T Le, J Li, R Ness, S Triantafillou, S Shimizu, P Cui, K Kuang, J Pei, ... (2023) Preface: The 2023 ACM SIGKDD Workshop on Causal Discovery, Prediction and Decision, The KDD'23 Workshop on Causal Discovery, Prediction and Decision, 1-2.

S Triantafillou, F Jabbari, GF Cooper (2023) Learning Treatment Effects from Observational and Experimental Data, International Conference on Artificial Intelligence and Statistics, 7126-7146.

S Singla, N Murali, F Arabshahi, S Triantafyllou, K Batmanghelich (2023) Augmentation by Counterfactual Explanation-Fixing an Overconfident Classifier, Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 4720-4730.

V Talisa, F Shah, CC Chang, C Seymour, L Tang, J Kennedy, ... (2022) 1191: HETEROGENEITY IN RESPONSE TO EARLY GOAL-DIRECTED THERAPY IN SEPSIS, Critical Care Medicine 51 (1), 594-594.

I Marinescu, S Triantafillou, K Kording (2022) Regression discontinuity threshold optimization, Plos one 17 (11), e0276755.

K Biza, I Tsamardinos, S Triantafillou (2022) Out-of-sample tuning for causal discovery, IEEE Transactions on Neural Networks and Learning Systems

S Triantafillou, F Jabbari, GF Cooper (2021) Causal and interventional Markov boundaries, Uncertainty in Artificial Intelligence, 1434-1443.

Developing algorithms for causal discovery and inference.

Developing methods for integration of multiple data sources from different experimental conditions or modalities.

Applying machine learning and causal inference methods to solve problems in biology and medicine.