I teach courses that bridge technology, data science, and business applications. My focus is helping students understand not just the technical mechanics of emerging technologies, but their strategic implications for business and society.

Teaching Approach

I bring an interdisciplinary perspective to the classroom, connecting insights from astrophysics, data science, and business analytics. Whether working with undergraduates or graduate students, I emphasize building intuition through hands-on experience with real-world problems.Multiple-time recipient of the 'Incomplete List of Teachers Rated as Excellent by Their Students' award.

My courses explore how artificial intelligence, machine learning, and distributed technologies are reshaping business—from financial reporting to strategic decision-making. I pioneered AI-driven instruction by creating multilingual avatar-based course delivery.

Current Courses

ACCY 593: AI in Business
iMBA Program, University of Illinois at Urbana-Champaign

BDI 577: Emerging Technology and Disruption
iMBA Program, University of Illinois at Urbana-Champaign

Course Materials & Open Educational Resources

I believe in open education and making high-quality course materials freely available:

UI-Deloitte Foundation Center for Business Analytics
As founding director, published entire courses through the center, with materials receiving over 1,000 downloads from six continents.The UI-Deloitte Foundation Center for Business Analytics provides free online data analytics curriculum to advance business education worldwide.

Software Carpentry Curricula
Developed: - SQL for Business - Python for Business

GitHub Course Repositories
Maintain open-source course materials covering data science, machine learning, and business analytics.Course materials available through github.com/lcdm-uiuc and github.com/ProfessorBrunner

Selected Coursera MOOCs

I've developed data analytics curricula and created multiple MOOCs in partnership with Coursera that have reached global audiences:

• Data Analytics for Accountancy, Part I
• Data Analytics for Accountancy, Part II
• Navigating Disruptions: Emerging Technologies
• Blockchains, Tokens, and the Decentralized Future
• Introduction to Artificial Intelligence
• Advanced Topics in Artificial Intelligence

Research on Data Science Education

Teaching Data Science
Brunner, R. J., & Kim, E. J. (2016).
Procedia Computer Science, 80, 1947-1956.
Paper | arXiv:1604.07397

Describes our approach to teaching introductory data science with no prerequisites, covering topics from data storage and visualization to probability, statistics, and high-performance computing using Python.