Ep. 73 - Causality, Graph Theory & The Brain ft. Alex Markham

<p><strong>Alex Markham </strong>is completing their <strong>Postdoc </strong>in the <strong>Math of Data and AI</strong> group at <strong>KTH Royal Institute of Technology</strong> in Sweden. Their research focuses on developing <em>new algorithms for learning causal models from data</em>. Causal inference is especially appealing to more applied researchers, because it offers an intuitive framework for reasoning about why stuff happens and how we can influence it to happen differently. Alex finds causal inference especially interesting because of the many different fields it draws from, including philosophy, cognitive science, and methodology, as well as computational and mathematical fields, like machine learning, statistics, graph theory, algebraic geometry, and combinatorics. Episode 73's got it all: math, science and philosophy -- join us for a holistic half hour!<br> <strong><br> INTRO</strong><br> Causal Inference<br> Correlation vs. Causality<br> <br> <strong>THE BRAIN<br> </strong>Neuroimaging &amp; fMRI<br> Statistics<br> Time<br> Variables<br> Complexity<br> Brain-Computer Interface (BCI)<br> Electroencephalography (EEG)<br> Prosthetics<br> The Matrix<br> <br> <strong>CAUSALITY<br> </strong>Causal Relationships (Direct, Indirect, Mediated)<br> The Limits of Probability &amp; Statistics<br> Extending the Language of Probability<br> The "Do" Operator<br> Symmetry of Correlation<br> "No Causation Without Manipulation"<br> Randomized Controlled Experimentation<br> <br> <strong>MATHEMATICS</strong><br> Machine Learning<br> Dependence &amp; Independence<br> (Acyclic) Directed Graphs (DAGs) &amp; Colliders<br> Causal Models<br> Graph Spaces<br> <br> <strong>///<br> CONTACT</strong><br> Alex's Website: <a href="http://causal.dev/" rel="nofollow" target="_blank">causal.dev</a><br> My Website: <a href="http://rapyourgift.com/" rel="nofollow" target="_blank">rapyourgift.com</a><br> <br> <strong>READINGS</strong><br> Introduction to Causality in Machine Learning by Alexandre Gonfalonieri on Medium: <a href="https: