Job Market Candidates

Please click on the + next to candidate names for bio & dissertation information.

First Name	Last Name	Contact Info	Subfield	Bio	Dissertation Title	Research Interests	Teaching Interests	Dissertation Summary	Personal Website Address
E. Grant	Baldwin	baldwinegrant@g.ucla.edu	American Politics, Urban/Local Politics, Public Policy, Public Opinion	I am a Ph.D. candidate whose research investigates the relationship between public opinion, elections, and public policy in the U.S., with a particular focus on the “low information” environments of city and state governments. My dissertation asks how much voters know about the policy choices of their city governments and whether that knowledge strengthens or hinders government accountability. My work has been published in Urban Affairs Review, is conditionally accepted at the American Political Science Review, and has been supported financially by the Institute for Humane Studies, the Urban Communication Foundation, and the UCLA Institute to Study Hate.	The Supply and Demand of Municipal Policy in a Polarized Era	My research investigates the relationship between public opinion, elections, and public policy in the U.S. with a particular focus on the “low information” environments of city and state governments.	I am prepared to teach courses on American politics, urban politics, public policy, public opinion, and research design.	Theories of democratic accountability expect voters to observe government performance to reward or punish incumbents accordingly. My dissertation asks whether residents can accurately identify the policies enacted by their city governments, whether partisan reasoning helps or hurts that accuracy, and what the consequences of voters' municipal policy knowledge are for democratic accountability. Linking an original survey of over 1,000 American city residents to a comprehensive accounting of the policy decisions of 321 city governments on 20 issues, I show that residents are only marginally better at accurately identifying their city governments' policy than chance, with errors skewing toward over-assuming government action. Partisan reasoning ultimately undermines accuracy because most residents cannot correctly identify which policies are more likely to be enacted in Democratic and Republican cities. Residents reward and punish their city governments based on their perceptions of congruence between city policy and their preferences, regardless of whether those perceptions match reality. These findings suggest that even in an era of nationalized politics, most residents are unable to use partisan reasoning to substitute for direct knowledge of local policy, and that frequent misperceptions of city government action hold real consequences for local democratic accountability.	https://www.egrantbaldwin.com
Jessica	Cobian	jcobian22@gmail.com	American Politics, Race and Ethnicity Politics, Political Psychology, Quantitative Methods, and Survey Experiments.	I am a PhD candidate in Political Science at UCLA, where my dissertation examines how xenophobic rhetoric shapes Latino immigration attitudes and political behavior through group-based emotions, using observational and experimental data. My research focuses on Latino politics, immigration policy, political psychology, and quantitative methods. Additionally, I am a Senior Fellow with the UCLA Voting Rights Project, where I study language access in elections and how census data gaps exclude language minorities from Section 203 protections. Previously, I spent over a decade in policy and campaign work, including as Senior Campaign Manager at the Center for American Progress. My work has appeared in the Annual Review of Political Science and the Journal of the American Medical Association.	The Emotional Effects of Xenophobic Rhetoric on Latino Immigration Attitudes	My research examines how group-based emotions shape Latino political attitudes and behavior, particularly regarding immigration policy. I study how xenophobic rhetoric triggers anger, sadness, and anxiety among Latinos, and how these emotions, moderated by identity, drive support for pro-immigrant policies and political engagement.	I am interested in teaching courses on public opinion, political psychology, and experimental methods focused on identity and public policy. My pedagogy emphasizes diverse scholarly perspectives, guides students in developing testable hypotheses from their own research questions, and gives them hands-on experience analyzing data and building their skills as confident scholars.	Recent years have witnessed a clear uptick in Latino opposition to immigration policies that benefit many of their co-ethnics, such as a pathway to citizenship for undocumented immigrants. What helps explain this trend? In an era of heightened nativism, I argue that Latinos’ immigration attitudes are especially sensitive to how xenophobic rhetoric makes them feel, with distinct emotions triggering various degrees of support for and opposition to pro-immigration policies. I test this claim across two studies. Study 1 leverages the 2016 Collaborative Multi-Racial Post-Election Survey (2016) to evaluate whether discrete emotions reliably predict Latino support for a pathway to citizenship for undocumented immigrants (N=2,753). I find that anger and sadness are each positively and substantively correlated with greater support for this policy, independently of partisanship, additional