About
Dr. Deepak Venugopal is an Associate Professor and Graduate Coordinator in the Department of Computer Science at the University of Memphis. He holds a PhD in Computer Science from the University of Texas at Dallas (2015). His research focuses on scalable algorithms for probabilistic graphical models, neuro-symbolic systems, and their applications in AI-driven education and cybersecurity. He leads the Learner Data Institute, exploring interdisciplinary research in educational data science.
Education:
- PhD in Computer Science, University of Texas at Dallas, 2015
Research Interests:
- Machine Learning
- Artificial Intelligence
- Probabilistic Graphical Models
- Neuro-Symbolic Systems
- Math Education Strategy Prediction
- Cybersecurity Analytics
Recent work emphasizes neuro-symbolic approaches for strategy discovery in educational data, probabilistic verification of relational explanations, and scalable inference methods. His 2020 NSF grant supports integrating Markov Logic Networks with deep learning for STEM education improvement.
Advising & Grants:
- Learner Data Institute Director
- Recipient of NSF RI: Small Grant (2020)
- Guides research on educational data mining and AI ethics
Labs & Teams:
- Learner Data Institute - advancing STEM learning through data-driven methods
- Cross-disciplinary collaborations in AI/education/cybersecurity
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