Spring 2025 Projects

This semester, we'll explore the world of omnichannel retail and its applications in areas like Generative AI and healthcare. We'll start by analyzing the core concepts of the field, including retail operations, propensity score adjustments, and information provision. 

Our project will map out the diverse approaches researchers take to operations research by constructing a "grid" that places methodologies along two key dimensions: from analytical to theoretical, and from inventory management to service operations (and various topics in between). This framework will not only provide a clear overview of each topic's application but also reveal the broader methodological trends in the field.

Despite its clinical potential, precision medicine adoption remains limited in the United States. Our project draws on theories on organizational behavior, innovation adoption, and case studies to examine trends in the uptake of precision medicine in the US. Specifically, we analyze how organizational structure and culture affect innovation integration, and how reimbursement, regulation, and risk-aversion slow adoption. Finally, we review how institutional incentives, knowledge transfer, and clinical utility shape precision medicine uptake, emphasizing the need for adaptable healthcare organizations.

Final Presentation Slides 

This project investigates how organizational goals and personal passion, when structurally misaligned, can devolve into unethical behavior, drawing on interdisciplinary research in behavioral psychology, business ethics, and organizational theory. Through an analysis of foundational texts (Locke & Latham’s goal-setting theory, Duckworth’s Grit, Heath and Soltes’ work on corporate crime), we explore the psychological mechanisms that enable well-intentioned professionals to rationalize misconduct. Case studies like Scott Harkonen’s data fraud at InterMune and Wells Fargo’s fake accounts scandal illustrate how techniques of neutralization (e.g., "denial of harm," "appeal to loyalty") bridge the gap between noble aspirations and harmful actions. The project also examines job crafting as a proactive solution to realign motivation with ethical guardrails. Findings highlight the paradoxical relationship between ambition and integrity, offering actionable insights for leaders designing incentive systems and individuals navigating goal-driven environments.

Final Presentation Slides 

Over the course of the semester, we hope to study some foundational topics in causal inference, specifically in the context of interference. This study begins with an overview of potential outcomes and counterfactuals, before delving deeper into ideas of interference. We shall focus on network-based interference, where treatment effects are not independent across units but rather may be dependent on the treatments of neighbors in a network. We explore different forms of interference, and methods for accurately estimating direct and indirect effect effects. The discussion will cover methodological challenges in estimating causal effects under interference, including contamination, spillover effects and extent of network dependence. We will study various approaches for addressing these challenges, including estimands designed to account for interference. Emphasis will be placed on both theoretical development and practical motivation. In doing so, we will engage with a broad range of literature, incorporating both foundational works and recent advancements to develop a comprehensive understanding of interference in causal inference.

Final Presentation Slides

This project investigates the predictability of asset returns using statistical learning methods. By analyzing historical price data and financial indicators, we aim to assess whether machine learning techniques can identify patterns that predict stock prices. We will explore classical econometric models, time-series forecasting techniques, and deep learning approaches to predict stock price movements. The research will also evaluate the implications of predictable patterns for quantitative trading strategies and risk management.

Final Presentation Slides