Machine learning algorithms are widely used for decision making in societally high-stakes settings from child welfare and criminal justice to healthcare and consumer lending. Recent history has ...
Chongzhi Di develops statistical learning methods for analyzing complex, high-dimensional, and real-time data in biomedical and behavioral research. His work focuses on wearable devices, accelerometry ...
Causal AI transforms key areas of manufacturing by revealing what happens and why. In predictive maintenance, it shifts focus from forecasting failures to understanding how maintenance strategies ...
Stern, Ariel Dora, and W. Nicholson Price, II. "Regulatory Oversight, Causal Inference, and Safe and Effective Health Care Machine Learning." Biostatistics 21, no. 2 ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More When you look at a baseball player hitting the ball, you can make ...
Li, Michael Lingzhi, and Kosuke Imai. "Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules." Journal of Causal Inference 12, no. 1 (2024).
Predictive approaches are also influencing industrial organization, where models forecast market entry, competition, and ...
The causal AI market presents significant opportunities in consulting and cloud services due to demand for causal inference ...
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