Statistical Artificial Intelligence and Relational Learning Group is interested in making smart machines that humans can use reliably in their everyday lives. Artificial Intelligence (AI) has made tremendous progress since its early days, and its advancement has helped shape the progress of research in many other fields. Traditionally, AI is used with either the logical approach to address structured problems or with the statistical approach to handle uncertainty. Our research interests lie at the intersection: advancement and application of algorithms that can do both.

Research Highlights


Latest News



 30 Sep 2020 Congratulations to Dr. Das for successfully defending her thesis
Dr. Srijita Das defended her dissertation on “Sample Efficient Cost-Aware Active Learning” on 31st August, 2020.

 29 Sep 2020 Paper on Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning accepted to CoDS-COMAD 2021
Paper on Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning accepted to CoDS-...

 29 Sep 2020 Paper on A Clustering based Selection Framework for Cost Aware and Test-time Feature Elicitation accepted to CoDS-COMAD 2021
Paper on A Clustering based Selection Framework for Cost Aware and Test-time Feature Elicitation accepted to CoDS-COM...

 15 Sep 2020 Professor Natarajan's talk from RBCDSAI Summit is now available on youtube
Watch Professor Natarajan’s talk from Indian Institute of Technology Madras Robert Bosch Centre for Data Science and ...

 15 Sep 2020 Congratulations to Devendra for winning the best student paper award at KiML 2020 co-located with KDD 2020
Devendra’s paper on Knowledge Intensive Learning of GANs was awarded the best student paper award at KDD Workshop on ...

For previous news, see the News Archive

Funding History


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2012
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Acknowledgements