emotions, and other established correlates of Latino opinion. Study 2 refines these results with a national survey experiment (N=909) that randomly assigned Latino adults to read about xenophobic rhetoric directed at their pan-ethnic group or a control article. I find that exposure to xenophobic rhetoric triggers a mix of anger, sadness, and anxiety. In turn, anger and sadness reliably increases Latino support for pro-immigrant policies, with anxiety displaying limited downstream effects. Building on these findings, Studies 3 and 4 introduce measures of Latino identity centrality and nativity to examine variation across subgroups. Study 3 investigates how identity centrality conditions emotional responses and their translation into immigration attitudes, while Study 4 evaluates how emotions influence political engagement. This dissertation demonstrates that xenophobic rhetoric activates group-based emotions that produce divergent policy preferences and political behaviors.	https://jessicacobian.com/
Soonhong	Cho	soonhongcho@ucla.edu	Causal Inference, Political Methodology, American Politics, Public Opinion	I am a Ph.D. candidate in the Department of Political Science at UCLA, where I am concurrently pursuing a Master’s degree in Statistics and Data Science. My research interest includes political methodology, causal inference, and public opinion. I am an affiliate at the Practical Causal Inference Lab, the Inequality Data Science Lab and the California Center for Population Research at UCLA. Before coming to UCLA, I received my MA in Political Science and BA in Economics and Political Science from Seoul National University.	Three Essays on Causal Inference under Real-World Complications	My research develops statistical methods for causal inference under extrapolation and partial identification, with applications to interrupted time series, synthetic control, and outcomes that are endogenously non-existent. Substantively, I study how political and institutional contexts shape mass behavior and intergroup attitudes in the United States, particularly how citizens respond to landmark legal change and how they form attitudes about immigrants and minority groups.	Quantitative Methods at any level (Basic Statistics, Data Analysis, Regression, Causal Inference, etc.), Game Theory, American Politics	My dissertation includes three essays that introduce methodologies for addressing the challenges of making inferences from political science observational data. The first essay proposes a statistical method for causal inference in observational time series settings where a treatment affects every unit simultaneously, so that the contemporaneous controls used by difference-in-differences and synthetic control are unavailable and the counterfactual must be extrapolated from a unit’s own pre-treatment history. I establish identification within the potential outcomes framework and estimate the counterfactual by Gaussian process (GP) regression. Connecting it to reproducing kernel Hilbert space theory, I derive a bias decomposition that isolates the component extrapolation inflates and a worst-case bound on that component, justifying the GP estimator’s posterior variance as extrapolation-aware uncertainty quantification. The method is illustrated with calibrated simulations and an analysis of handgun purchases after the Supreme Court’s Heller decision, a universal treatment whose practical effect concentrates in a single jurisdiction. In the second essay (with Chad Hazlett and Doeun Kim), we explore the GP as a flexible regression approach for handling uncertainty in predicted counterfactual values. We provide an accessible explanation and an implementation suitable for social science inference problems, reducing user-chosen hyperparameters. We illustrate our approach in settings where conventional approaches struggle due to model-dependency or extrapolation in data-sparse regions, applying it to scenarios with poor covariate overlap, interrupted time series designs, and regression discontinuity. The third essay addresses the challenge of inherently missing outcomes in experimental or observational studies. I extend principal stratification strategies and develop new semiparametric estimators to improve non-parametric bounds. The proposed methodology incorporates machine learning tools to tighten often-wide non-parametric bounds using both discrete and continuous covariates. I conduct a simulation study to demonstrate performance and illustrate with social science studies.	https://soonhong-cho.github.io/
Shing Hon	Lam	shinghon@ucla.edu	International organizations, Chinese foreign policy, International political economy	Shing Hon Lam is an Early Career Research Fellow in the School of Social Sciences at Nanyang Technological University. He received his PhD in Political Science and an MS in Statistics from UCLA in 2026. His research examines how states exercise inﬂuence inside international organisations, with current projects on China at the United Nations, trade barriers at the WTO, and who contests regulation at home. His work has appeared in International Affairs, the Review of International Organizations, Global Policy, and the Journal of Global Security Studies. He has also written for the Lowy Institute and the Washington Post.	The Politics of Trade Protection: Evidence, Coalitions, and Rhetoric in International Trade	I study how countries get their way inside international organisations. My work covers China's influence at the United Nations, through staffing, agenda-setting and endorsement-building, and how states use notification and comment at the WTO to contest each other's trade barriers. I build large text datasets to measure both.	I teach international relations, international political economy, international organisations, Chinese foreign policy and game theory.		https://shinghon.github.io/
