Deepak Venugopal
About
Dr. Deepak Venugopal joined the Department as an assistant professor in Fall 2015 after completing his PhD in computer science at the University of Texas at Dallas. Dr. Venugopal's primary research interest is in developing fast, scalable, and accurate algorithms for inference and learning in probabilistic graphical models and their first-order extensions such as Markov Logic Networks. His work has resulted in key techniques that lift approximate inference methods to first-order models and has been published in several top-tier conferences in Machine Learning and Artificial Intelligence, such as NIPS, AAAI, UAI, and EMNLP.
Research Performance Summary
First Recorded Paper
An efficient signature representation and matching method for mobile devices
Year: 2006
Citations: 29
Venue: Proceedings of the 2nd annual international workshop on Wireless internet, 16-es
Latest Recorded Paper
Analyzing Strategies inĀ MATHia withĀ BERT
Year: 2025
Citations: 0
Venue: Artificial Intelligence in Education. AIED 2025 Conference proceedings
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.