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1. Theory and Applications of Estimation Methods for Exponential-family Random Graph Models

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2. Extracting information in text and time series datasets

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3. Interpretable Statistical Learning: From Hidden Markov Models to Neural Networks

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4. Advances in Spatial Statistics and Inference Methods for Markov Population Models

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5. Mechanistic models for spatial and spatio-temporal data.

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6. Advances of Spatio-Temporal Models in Ecology: Applications in Landscape Genetics, Disease Spread, and Animal Movement

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7. Topics on power enhancement in high-dimensional hypothesis tests

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8. New Statistical Tools for Independence and Conditional Independence

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9. Statistical Methods in Single Cell and Spatial Transcriptomics Data

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10. Mixed Integer Programming, Whitening, and Functional Data Analysis: Improving Feature Selection in “Omics” Research

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