This is the long presentation that I delivered at ICML 2022 for the paper Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness. The project was born out of several “grand challenges” in computational biology and the analysis of single-cell RNA-seq data. One challenge is integrating different datasets that exhibit some kind of technical variation. Another is predicting the effects of drugs and gene knock-outs on certain cells. In this project, we were able to translate these problems into a representation learning setting and then focus on computational methods to enforce the all-important contraint: z independent of c.