• Spectral Clustering on Graphs
  Understanding graphs by an intuitive deep dive into the graph Laplacian and showcasing its application in effectively partitioning a graph into clusters.
  


• Constrained Optimization and the KKT Conditions
  A discussion of how the Lagrangian handles constraints in optimization and the role of KKT conditions.
  Published in TowardsDataScience
  


• Geodesic Regression
  A generalization of regression in Euclidean space to Riemannian Manifolds.
  Published in TowardsDataScience
  


• Principal Geodesic Analysis
  Explanation on obtaining principal geodesics for data lying in a Riemannian Manifold, akin to Principal Component Analysis (PCA) in Euclidean space, serving as a dimensionality reduction technique for manifold-valued data.
  Published in TowardsDataScience
  


• The Principle of Stationary Action - Nature's Hidden Script
  Shedding light on the foundational principle that unifies all of physics.


• Noether's Theorem
  Insights on the beautiful connection between symmetry and conservation laws.


• A soft Intro to General Relativity
  Offering insights into the foundational principles of Einstein's Theory of General Relativity by exploring the everyday effects of gravity from a relativistic standpoint.
  Published in Cantor's Paradise
  


• How Interesting are Black Holes?
  A lighthearted presentation on the interesting facts about Black Holes.