Sivaji Bandyopadhyay

Sivaji BandyopadhyaySivaji Bandyopadhyay received the Ph.D. degree in Computer Science and Engineering from Jadavpur University, Kolkata, India in 1998. Since 1991 he has been a faculty member of the Department of Computer Science and Engineering, Jadavpur University. H is engaged with several national and international projects such as "Development of Cross Lingual Information Access (CLIA)", DIT, Government of India, August 2006 - 2010, "Development of English to Indian Languages Machine Translation Systems (EILMT)", DIT, Government of India, August 2006- 2010, "Development of Indian Languages to Indian Languages Machine Translation Systems (IL-ILMT)", DIT, Government of India, August 2006- 2010, "An Advanced Platform for Question Answering Systems", Indo-French Center for the Promotion of Advanced Research (IFCPAR), 2009-2012, "Multidisciplinary Research Field on Sentiment Analysis where AI meets Psychology (SAAIP)", Strategic India-Japan Cooperative Programme-Project in the area of multidisciplinary ICT, DST, Government of India 2010-2013, "Answer Validation through Textual Entailment", CONACYT, Mexico, DST, India, 2010-2012. His research interests are in the area of Natural Language Processing, Machine Learning, Machine Translation, Sentiment Analysis, Question Answering Systems and Information Extraction. He has had more than 100 publications in top conferences and journals and has served as program chair, workshop chair and PC member of IJCNLP, NAACL, NLPKE, ICON and others. Author is a member of the ACL, AAMT. Read More Read Less

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Modeling, Simulation and Optimization37 %
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Modeling, Simulation and Optimization37 %
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Modeling, Simulation and Optimization37 %
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Big Data, Machine Learning, and Applications37 %
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Proceedings of International Conference on Big Data, Machine Learning and Applications37 %
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Practical Guide to Sentiment Analysis37 %
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Practical Guide to Sentiment Analysis37 %
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Empowering Low-Resource Languages With NLP Solutions43 % NR
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Empowering Low-Resource Languages With NLP Solutions5 % NR
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