New Funded Research at CAAI

The Chicago Booth School of Business is an ecosystem, one that thrives on alumni funding, faculty involvement, and student support to drive growth and discovery across new research focuses and topics. After the launch of a new program that provided research funding in late 2024, the 2025-25 academic year brought with it accelerated growth and  funding for an additional seven research projects in the Fall and Winter of 2025. 

From stereotypes and language constructs to surgery and decision-making, take a glimpse into how the Center for Applied Artificial Intelligence is facilitating breakthroughs in business, finance, and medicine to support our mission to drive social benefit through innovation.

New Projects 

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AI & Medicine Assistant Professor of Operations Management XY Han is discovering how AI can support surgeons in the operating room. Surgical applications of AI have traditionally been held back by two things: limited data and limited labels. Working alongside a team of surgeons and software engineers, Han is learning to train state-of-the-art AI models to be applied in real-world settings by helping medical practitioners improve surgical outcomes. Supported by CAAI research professionals Yegor Baranovski and Kirill Skobelev, his research exemplifies the collaborative nature of research at Booth that extends beyond the university and  applies change through real-world collaboration with the Surgical Data Science Collective. 

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AI & International Economics Assistant Professor of Finance and Applied AI Suproteem Sarkar is exploring how language shapes global investment patterns, and its potential to inhibit economic growth in developing countries. Since foreign investment is a crucial driver of development, Sarkar uses AI to detect stereotypes embedded in influential economic reports to learn how regionally-situated bad news may have ‘spillover effects’ that alter public perception of unrelated by proximal countries. Tracking those effects over time, Sarkar turns to machine learning tools to identify which specific events or characteristics trigger stereotypical thinking in investment reports. His work, supported by CAAI research professional Eric Fithian, offers a novel approach to quantifying bias that may slow growth, and potentially finding ways to counteract it.

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AI & Finance Examining investment dynamics, Associate Professor of Economics Kilian Huber's paper with Niels Gormsen explores the relationship between interest rates, asset prices, and corporate investment. Using AI to analyze corporate conference call transcripts, they discovered a significant gap between borrowing costs and actual investment behavior, highlighting that lower interest rates don't automatically boost business investment as quickly as economic theory predicts. Together with CAAI research professional Kirill Skobolev the researchers' findings challenge traditional models of the established investment-finance relationship.

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AI & Policy The role of central banks in climate policy is a subject of ongoing debate, and Associate Professor of Accounting Rimmy Tomy’s research is contributing to the conversation. Following the Federal Reserve’s withdrawal from an international climate coalition, the question of where the line between monitoring risk and pushing a climate agenda has become central. RP Kirill Skobolev is helping as Tomy employs AI to analyze thousands of documents from the Federal Reserve, Office of the Comptroller of the Currency, and Federal Deposit Insurance Corporation to better understand levels of public engagement around climate policymaking. Their research may provide insights into whether financial regulators have expanded their scope beyond their original mandate, highlighting questions of democratic accountability and the intersection of policy and public debate. 
 

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AI & Financial Markets Scott Nelson is trying to shine a light into the black box of AI, revising previous research papers with the help of CAAI research professional Yegor Baranovski. As he uncovers tools for regulators to oversee AI models that are more difficult to understand by using economic principles, and measures the effects of incomplete data on lending decisions, Nelson is tackling the challenges of regulating the unknown of AI in high-stakes financial decisions.

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AI & Operations As models improve, AI-generated responses to common questions are still sometimes wrong. A phenomenon called ‘model hallucination’ can lead to misleadingly plausible but incorrect model outputs, and researchers find themselves spending copious amounts of time verifying the validity of AI-generated proofs. Rad Niazadeh, Associate Professor of Operations Management, is tackling this problem by building an automated system where multiple AI models (Claude, ChatGPT, and Gemini) collaborate on mathematical problems while a formal verification tool checks their work in real-time. By mapping out each model's mathematical strengths and weaknesses, Niazadeh aims to transform AI from an unreliable assistant requiring constant supervision into a fully automated theorem-proving machine. His research is supported by CAAI research professional Eric Fithian. 

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AI & Marketing Two current projects demonstrate how AI is transforming our understanding of consumer behavior. Oleg Urminsky, Theodore O. Yntema Professor of Marketing, is using AI to systematically analyze what makes headlines effective. By testing his system on thousands of real-world A/B tests and validating the results with human subjects, Urminsky is creating a transparent and replicable method for understanding persuasion at scale, with significant implications for both marketers and behavioral scientists.

Meanwhile, Giovanni Compiani, Associate Professor of Marketing, is continuing spring-funded research that explores how consumers actually choose between products. Using machine learning to analyze product descriptions, reviews, titles, images, Compiani’s work—supported by research professional Janani Sekar—uncovers the subtle patterns in decision making that guide how consumers perceive product similarity and make substitution decisions. 

As consumer behavior increasingly leaves digital traces across platforms and formats, these researchers are developing rigorous methods to extract insights from information that once seemed too unstructured to analyze systematically, contributing to a more nuanced, data-driven understanding of marketing and consumer choice in the digital age.

Research at CAAI 

The projects funded by the Center for Applied AI represent more than academic curiosity, they embody CAAI’s mission to harness AI for meaningful social benefit. As the Center continues to expand its reach and research capabilities, keep an eye out for emerging opportunities in research, engagement, and collaboration. Stay connected to a community dedicated to the future of AI-driven discovery, and explore our growing collection of research by Booth faculty.