My research interests lie in the fields of Artificial Intelligence and Machine Learning and their application to healthcare problems. More specifically, I am interested in the areas of Relational Learning, Reinforcement Learning, Graphical Models, and Planning. Please read more about our projects and team on our team webpage.

Till 2013, I was a faculty member at Translational Science Institute of Wake Forest School of Medicine. I was a Post-Doc earlier at the Department of Computer Science in the University of Wisconsin Madison, working with Professors Jude Shavlik and David Page.

I completed my PhD in fall 2007 under Professor Prasad Tadepalli in the School of EECS at Oregon State University.

Note to incoming students: If you are interested in working with me, please register for a course that I teach. I do not hire students before they take my course. Also, I do not have any internship/short-term positions. Please do not contact me if you want to work with me for less than a year.


Updates

Thanks to AFRL for funding our proposal on Efficient Learning with Human-in-the-Loop in Structured, Noisy and Temporal Domains.

Thanks to Intel AI Academy for the Faculty Award.

I am teaching in the ACAI summer school on Statistical Relational AI. I will be teaching about our work on Human Allied Statistical Relational AI this September.

I am excited to be a speaker in the NSF Serbia Balkan workshop where I will be presenting about our lab's work on Human-Allied Artificial Intelligence at Belgrade this August.

Our collaborative work with David Poole's group and Kristian Kersting on Boosting Relational Logistic Regression has been accepted to KR 2018. Congratulations Nandini.

I am giving the invited talk this year at StaRAI workshop at IJCAI this year.

Our work on Active Feature Elicitation that enables identifying specific examples to acquire more information as advice has been accepted to IJCAI. This enables a new research study to identify potential recruits.

Check our latest work on Drug-Drug Discovery using kernel learning has been accepted to the IEEE Conference CHASE 2018. Congratulations Devendra and Mayukh.

Phillip's work on Unified Advice-Taking framework for SRL models accepted to the Frontiers in Robotics and AI journal special issue (pre-print coming soon).

Thanks Amazon for the Amazon Faculty Research Award

Mayukh's paper with Rakib on Advice seeking in Probabilistic Planning accepted at AAMAS (pdf coming soon). Congratulations Mayukh and Rakib!

Welcome Dr. Gautam Kunapuli who joins our lab as a Research Associate Professor.

I am presenting a tutorial on Statistical Relational AI with Luc De Raedt, Kristian Kersting and David Poole at NIPS 2017.

AAAI submission on Mixed Sum-Product Networks accepted!