Hi! Welcome to my webpage. I am a PhD candidate in the Machine Learning Department, School of Computer Science at Carnegie Mellon University. Eric Xing is my fantastic adviser. I also collaborate with Tom Mitchell, Dan Roth and Ed Hovy. My research is in the interface of machine learning, natural language processing, knowledge discovery and reasoning (inference). Specifically, I focus on machine reading -- on building background knowledge of the world by extracting knowledge from text and incorporating the extracted background (domain) knowledge to solve problems that require complex reasoning. During my PhD research, I have focused on building automated solvers for standardized tests. In a previous avatar, I used to work on Network Analysis. You can view my publications to get a more definitive idea of my work.
I spent my undergraduate years at Indian Institute of Technology (IIT), Kanpur, where I graduated with a B.Tech. in Computer Science and Engineering. I worked with the Information Management group at IBM Research India from 2010-12. I spent a fantastic summer in 2014 at the Machine Learning Group at Microsoft Research, Redmond where I worked on Machine Comprehension with Matthew Richardson. This work was selected as one of the outstanding papers at the ACL 2015 conference. I also spent a fantastic summer in 2016 at the Allen Institute of AI where I worked with the Euclid team. I am fortunate to be supported by the CMLH Fellowship for the year 2017-18. I was supported by the IBM Fellowship for the year 2016-17 and the Siebel Scholarship for the year 2013-14. I was also a finalist for the Facebook Fellowship in 2014-15. I regularly review for top ML and NLP conferences.
Besides my research, I am passionate about sports (football -- read soccer ;-) , tennis, squash), socio-tech startups and community service. I like to listen to music (contemporary, instrumental, indian classical, sufi, ghazals, electro, etc.) and travel around the world.