Jacques	Courbe	jcourbe@g.ucla.edu	American politics, Computational methods, Political communication, Political psychology, Voting behavior	I graduated from the Dual-BA program between Columbia University and Sciences Po in 2016 with departmental honors in political science and was inducted into Phi Beta Kappa. After graduating, I worked for the New York State Attorney General’s Office in the Financial Crimes Bureau, where I received a Superior Service Award for my data analytics work on investigations involving securities fraud in cryptocurrency and foreign exchange markets, which led to millions of dollars in penalties and restitution. Concurrently to my PhD, I’m pursing an MS in statistics. In my free time, I do yoga, play pickleball, and read/watch science fiction.	Is Conversation Persuasive? Experimental Evidence from AI Political Persuasion	My current research focuses on using AI to better understand the psychological processes that underlie persuasion. I’ve also researched the role of information and interest groups in voting behavior. I’m broadly interested in using computational methods to advance political research and examine how technology affects politics in democracies.	I enjoy teaching interdisciplinary courses from various subfields of political science. I’m particularly interested in teaching courses that view technology as an object of, or methodological tool for, political inquiry. I’ve designed an undergraduate seminar that introduces theories from across the subfields of political science to make sense of AI.	Is conversation more persuasive than static, one-way messaging (like ads, social media posts, and op-eds)? Despite extensive research on deliberative democracy, canvassing, and political conversation, there is surprisingly limited evidence that speaks to whether conversation itself can enhance political persuasion. Recent advances in AI have intensified the urgency of this question: large language models can persuade humans in conversations about candidate choice (Lin et al. 2025) and policy preferences (Hackenburg et al. 2025), raising concerns about opinion manipulation and threats to democratic governance (Argyle 2025). Existing studies on the political persuasiveness of LLMs have compared conversation to one-way messaging (Argyle et al. 2025; Chen et al. 2026; Hackenburg et al. 2025), but they produce conflicting findings, and all of them compare conversation to other treatments that differ on multiple dimensions. I perform an apples-to-apples test for the persuasive effects of conversation, keeping the persuasive strategy and volumes of content equal across conditions. In contrast to Hackenburg et al. (2025), who estimated that a conversation was 41–52% more persuasive than a one-way message, my null result rules out a relative conversational advantage larger than 12%. In both conditions, the LLM was instructed to use facts to persuade, suggesting a central role for information, not conversational interaction, in AI persuasion. I also leverage human-validated LLM coding and other text-analysis techniques to analyze the content of the persuasive communications and open-ended survey items to explore two mechanisms that may differ across conversation and one-way messaging: message personalization and depth of cognitive processing.	https://jacquescourbe.me/
Natalie	Bryce	nataliemarisabryce@gmail.com	International relations; comparative politics; international law; international security; computational, quantitative, and qualitative methods.	I am a Ph.D. candidate in Political Science at UCLA and a Genocide and Atrocity Prevention Research Fellow at the Simon-Skjødt Center for the Prevention of Genocide. As a data consultant for the U.S. Holocaust Memorial Museum’s Early Warning Project, I contribute to statistical models identifying countries at risk of new mass killings. I have six years of teaching experience as an adjunct professor at Pepperdine University and as an instructor and teaching assistant at UCLA. I previously earned an MPA and Certificate in International Policy and Planning from the USC Price School of Public Policy.	The Causes and Consequences of UN Human Rights Investigations	I study international relations, with a focus on international law, human rights, and political violence. My research examines the politics of preventing and punishing mass atrocities: when international institutions respond to serious human rights violations, why legal accountability is uneven, and how policymakers can identify risks before violence escalates.	I am prepared to teach introductory and advanced courses in international relations, including international organizations, international law, human rights, political violence, and foreign policy. I can offer courses in global governance, research design, and quantitative and qualitative methods, as well as interdisciplinary courses connecting international affairs, law, and public policy.	