Tony Liu
Assistant Professor of Computer Science @ Mount Holyoke College. PhD @ UPenn, former Scientist/PM @ Roblox.
Hello! My research sits at the intersection of causal inference and machine learning, with a focus on observational methods: how do we build an understanding of the world when we cannot run a randomized experiment?
I develop machine learning approaches that improve observational causal methodology in order to answer causal questions in complex data domains. Alongside my awesome collaborators, I use these methods across data science applications in public health, social communication, mental wellness, and medicine.
selected publications
- Measuring Causal Effects of Civil Communication Without RandomizationInternational AAAI Conference on Web and Social Media (ICWSM), 2024
- Automated Detection of Causal Inference Opportunities: Regression Discontinuity Subgroup DiscoveryTransactions of Machine Learning Research (TMLR), 2023
- Data-driven exclusion criteria for instrumental variable studiesConference on causal learning and reasoning (CLeaR), 2022
- The relationship between text message sentiment and self-reported depressionJournal of affective disorders, 2022
- Quantifying causality in data science with quasi-experimentsNature computational science, 2021
- Machine learning for phone-based relationship estimation: the need to consider population heterogeneityProceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies, 2019