Doctoral Symposium Talk: Hasna Njah

Abstract: Dr. Hasna Njah's (University of Sfax, 2019) research focuses on learning bayesian networks (BNs) for health applications in the context of high-dimensional data. In particular, Dr. Njah's research proposes a new kind of BN, called a Bayesian Network Abstraction (BNA) framework, which uses latent variables to ameliorate the computational and optimization difficulties imposed by high-dimensional data. The BNA framework first uses dependency-based feature clustering algorithms to cluster input variables, followed by learning to summarize each cluster in a separate latent variable, thereby realizing the entire network in a hierarchical clustering & summarization BN, with the overall system learned using the greedy equilibrium criteria and hierarchical expectation maximization. In other work, Dr. Njah has focused on applying BNs to protein-protein interaction data and gene regulatory networks.

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