The general research objectives of the CIPHOD team are to put forth novel theoretical findings and develop innovative methodologies in the realm of causal inference, with a focus on their applicability and utility for epidemiologists. These objectives are centered around three axes while placing particular importance on temporal data and high-level background knowledge (abstractions). The three axes are: discovering causal graphs, identifying and estimating total and direct effets, and searching for root causes of anomalies.
S. Ferreira and C. K. Assaad. Identifying macro conditional independencies and macro total effects in summary causal graphs with latent confounding. the Thirty-Nine AAAI Conference on Artificial Intelligence. 2025. Soon
L. Zan, C. K. Assaad, E. Devijver, E. Gaussier, and A. Ait-Bachir. On the fly detection of root causes from observed data with application to IT systems. ACM International Conference on Information and Knowledge Management. 2024. Link
C. K. Assaad, E. Devijver, E. Gaussier, G. Goessler, and A. Meynaoui. Identifiability of total effects from abstractions of time series causal graphs. The 40th Conference on Uncertainty in Artificial Intelligence. 2024. Link
D. Bystrova, C. K. Assaad, J. Arbel, E. Devijver, E. Gaussier, and W. Thuiller. Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms. Transactions on Machine Learning Research. 2024. Link
S. Ferreira and C. K. Assaad. Identifying macro conditional independencies and macro total effects in summary causal graphs with latent confounding. CI4TS Workshop at The 40th Conference on Uncertainty in Artificial Intelligence. 2024. Link
S. Ferreira and C. K. Assaad. Average controlled and average natural micro direct effects in summary causal graphs . 2024. Link
C. K. Assaad. Causal reasoning in difference graphs. 2024. Link
C. K. Assaad. Toward identifiability of total effects in summary causal graphs with latent confounders: an extension of the front-door criterion. 2024. Link
D. Bystrova, C. K. Assaad, S. Si-moussi, and W. Thuiller. Causal discovery from ecological time series with one timestamp and multiple observations. 2024. Link
B. Glemain, C. K. Assaad, W. Ghosn, P. Moulaire, X. de Lamballerie, M. Zins, G. Severi, M. Touvier, J.F. Deleuze, SAPRIS-SERO Study Group, N. Lapidus, F. Carrat. Does hospital overload increase the risk of death when infected by SARS-CoV-2? 2024. Link