User Generated Content, which can range from social media discussions to product reviews to private physician notes, present naturally occurring data that can be used to develop large-scale Machine Learning algorithms for effective processing of human language. My general research interest is in developing linguistically-aware and cognitively-motivated Machine Learning algorithms for prototypical problems that arise in the context of Biomedical Informatics and Business Intelligence. Read more here; my CV.



Postdoc, 2016-Present.
Computational Health Informatics Program (CHIP), Harvard University
Machine learning and NLP systems for extracting clinically-valuable knowledge from EHR and social media texts.
Keywords: Biomedical Informatics, Machine Learning in Health, Language Modeling, Representation Learning.


Postdoc, 2014-2016.
Computational Linguistics and Information Processing (CLIP), University of Maryland
Representation learning with applications to churn prediction and sentiment analysis.
Keywords: Representation Learning, Churn Prediction, Sentiment Analysis.

  Research Scientist, 2013-2014.
Institute for Infocomm Research (I2R)
Community detection and brand name disambiguation in social media.
Keywords: Live Social Media Analytics, Community Detection, Brand Monitoring.

Ph.D., 2009-2013.
Advisor: Dr. Tat-Seng Chua
Lab for Media Search (LMS), National University of Singapore
Sentiment analysis and live event detection and tracking (for organizations and businesses) in social media.
Keywords: Live Social Media Analytics, Event Detection and Tracking, Sentiment Analysis.


M.Eng., 2005-2008.
Advisors: Drs. Farhad Oroumchian, and Maseud Rahgozar
Database Research Group (DBRG), University of Tehran
Distributed information retrieval, Persian search and POS tagging. See Bijbakhan and Hamshahri dataset used at CLEF'08 -09.
Keywords: Distributed IR, Persian Text Retrieval and POS tagging, Multilingual Text Retrieval.