d-separation And The Role of Directed Acyclic Graphs in Causal Reasoning

Abstract

Lecture topic: d-separation And The Role of Directed Acyclic Graphs in Causal Reasoning

Bio:

Rohit is a PhD candidate in Computer Science at Johns Hopkins University. His research focuses on the development of statistical and machine learning methods to infer causal relations from unstructured data as well as the application of such methods to complex genome wide association studies to improve patient outcomes. Rohit is passionate about sharing his love for causal inference, machine learning, and computational genomics through pedagogy. This means that during his PhD, when Rohit was not hunched over his laptop writing research papers, he was instead hunched over his laptop developing pedagogical materials to explain concepts at the intersection of these fields in fun and interesting ways.

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