David Muchlinski
Assistant Professor
- Sam Nunn School of International Affairs
Overview
Greetings,
I am an Assistant Professor of International Affairs in the Sam Nunn School of International Affairs at Georgia Tech.
My research crosses the subfields of International Relations, Comparative Politics, and Political Methodology. I am a computational political scientist using Artificial Intelligence, Large Language Models, and machine learning to predict outbreaks of civil wars, secessionist conflict, and targeted mass killings and other atrocities. Theoretically, I focus on the debate between ethnic identities, grievances, and political opportunity structures to understand when and where conflict may erupt. Methodologically, I am interested in developing new measures of ethnic salience, state capacity, and conflict dynamics using novel sources of data including text, images, and audio.
My research has been published in leading journals in the field including the American Political Science Review, Journal of Peace Research, Political Analysis, Political Science Research and Methods, Journal of Conflict Resolution, and The Journal of Human Rights, as well as peer reviewed conference proceedings including Empirical Methods in Natural Language Processing and the Association for Computational Linguistics.
I teach courses on quantitative research methods, as well as political violence at both the graduate and undergraduate levels.
I am actively seeking qualified Political Science, Computer Science, and Engineering graduate students, as well as exceptional undergraduates, to assist me on various research projects.
- Ph.D. Political Science, Arizona State University
- MA, Political Science, Arizona State University
- BA, International Relations, University of Redlands
- BA ,Economics, University of Redlands
Interests
- Applied Econometrics
- Comparative Politics: Regional Studies
- Digital Humanities
- Econometrics
- Emerging Technology and Security
- International Security Policy
- Regional Security Challenges
- Science and Technology Studies
- Science, Technology, and International Policy
- Armed Conflict
- Conflicts
- Digital and Mixed Media
- Digital Humanities
- Human/Machine Interaction
- National Security
- Politics
- Religion and Politics
- Science and Technology
- Social Movements
- Statistics
- Terrorism
Courses
- INTA-2010: Empirical Methods
- INTA-2120: Intro to Intl Security
- INTA-2210: Pol Phil & Ideologies
- INTA-2698: Research Assistantship
- INTA-4699: India's Democratic Resilience
- INTA-4803: Special Topics
- INTA-6003: Empirical Research Meth
- INTA-6004: Model,Forecast&Decision
- INTA-6450: Data Analytics and Security
- INTA-8001: Sci,Tech&Intl Affairs II
- INTA-8803: Special Topics
Publications
Recent Publications
Journal Articles
- Reducing mass atrocities through transitional justice
In: Journal of Human Rights [Peer Reviewed]
Date: 2025
- The 2023/24 VIEWS Prediction challenge: Predicting the number of fatalities in armed conflict, with uncertainty
In: Journal of Peace Research [Peer Reviewed]
Date: 2025
- From Academia to Policy Makers: A Methodology for Real Time Forecasting of Infrequent Events
In: Journal of Computational Social Science [Peer Reviewed]
Date: 2022
Chapters
- Machine learning and deep learning
In: Elgar Encyclopedia of Technology and Politics [Peer Reviewed]
Date: 2022
Conferences
- Silent Signals, Loud Impact: LLMs for Word-Sense Disambiguation of Coded Dog Whistles
In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) [Peer Reviewed]
Date: 2024
All Publications
Journal Articles
- Reducing mass atrocities through transitional justice
In: Journal of Human Rights [Peer Reviewed]
Date: 2025
- The 2023/24 VIEWS Prediction challenge: Predicting the number of fatalities in armed conflict, with uncertainty
In: Journal of Peace Research [Peer Reviewed]
Date: 2025
- From Academia to Policy Makers: A Methodology for Real Time Forecasting of Infrequent Events
In: Journal of Computational Social Science [Peer Reviewed]
Date: 2022
- Swords and plowshares: Property rights, collective action, and nonstate governance in the Jewish community of Palestine 1920–1948
In: American Political Science Review [Peer Reviewed]
Date: 2021
- Introducing the Targeted Mass Killing Data Set for the Study and Forecasting of Mass Atrocities
In: Journal of Conflict Resolution [Peer Reviewed]
Date: January 2020
- We need to go deeper: measuring electoral violence using convolutional neural networks and social media
In: Political Science Research and Methods [Peer Reviewed]
Date: 2020
- The Politics and Effects of Religious Grievance
In: Oxford Research Encyclopedia of Politics. [Peer Reviewed]
Date: 2019
- Electoral violence prevention: what works?
In: Democratization [Peer Reviewed]
Date: August 2017
- The Dataset of Countries at Risk of Electoral Violence
In: Terrorism and Political Violence [Peer Reviewed]
Date: 2017
- Comparing random forest with logistic regression for predicting class-imbalanced civil war onset data
In: Political Analysis [Peer Reviewed]
Date: 2016
- Grievances and Opportunities: Religious Violence across Political Regimes
In: Religion and Politics [Peer Reviewed]
Date: 2014
Chapters
- Machine learning and deep learning
In: Elgar Encyclopedia of Technology and Politics [Peer Reviewed]
Date: 2022
- Electoral violence: Patterns and trends
In: Electoral integrity and political regimes [Peer Reviewed]
Date: 2017
Conferences
- Silent Signals, Loud Impact: LLMs for Word-Sense Disambiguation of Coded Dog Whistles
In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) [Peer Reviewed]
Date: 2024
- Latent Hatred: A Benchmark for Understanding Implicit Hate Speech
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing [Peer Reviewed]
Date: 2021
Updated: Feb 11th, 2026 at 3:13 PM