Why do some mass atrocities trigger international investigations while others do not, and how do politics shape what these investigations ultimately produce? UN investigative mechanisms (IMs), such as fact-finding missions and commissions of inquiry, have become a routine response to allegations of genocide, war crimes, and crimes against humanity. Although IMs do not prosecute perpetrators, they document abuses, attribute responsibility, publish legal findings, and increasingly collect evidence for future domestic and international proceedings. Yet political science has paid relatively little attention to these institutions. My dissertation addresses this gap through the first large-N study of the causes and consequences of UN IMs. I argue that they sit at the center of a political tension: they are designed to provide independent documentation of atrocities and support accountability, yet they are created, funded, and constrained by states. Across three papers, I analyze the full life cycle of these investigations: the political decisions that determine when they are established, the mandates and evidentiary constraints that shape how investigators attribute responsibility, and the conditions under which investigative findings support later accountability efforts. Using original data, statistical analysis, computational text analysis, and interviews, the project shows how strategic state interests, institutional design, and legal practices shape the pathway from mass violence to international documentation and criminal accountability.	https://nataliemarisabryce.weebly.com/
Jack	Kappelman	jakappelman@ucla.edu	American Politics, Methods	I am a PhD Candidate in the Department of Political Science at UCLA, where I study American Politics and Methodology. My research examines how citizens respond to political signals—particularly elections that signal sharp policy swings—and how political and institutional contexts shape behavior, markets, and policy implementation. My research combines large-scale administrative data with causal inference methods to observationally evaluate these relationships.	Can Voters Connect Elections to Policy?	Political behavior, gun violence & firearm policy, causal inference, spatial methods, institutions	American politics, methods, public policy	Do voters connect elections to policy? I show that when elections signal potential threats to policies people depend on, citizens adjust their behavior to hedge against the possible erosion of rights that they value. Using administrative records on 500 million firearm background checks and a novel dataset of nearly 11 million marriages across the United States, I find that when a party associated with restricting a valued right wins the presidency, people lock-in access before new restrictions arrive. People buy guns to preempt restrictions associated with Democratic administrations; same-sex couples marry before a conservative government can rescind protections for marriage equality. Political expectations, absent as-yet realized policy change, are sufficient to drive costly, measurable behavior. These findings suggest policy is an important part of how voters interpret elections.	https://www.jakappelman.com/
Erik Clint	vanSonnenberg	vanc12@ucla.edu	Comparative Politics, Quantitative & Qualitative Research Methods (esp. Bayesian Casualty Estimation and Legal Ethnography/Anthropology), Conflict Studies, Int’l., Conflict & Transitional Justice, Human Rights	After earning a BA (w/ Distinction) in Government & Minored in Philosophy at the University of Virginia, I worked as a journalist while continuing interdisciplinary coursework. Focusing on legal anthropology, I gained an MSc in Social Anthropology (w/ Merit) from the London School of Economics and Political Science (LSE), before earning my MA and PhD (2026) in Political Science from UCLA. I am interested in interdisciplinary methods for combining research and policy, conducting yearslong statistical and legal ethnographic research for and/or on Colombia’s Special Jurisdiction for Peace (JEP) war crimes court, Peru’s victims’ unit (RUV), and US immigration courts (EOIR).	A Counting and Accountability for Peace: Conflict Justice and Civil War Violence	My research focuses on the intersection of conflict studies and transitional justice, a much larger field I call conflict justice, which scholars, policy-, and peace-makers require decoupling to establish valid evidence on both transitional and conflict justice. I employ mixed (esp. Bayesian) quantitative, qualitative, and extended ethnographic methods to understand & estimate patterns of conflict violence & its responses to conflict and transitional justice.	Civil War; Conflict Studies; Transitional Justice, Conflict Justice, International Law & International Justice; Statistics and Conflict Data and Casualty Estimation (esp. Bayesian Multiple Systems Estimation/Capture-Recapture); Human Rights; Research Methods—Quantitative, Qualitative, & Ethnography; Legal Anthropology; Political Violence; (Statistical) Network Analysis; Political Theory; Interdisciplinary Studies and Ethnography/Participant-Observation as a Means to Bridge Theory & Practice, Research & Policy.	