Raksha P.S is a PhD Student at Web Science Lab. She has a Master’s degree in Web Technology from PES Institute Of Technology, Bangalore and Bachelor’s degree in Computer Science from K S Institute Of Technology, Bangalore. Prior to joining IIITB she has worked as a Big Data Engineer at Cogknit Semantics Pvt Ltd, Bangalore. Previously she has worked on Ontology Based Semantic Data Validation, Big Data, Data Visualization using D3.js, Web Crawlers and Developing Learning Management System. Currently she is working on Characterizing online social cognition as a marketplace of opinions. Her research interests are Web Science, Network Science, Data Mining and Social Cognition. For more, please visit her Linkedin Profile.
- Raksha Pavagada Subbanarasimha. 2019. Designing the Cogno – Web Observatory: To characterize the dynamics of Online Social Cognition. Doctoral Consortium of the 12th ACM International Conference on Web Search and Data Mining, Melbourne, Australia, Feb 2019. (WSDM 2019)(To Appear).
- Srinivasa S., Pavagada Subbanarasimha R. (2018) Design of the Cogno Web Observatory for Characterizing Online Social Cognition. In: Anirban Mondal, Himanshu Gupta, Jaideep Srivastava, P.Krishna Reddy, D.V.L.N. Somayajulu. (eds) Big Data Analytics. BDA 2018. Lecture Notes in Computer Science. Springer, Cham. (To appear)
- Raksha Pavagada Subbanarasimha, Lokesh Todwal, Mamillapalli Rachana, Aditya Naidu, and Srinath Srinivasa. 2018. Mithya: A Framework For Identifying Opinion Drivers On Social Media. Demo at ACM IKDD Conference on Data Science and International Conference on Management of Data, Goa, India, Jan 2018 (CODS-COMAD 2018).
- Anish Bhanushali, Raksha Pavagada Subbanarasimha, and Srinath Srinivasa. Identifying Opinion Drivers on Social Media. In Proceedings of ODBASE 2017, Rhodes, Greece, October 23-27, 2017, Springer International Publishing, Cham, 242–253.
- Web Information Retrieval (Reading elective – CS 902)
- Network Science for the web (DS 608)
- Foundations for Big Data Algorithms (CS/DS 812)
- Machine Learning – I (CS/DS 864)