I am working with Professor Aaron Clauset. My current research involves inference and learning in graphical models. I am interested in looking at inference problems from different angles like Bayesian approaches in statistics and machine learning, free energy in statistical physics and information theoretic perspective from electrical engineering and physics. 

Previously I worked on 
  • detectability limits and optimal algorithms for community detection in dynamic networks,
  • analyzing and comparing various model selection approaches in networks,
  • analyzing the overfitting and underfitting issues in community detection problem.
My research interests lie in machine learning, information theory, statistical inference, random matrix theory, data mining, and signal processing.


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