Among more than 120 countries to endure an average 15 years of civil conflict since 1989, more than 85 have turned to legal interventions to punish and/or pardon armed actors. Within this period, civil wars have killed more than 10 million persons—roughly 90% civilians—dying mostly at the hands of government forces. As peace- and policymakers grapple with equally historic 140 ongoing armed conflicts and hundreds of thousands of annual fatalities—paralleling democratic backsliding’s re-reversed of the democratic third-wave and (transitional) justice cascade that brought both to three of four nations—transitional justice’s 21st-century conflation of justice for (victims of) past repressors amid political transitions, with wartime prosecutions and amnesties of tens and hundreds of thousands of fighters, respectively, has confounded both phenomena. Peacemakers and democracy advocates have been left without internally or externally valid evidence on justice to guide peace and democratization. This project’s conceptual point of departure decouples transitional justice—trials, amnesties, truth commissions, and reparations, designed to help post-authoritarian polities remedy past repression and consolidate democracy and human rights amid political transitions—from what I call conflict justice—trials, amnesties, and other interventions targeting combatants and leaders with (un)accountability for war crimes, crimes against humanity, and other conflict violence. After reviewing civil war research and transitional justice’s conflation of accountability for repressive political regimes with the wholly distinct acts, actors, processes, and objectives of wartime justice, I propose a relational taxonomy of conflict justice to decouple these fields—and stimulate interdisciplinary, especially empirical research into wartime justice—its causes, components, and consequences. Chapter 4 proposes theoretical pathways through which conflict justice trials, amnesties, and connected policies may relate to (non-)state armed networks, their members, patterns and repertoires of victimization, and responses to forces of conflict justice. The chapter closes with statistical analyses of disaggregated forms of conflict justice and violence globally. Chapter 5 further employs statistical network analyses: (re)estimating undocumented casualties in Peru’s and Colombia’s armed conflicts, before briefly outlining continuing research into dozens of Colombian conflict justice programs and their impacts on spatiotemporal and other patterns of conflict violence.
Ayoung	Chun	chun79@purdue.edu	American Politics, Methods	Ayoung Chun is a Postdoctoral Research Associate in the Program on American Institutional Renewal at Purdue University. She received her Ph.D. in Political Science from UCLA in 2025. Her research examines American political institutions, with a focus on Congress and state legislatures, campaign finance, political representation, and legislative behavior. Her work studies how donors and organized interests shape legislators’ priorities, institutional roles, and policymaking activities. Her research has appeared in Legislative Studies Quarterly and has received the APSA State Politics and Policy Section’s Best Graduate Student Paper Award.	The Primary Connection: How Early Money Influences Lawmaking in Congress	American legislatures; Congress and state legislatures; campaign finance; parties and interest groups; political representation; elections; legislative behavior and institutions.	American politics; Congress and representation; parties and interest groups; campaign finance; state and local politics; the presidency; research design; quantitative methods; causal inference; computational social science and text-as-data.	This dissertation examines how the timing of campaign contributions, specifically support from early “seed” donors, shapes legislators’ careers and policy engagement in Congress. I argue that financial relationships formed early in a candidate’s career can persist beyond individual election cycles and remain visible in governing. Early donors provide support before candidates have established congressional records, creating relationships that may endure through obligation, shared policy priorities, or continued access to information and policy networks. I examine whether these early relationships are reflected in the institutional positions legislators occupy and the issues to which they devote attention once in office. Empirically, I analyze campaign contribution records, committee rosters, and congressional hearing transcripts to assess whether early donor ties are associated with committee assignments and legislative speech during hearings. The findings show that seed donor influence is evident in both committee placements and the content of hearing speeches. These results suggest that early financial relationships can shape the long-term structure of congressional careers and legislative agendas, leaving a lasting imprint on American political representation.	https://ayoungchun.github.io/
