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



 07 Jun 2018 Submission on Kernel Learning from Heterogeneous Similarities accepted to CHASE
“Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities” was accepted to CHASE, IEEE Confer...

 07 Jun 2018 Submission on Active Feature Elicitation accepted to IJCAI
“Whom Should I Perform the Lab Test on Next? An Active Feature Elicitation Approach” was accepted at International Jo...

 22 Feb 2018 Sriraam Natarajan Awarded with Amazon Faculty Award
Professor Sriraam Natarajan is a recipient of the 2017 Amazon Research Awards for work on “Guiding Probabilistic Lear...

 25 Jan 2018 AAMAS'2018 Papers Accepted
Great start to 2018, our two papers were accepted in International Conference on Autonomous Agents and Multiagent Sys...

 04 Dec 2017 Statistical Relational Learning Tutorial at NIPS
Sriraam Natarajan presented a tutorial on Statistical Relational AI with Luc De Raedt, Kristian Kersting and David Po...

For previous news, see the News Archive

Funding History


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2012
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Acknowledgements