Department of Computer Science and Engineering
Indian Instiute of Technology
Hauz Khas, New Delhi. 110016
Phone : 91-11-26596064
Email : parags [at] cse [dot] iitd [dot] ac [dot] in
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I am an Associate Professor in the Department of Computer Science and Engineering at Indian Institute of Technology, Delhi. I am a member of the newly formed Data Analytics and Intelligence Research (DAIR) Group. Earlier, I worked as a postdoctoral fellow with Raymond Mooney at the University of Texas at Austin. I finished my Phd with Pedro Domingos at the University of Washington, Seattle in 2009.
My broad interests lie in the area of Machine Learning. Specifically, my reseach focus has been in the area of Statistical Relational Learning (SRL) which aims to combine the power of logic and probability. I have extnesively worked on one such widely used model by the name Markov Logic. I was one of the developers of Alchemy, the first open source implementation of Markov Logic. The key to scaling up inference in SRL models is to exploit the underlying symmetry of the model for efficient inference and learning (referred to as lifted inference and learning). I have done some pioneering work on the problem of lifted inference in SRL models and my core research focus continues to be along the same lines. I am also interested in looking at efficient inference techniques for Computer Vision problems. Peripherally, I have done some work on applying machine learning techniques to problems in Social Network Analysis.