RBV Subramanyam
Also known as: R Bala Venkata Subramanyam
National Institute of Technology Warangal, Indian Institute of Technology Kharagpur
About
RBV Subramanyam is Professor, Department of Computer Science & Engineering, National Institute of Technology Warangal. He has obtained both his MTech and PhD from IIT Kharagpur. His research interests include Data Mining, Machine Learning, Big Data Analytics, Fuzzy Systems. He has guided 10 Ph.D.s and currently six are under supervision. His past administration and academic positions at NIT Waragal were Head of CSE department (2018-2020), Computer Center (2016-2018) Associate Dean (Academic) (2014-2016), Dy Registrar (Academic), Chairman Board of Studies. He has organized Int'l Conf on Big Data Analytics twice (2015, 2018) and several other international, national conferences. He is General Chair for Indicon 2023 (Dec 14-17 2023), MICA 2023 (Oct 30-31 2023). He is reviewer for several journals and conferences. He has organized several FDPs (more than 100) and workshops. He is Senior Member of IEEE and member of Senate/academic council/board of studies of various CFTIs, CFIs, Universities and autonomous colleges. He has served as expert member of NBA accreditation committees and several national level committees. He visited Cambridge UK. He has completed three projects (Govt of India funded, Industry funded) sofar. He is currently Chief Investigator of Electronics & ICT Academy set up by MeitY Govt of India at NIT Warangal which is Rs.25 crore project from March 2019 onwards.
Employment
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National Institute of Technology Warangal Professor2008 - Present
Education
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Indian Institute of Technology Kharagpur MTech and PhD2001 - 2006
Projects & Funding
Projects & funding information is unavailable.
Publications (4)
- Aspect-Specific Sentiment Representation with Knowledge-Enhanced GCN for Multilingual Sentiment Analysis Save
- MSMVAN: Multi Step Multi Variate Deep Attention Network for Renewable Energy Forecast Save
- RDGT-GAN: Robust Distribution Generalization of Transformers for COVID-19 Fake News Detection Save
- URBAN TRAFFIC CRASH ANALYSIS USING DEEP LEARNING TECHNIQUES Save