Paramveer Dhillon is a Postdoctoral Associate in Management Science working with Prof. Sinan Aral.
His current research interests lie in causal inference for network science, digital experimentation, quantitative marketing & statistical machine learning. The focus of his research continues to be building statistical models which are driven by data and at the same time powered by strong theory.
During his PhD studies, Paramveer worked on developing spectral learning algorithms for natural language processing (NLP) and brain imaging. His thesis demonstrated that simple linear models give accuracies comparable to or better than state-of-the-art "deep-learning" algorithms on data from two diverse domains--text/NLP and brain imaging. In addition, the spectral learning methods have strong theoretical grounding, which is absent for deep-learning based approaches.
Paramveer spent the summer of 2011 interning with the Machine Learning group at Yahoo! Research, Santa Clara, CA. In the past, he has also interned at the Max Planck Institute for Biological Cybernetics, Tübingen, Germany, and the Information Sciences Institute, USC, Marina Del Rey, CA.
For more details please visit his personal homepage here.