Pennsylvania State University

Courses Taught at Pennsylvania State University

• AI 100: Artificial Intelligence: The Very Idea (Undergraduate, General Education)
• Principles of Artificial Intelligence (Graduate)
• Principles of Machine Learning (Graduate)
• DS 310: Machine Learning for Data Science (Undergraduate)
• DS 560: Principles of Causal Inference (Graduate)
• Data Science for Researchers and Scholars
• IST 510: Computational Foundations of Informatics (Graduate)

Courses Taught at Iowa State University

• Principles of Artificial Intelligence (Com S 472, Com S 572)
• Principles of Machine Learning (Com S 573)
• Computational Functional Genomics and Systems Biology (BCB 570, Com S 570)
• Elements of Neural Computation ComS 474
• Multi-agent Systems ComS 574
• Computational Models of Learning ComS 672
• Advanced Topics in Artificial Intelligence and Cognitive Modelling

Honavar has taught several seminar courses covering advanced topics in machine learning, causal inference, probabilistic graphical models, multi-agent systems, deep learning, semantic web, bioinformatics, systems biology, information integration, neural computation, knowledge representation, and related topics.

Curriculum Development

• Data Sciences Undergraduate Program, Pennsylvania State University
• Biomedical Data Sciences PhD Training Program, Pennsylvania State University.
• Bioinformatics and Computational Biology PhD Program, Iowa State University.

Honavar is especially interested in developing curricula that introduce the principles of computing across multiple disciplines.