Robert Brunner

For More Information

• Gies College of Business Profile Web Site

Research Statement

My recent research focuses on the intersection of statistical and machine learning techniques with real-world problems in business, finance, and society. This work has advanced the use of graph neural networks (GNNs) for financial market prediction, high-frequency trading analysis, and community detection in economic data. Current studies include innovative approaches for forecasting equity markets using GNNs on financial correlation networks and developing unified frameworks for industry recovery via intraday stock data and advanced analytics.

Other ongoing projects investigate the reliability and impact of AI annotation methods in financial text corpora—a critical step for building next-generation financial analytics platforms. Across all efforts, this research brings cutting-edge technology to practical challenges, helping organizations make better data-driven decisions, anticipate disruptions, and harness quantum computing for more predictive business models.