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1. Contributions to semiparametric inference and its applications

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2. Statistical Learning on High-Dimensional Multi-Source Data

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3. Statistical Learning for Robust Topological Inference

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4. Inference Methods for High-Dimensional Data: A Focus On Different Hypothesis Testing Problems

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5. Computational Methods and Spatial Models with Intractable Likelihoods

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6. Statistical Analysis of Missing Not at Random Problems with a Nonparametric Regression Model and Semiparametric Missingness Mechanism.

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7. Dimension Reduction and Graphical Models using Optimal Transport

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8. Robust Techniques for High-dimensional Data: Modern Approaches and Applications

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9. A Bayesian Segmented Linear Regression Model to Observe Breakfast Canyon Patterns in Honeybee Hive Weight Data

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10. Modeling data in time and space - studies of irregularities, dependence structure and applications

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