Sotabase

Career

· Professor of Philosophy, California Institute of Technology2013–
· McDonnell Postdoctoral Fellow, University of California, Berkeley2013–
· Assistant Professor, Washington University in St. Louis2013–
· Ph.D. in Logic, Computation and Methodology, Carnegie Mellon University2007–
· M.S. in Knowledge Discovery and Data Mining, Carnegie Mellon University2005–
· B.S. in Philosophy & Mathematics, London School of Economics2002–

Publications (59)

Interventions and Causal Inference
Philosophia Scientiæ · 2007
299
cited
On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables
Conference on Uncertainty in Artificial Intelligence · 2005
162
cited
Visual Causal Feature Learning
Conference on Uncertainty in Artificial Intelligence · 2014
156
cited
Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming
Conference on Uncertainty in Artificial Intelligence · 2014
144
cited
Learning linear cyclic causal models with latent variables
Journal of machine learning research · 2012
141
cited
Experiment selection for causal discovery
Journal of machine learning research · 2013
110
cited
Causal feature learning: an overview
2017
98
cited
Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure
Conference on Uncertainty in Artificial Intelligence · 2013
97
cited
Actual causation: a stone soup essay
Synthese · 2009
93
cited
Introduction to the foundations of causal discovery
International Journal of Data Science and Analysis · 2017
91
cited
N-1 Experiments Suffice to Determine the Causal Relations Among N Variables
2006
72
cited
Do-calculus when the True Graph Is Unknown
Conference on Uncertainty in Artificial Intelligence · 2015
64
cited
Almost Optimal Intervention Sets for Causal Discovery
Conference on Uncertainty in Artificial Intelligence · 2008
63
cited
Approximate Causal Abstractions
Conference on Uncertainty in Artificial Intelligence · 2019
63
cited
Multi-Level Cause-Effect Systems
International Conference on Artificial Intelligence and Statistics · 2015
61
cited
Confirmation in the Cognitive Sciences: The Problematic Case of Bayesian Models
Minds and Machines · 2011
55
cited
Combining Experiments to Discover Linear Cyclic Models with Latent Variables
International Conference on Artificial Intelligence and Statistics · 2010
47
cited
Causal Discovery from Subsampled Time Series Data by Constraint Optimization
European Workshop on Probabilistic Graphical Models · 2016
45
cited
Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data
Conference on Uncertainty in Artificial Intelligence · 2016
43
cited
Causal mapping of emotion networks in the human brain: Framework and initial findings
Neuropsychologia · 2017
40
cited
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