I am a Research Scientist specializing in machine learning and natural language
In my past life, I was a Senior Research Scientist at Google. I got my PhD
from University of Illinois at Urbana-Champaign working with Prof. Dan Roth. I received M.S. in Computer Science from the same Department in May, 2009. Before that, I obtained a B. Tech degree from the Department of Computer Science at IIT Bombay.
I have done research internships at Yahoo! Labs, Microsoft Research, and Google Research in the summers of 2008, 2010, and 2012, respectively.
- A Discriminative Latent Variable Model for Online Clustering with Kai-Wei and Dan Roth. ICML 2014.
- Restricted Transfer learning for Text Categorization with Gideon Mann. Neural Information Processing Systems (NIPS) workshop on New Directions in Transfer and Multi-Task: Learning Across Domains and Tasks, (2013).
- A Constrained Latent Variable Model for Coreference Resolution with Kai-Wei Chang and Dan Roth. EMNLP 2013.
- Illinois Cognitive Computation Group UI-CCG TAC 2013 Entity Linking and Slot Filler Validation Systems with X. Cheng and B. Chen and K.-W. Chang and Z. Fei and M. Sammons and J. Wieting and S. Roy and C. Wang and D. Roth
- Algorithms for Structural Learning with Decompositions UIUC PhD Thesis - 2013
- A Framework for Tuning Posterior Entropy in Unsupervised Learning with Ming-Wei Chang and Dan Roth. ICML workshop on Inferning: Interactions between Inference and Learning, (2012).
- Efficient Decomposed Learning for Structured Prediction with Dan Roth. ICML 2012. Supplementary Material Containing Proofs.
- Unified Expectation Maximization with Ming-Wei Chang and Dan Roth. To appear in NAACL 2012.
- Illinois-Coref: The UI System in the CoNLL-2012 Shared Task with Kai-Wei Chang, Alla Rozovskaya, Mark Sammons, and Dan Roth. CoNLL Shared Task 2012.
- Domain Adaptation with Ensemble of Feature Groups with Wen-tau Yih. IJCAI 2011.
- Constrained Conditional Models For Information Fusion with Gourab Kundu and Dan Roth. Fusion 2011.
- Inference Protocols for Coreference Resolution with Kai-Wei Chang, Alla Rozovskaya, Nick Rizzolo, Mark Sammons, and Dan Roth. CoNLL Shared Task 2011.
- Automatic Model Adaptation for Complex Structured Domains with Geoffrey Levine, Gerald DeJong, Li-Lun Wang, Shankar Vembu, and Dan Roth. ECML PKDD 2010.
- Learning Multi-linear Representations of Distributions for Efficient Inference with Dan Roth. 2009. ECML-PKDD 2009 and Machine Learning Journal. Amongst 14 out of 600 papers to be published in a special Machine Learning journal edition of ECML PKDD 2009.