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Sriraam Natarajan
Statistical Relational Learning
Reinforcement Learning
Graphical Models
Healthcare Applications Of AI
About
Sriraam Natarajan, Ph.D. is a Professor of Computer Science at The University of Texas at Dallas and Director of the Center for Machine Learning. His research interests include artificial intelligence, machine learning, statistical relational learning, reinforcement learning, graphical models, and healthcare applications of AI. He earned his Ph.D. in Computer Science from Oregon State University and has held faculty positions at Indiana University and Wake Forest School of Medicine. Natarajan is a Fellow of the Association for the Advancement of Artificial Intelligence and has received multiple awards for research and teaching excellence.
Research Performance Summary
1980-2025
Active Research Span
First Recorded Paper
A COMPOSITE CERAMIC-POLYMER MATERIAL USED FOR ALVEOLAR BONE PRESERVATION
Year:
1980
Citations:
0
Venue:
Eighth Annual Northeast Bioengineering Conference, Massachusetts Institute
Latest Recorded Paper
Combining Planning and Reinforcement Learning for Solving Relational Multiagent Domains
Year:
2025
Citations:
0
Venue:
arXiv preprint arXiv:2502.19297
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.
Publication Venues and Collaboration
Journal, Conference, and Book Publication Breakdown
Top Coauthors
Natarajan
Kersting
Khot
Research Impact by Period
Papers
13
Citations
69
Avg. Citations / Paper
5.3
H-Index
2
Papers
90
Citations
557
Avg. Citations / Paper
6.2
H-Index
11
Papers
95
Citations
1781
Avg. Citations / Paper
18.7
H-Index
20
Papers
79
Citations
1895
Avg. Citations / Paper
24
H-Index
21
Papers
25
Citations
778
Avg. Citations / Paper
31.1
H-Index
11
Papers
6
Citations
1
Avg. Citations / Paper
0.2
H-Index
1
Papers
7
Citations
1
Avg. Citations / Paper
0.1
H-Index
1
Papers
3
Citations
4
Avg. Citations / Paper
1.3
H-Index
2
Contact and Professional Links
Detected Research Keywords
Statistical Relational Learning
Markov Logic Networks
Knowledge Intensive Learning
Learning Relational Domains
Relational Dependency Networks
Decision Theoretic Assistance
Predicting Drug Drug
Drug Drug Interactions
Statistical Relational Artificial
Relational Artificial Intelligence