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



 25 Aug 2021 Prof. Sriraam Natarajan talks about AI on The Tech Between Us Podcast
Prof. Sriraam Natarajan talks about AI on The Tech Between Us Podcast. The full version of the podcast can be found h...

 11 Aug 2021 Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models wins the best poster award at EEML 2021
The poster for Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models has won the ...

 22 Jul 2021 Two publications at ICAPS 2021
Our Relational Planning and RL framework (RePReL) was accepted in the Planning and Learning Track, and our Human-guid...

 14 Jun 2021 Two papers presented at Artificial Intelligence in Medicine (AIME) Conference
Two papers are being presented at the 19th International Conference on Artificial Intelligence in Medicine AIME this ...

 03 May 2021 Professor Natarajan's talk from RBCDSAI Distinguished Fellow Colloquium Series - Coffee Shop Banter is now available on youtube
Watch Professor Natarajan and Professor Kersting discuss Symbolic and Deep Learning and what it means for the future ...

For previous news, see the News Archive

Funding History


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2012
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Acknowledgements