Interactive Machine Learning- Visualization and Explainability

Interactive, mixed-initiative machine learning promises to combine the efficiency of automation with the effectiveness of humans for a collaborative decision-making and problem-solving process. This can be facilitated through co-adaptive visual interfaces. This course will first introduce the foundations of information visualization design based on data charecteristics, e.g., high-dimensional, geo-spatial, relational, temporal, and textual data. Second, we will discuss interaction techniques and explanation strategies to enable explainable machine learning with the tasks of understanding, diagnosing, and refining machine learning models.

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Mennatallah El-Assady
Mennatallah El-Assady
Data Analysis and Visualization

I work at the intersection of data analysis, visualization, computational linguistics, and explainable artificial intelligence. My general research interest is in combining data mining and machine learning techniques with visual analytics, specifically for text data.