Aaron F.	Rudkin	rudkin@mit.edu	Methods, American Politics, Comparative Politics	I am a political scientist and computer scientist working as a postdoctoral associate at Massachusetts Institute of Technology on LobbyView. As an applied methodologist, my current focus is on the application of artificial intelligence to the social sciences. My substantive focus is on threats to democratic representation. At UCLA I worked on Voteview/NOMINATE, DeclareDesign, and the Nationscape public opinion survey. My work has been published in American Political Science Review; Journal of Politics; Information, Communication, and Society; Nature Scientific Data; Vaccine; and other scientific journals, and has been widely cited in the popular press.	Three Studies Applying Frontier Methods to Problems in Political Science	Methodology: Artificial intelligence, text-as-data, measurement and scaling, causal inference, survey experiments, software development, meta-analysis, open data.	I am ready to teach core Methodology, Comparative Politics, and American Politics courses, with methodology interests including artificial intelligence and text-as-data and substantive interests in legislative institutions, including the U.S. Congress and legislatures in comparative perspective.	My dissertation consists of three papers applying frontier methods to problems in political science. In “Dunstkreis: Detecting Radical Right Populist Speech Contagion in German State Legislatures with a Data-Driven AI/ML Pipeline”, I introduce DEAL, a text-as-data workflow using document embeddings, automated model selection, and LLM-based training labels. DEAL outperforms traditional text-as-data models and scales cheaply and effectively to large corpora. Contrary to prior findings in the literature, I find a large and sustained increase in radical right populist speech by mainstream parties, across policy issues, following the entry of the Alternative für Deutschland into German state legislatures. In “DC On My Mind: Voter Evaluations of Nationalized Policy Positions in State and Local Politics” (Journal of Politics), my co-author and I use a conjoint survey experiment to directly show that national issues dominate state and local issues even when voters consider candidates for state and local office; voters use national issue cues as a heuristic for ideological alignment, and the effect persists net of partisan cues. We find that democratic representation is “bent, but unbroken.” In “Do commodity prices cause armed conflict? A meta-analysis of natural experiments” (American Political Science Review), my co-authors and I conduct one of the first-ever meta-analyses of observational data, providing a roadmap for re-analysis of observational data and meta-analytic effect size interpretation in this context, and finding that the effect of commodity prices on conflict depends on the type of commodity.	https://rudkin.ca/
Kevin	Grieco	kevin.grieco@tse-fr.eu	Comparative politics	I am currently a Research Fellow at the Institute for Advanced Study in Toulouse. I received my PhD in Political Science from UCLA in 2024. In my research, I collect original quantitative and qualitative data, use methods of causal inference, and partner with local governments, traditional authorities, and civil society organizations. My research draws on insights and networks from more than four years living in Sierra Leone and has been supported by 18 external grants totaling over $1.3 million.	Building Fiscal Capacity in Weak States: Experimental and Qualitative Evidence from Sierra Leone	I study the political economy of state-building and governance in low-capacity contexts, where governments struggle to implement their policies. My primary research agenda takes up two questions: (1) How do weak states collect taxes in the absence of enforcement capacity? (2) What are the political consequences of these tax collection efforts?	I am prepared and eager to teach Introduction to Comparative Politics, for which I led sections at UCLA across three terms. I would also welcome the opportunity to develop and teach courses related to my substantive interests in the political economy of development, state capacity, and African politics.	My dissertation explores how weak states collect taxes in the absence of enforcement capacity. My job market paper, comprising two dissertation chapters, asks whether and why collaboration between local government and traditional authorities in Sierra Leone increases citizens’ compliance with a new property tax. Combining evidence from a large-scale field experiment with qualitative data from 261 interviews, I show that state collaboration with traditional authorities increases citizens’ tax compliance because these authorities possess enforcement capacity and are accountable. This research sheds light on the mechanisms of traditional political authority and improves our understanding of how weak states implement their policies. The question of how weak states collect taxes motivates my third, coauthored chapter, in which we test a prominent social contract view of fiscal capacity: that public participation in politics builds government legitimacy, which in turn boosts tax compliance. We partnered with the municipal government in Freetown, Sierra Leone, to design a digital participatory budgeting program where participants discussed local service preferences with neighbors, pitched potential projects to local politicians, and then voted for public service projects that were subsequently implemented. Evaluating this program with a large-scale field experiment, we show that the intervention durably increased participants’ perceptions of government legitimacy. However, impacts on tax compliance were sharply polarized along partisan lines: participation increased compliance among supporters of the local government but reduced it among opponents, yielding no average effect. Our results provide some of the first experimental evidence on the promise and limitations of social contract-based state-building.	https://kevingrieco.net/
First Name	Last Name	Contact Info	Subfield	Bio	Dissertation Title	Research Interests	Teaching Interests	Dissertation Summary	Personal Website Address