Scholars come together at Virginia Tech to discuss causality and machine learning/AI technologies | Virginia Tech News

Dan Sui, senior vice president and chief research and innovation officer, delivered opening remarks that emphasized the importance of understanding causality in research. Sui’s speech highlighted how causality, beyond simple correlations, is critical for advancing scientific discovery — especially in the university’s identified frontiers in AI, health care, security, and quantum research.

“Causality in research is of significant importance because it allows researchers to understand ‘why’ something happens, not just that two things are correlated,” Sui said. “I’m pleased to see the Kohl Centre organize such an event to explore this important topic.”

The workshop topics included the following:

• Causality in the age of generative AI
• Toward trustworthy machine learning: A causal lens on learning non-spuriousness
• Current and prospective uses of AI/ML in addressing problems related to 6G security
• Rehabilitating the once-abandoned endogenous IV
• Causal machine learning for policy evaluation with housing transaction data
• Dynamic treatment effect estimation with interactive fixed effects and short panels
• Bi-level offline reinforcement learning
• Controlling for problematic responses in survey data: a causal forest approach
• Valid post-inference for contextual bandit problems
• Randomization inference and sensitivity analysis for quantiles of individual treatment effects
• Estimating stochastic block models in the presence of covariates
• Heterogeneous complementarity and team design
• Causal inference in the presence of network interference with low-order interactions

“I am a fan of research workshops that allow for deeper interactions, including the exchange of ideas, early results, and bonding, which is highly needed for successful collaboration and community building,” said presenter Jacek Kibilda, research associate professor with the Commonwealth Cyber Initiative and Bradley Department of Electrical and Computer Engineering. “I truly enjoyed the transdisciplinary nature of the workshop, and learning how others apply and extend the causality framework in their disciplines gave me a lot of new ideas.”

The Kohl Centre serves as a hub for advancing, implementing, and disseminating state-of-the-art solutions for applied economic problem-solving through data analytics. The Kohl Centre is directed by Le Wang in the Department of Agricultural and Applied Economics. The David M. Kohl Chair was established through a generous gift from James A. and Renae C. Pearson, distinguished alumni of the university.

This prestigious chair honors Professor Emeritus David M. Kohl, who dedicated 25 years to the Department of Agricultural and Applied Economics. Throughout his career, Kohl made significant contributions to the fields of agricultural finance, small business management, and entrepreneurship. His work as an Extension economist allowed him to collaborate closely with agricultural producers, agribusinesses, lenders, and policymakers, addressing the real-world challenges faced by Virginia’s farming community and agricultural sector.

Learn more about the Kohl Centre.