Students will conduct empirical analysis using large‑scale financial reporting data.

Skills Required

1. Proficiency with R, Python, or Stata
2. Ability to write code for empirical research
3. Basic understanding of financial reporting data

Project Duration

Summer, likely continuing into Fall

Impact of Work Scheduling Regulations on Employee Satisfaction and Customer Perceptions

Professor Jing Tang

This project investigates how scheduling‑stability laws in the service sector affect employees and customers. Using Glassdoor and Yelp reviews, students will analyze changes in online ratings, sentiment, and discussion topics related to working conditions and service quality.

Skills Required

1. Basic experience with Python or R (or willingness to learn)
2. Data cleaning and organization
3. Interest in text analysis (sentiment, topics)
4. Attention to detail and comfort with messy data

Project Duration

Two semesters

AI and the Great Software Reset: Understanding the Global Software Sector’s Market Shock

Professor Kean Wu

Software companies lost nearly 20% in market value in early 2026, alongside global layoffs. This project analyzes whether AI tools—such as code‑generation systems and AI agents—are driving structural changes in the software sector. Students will examine narratives across global markets using scraped data and NLP techniques.

Skills Required

1. Python for web scraping, database construction, and NLP
2. Strong motivation and ability to document research
3. Preferred backgrounds: analytics, computing, business, information systems

Project Duration

Two semesters

Artificial Intelligence Innovation Proliferation

Professor Shubhobrata Palit

This study maps how major U.S. technology companies (Nvidia, AMD, Google, Amazon, Apple, Meta) have built their AI capabilities over the past two decades. Students will analyze large datasets to create a comprehensive view of AI capability development and ecosystem evolution.

Skills Required

1. Proficiency in Stata, R, and/or Python
2. Ability to work with large datasets
3. Knowledge of text analytics (bonus)
4. High‑performance laptop required (≥500GB storage, 32GB RAM)

Project Duration

Two semesters