CURRENT

This “what if” project imagines how I would study people in untraditional jobs (example: night shifts, multiple jobs, gig work, and low-wage service work) to understand when they find community and when they feel isolated. Building on papers about integration behaviors, race, and belonging, I will create research questions, a simple model, and a method plan (likely interviews) rather than collecting real data. I focus on how race and class might intersect with these untraditional jobs. 

This semester, we will read a series of papers about how incentives shape the decisions we make in every aspect of our lives. I will present a summary of these papers, as well as compile a description of the general characteristics of effective incentives and of those that lead to unexpected behaviors. The papers include works such as Gneezy and Rustichini (2000), Jacob and Levitt (2003), and more. 

We begin by studying the theoretical foundations of causal inference along with methodologies used in observational studies, following the textbook Observational Studies by Paul R. Rosenbaum. Topics include accounting for biases using sensitivity analysis, as well as adapting to study design methods such as matching and stratification. Later in the semester, we will explore applications of these methods by engaging with field-specific papers.

Although traditional statistical inference addresses the unilateral problem of testing a single null hypothesis, many modern problems are multifaceted, with multiple variables, outcomes, or datasets being simultaneous objects of study. In this program, we will track the evolution of statistical methods developed to address problems arising from multiplicity---including settings such as global null testing, family-wise error rate control, and false discovery rate control. As we study these methods, we will also place them in context. What real-world problems motivated these settings and procedures? What practical and theoretical improvements did these methods provide over their predecessors? What issues continue to plague statisticians? By doing so, we will unlock a deeper understanding of the current state of large-scale statistical inference.

Over the course of the semester, we plan on studying several different approaches to pricing that peer to peer platforms have utilized. This will allow us to explore how marketplaces attempt to reach stable equilibriums, what the goals of each actor on a marketplace are, and how market makers design platforms to encourage transactions. The goal will be to look at real P2P marketplace data, and perform an exploratory project, where we learn and utilize machine learning tools to gain a better understanding of what factors go into pricing.

Recent economic models argue that increasing housing supply at the high end of the market can improve affordability throughout the income distribution by easing competition for mid- and low-quality housing. This project examines that prediction through an empirical lens, with particular attention to large U.S. cities such as New York City.

Over the course of the semester, I plan to study how new luxury housing construction affects local housing prices, rents, and ownership patterns, and whether these effects are mediated by investor demand - particularly purchases by foreign or non-occupant buyers. Using neighborhood-level data on housing construction, transaction records, and buyer characteristics, I will test whether luxury supply primarily induces “trickle-down” vacancy chains, as predicted by segmented housing models, or instead attracts additional investment capital that amplifies housing price inflation.

The project aims to connect modern equilibrium models of housing markets with real-world institutional features - such as capital flows, asset pricing behavior, and investor participation - that may limit the affordability gains from high-end construction in certain urban contexts.

"Over the course of the semester, this project will examine the institutional, legal, and political-economic factors shaping the ongoing development of Central Bank Digital Currencies (CBDCs). We begin by understanding CBDCs in the US political system, asking questions about the incentives for a country to develop a CBDC. From there, the project plans to explore how institutional structures and legal frameworks influence CBDC policy design and implementation. 

This project will take a comparative case study approach, focusing on countries that have piloted or implemented CBDCs to understand how their regulatory environments and relationships may differ or look similar to the US. The goal with this project is to situate CBDC development with broader questions of how institutional differences may produce divergent or similar policy incentives in a rapidly digitizing economy. "

We are pursuing research direction on the intersection of Conformal Inference, Differential Privacy and applications in Natural sciences (Medicine). Specifically, we are interested in developing conformal prediction methods, while ensuring that user data remains provably secure. 

We will begin with reading Theoretical Foundations of Conformal Prediction. Then, we will move to reading papers on the Differential Privacy and using Altschuler's seminar notes. Our goal is to build up on 2025 Privacy-Preserving Conformal Prediction Under Local Differential Privacy paper by the end of the WDRP.

This project examines theoretical and empirical research on corruption, regulatory enforcement, and economic outcomes. We begin with foundational models of incentives and information in corruption, then study how regulatory failures, such as emissions cheating, affect public health and welfare. The project focuses on firm behavior under enforcement and discretion, drawing on evidence from environmental regulation in developing and advanced economies, and concludes with work on public corruption and monitoring. Readings are drawn from leading economics journals and are reviewed with attention to institutional design and policy implications.

This independent study examines how firms operate as political actors in the international

arena—especially under conditions of conflict, war, and national-security regulation. We will

connect normative debates in business ethics (complicity, political responsibility, “business

and peace”) with political economy, management, and legal scholarship on policy risk,

investment strategy, and national security review of corporate transactions.

Over the course of the semester, we hope to cover introductory topics in the field of ranking problems as well as their applications. This study will begin with an overview of topics including preference representations using tournaments, aggregations of those preferences and their limitations as explained by Arrow's Impossibility Theorem. We will study how existence of Condorcet Cycles in tournaments make ranking problems difficult. We will spend the rest of the semester examining its applications to aligning LLMs based on human feedback, which includes modern techniques like RLHF and NLHF. We plan to read through a collection of papers starting with earlier works of Kendall, Moran, and Moon, on paired comparisons and rankings, culminating in state-of-the-art LLM-aligning works such as "Statistical Impossibility and Possibility of Aligning LLMs with Human Preferences: From Condorcet Paradox to Nash Equilibrium."