Principal Ai Deng has authored two papers on antitrust issues. The first, “Measuring Benchmark Damages in Antitrust Litigation: Extension and Practical Implications,” looks at a study of two reduced-form regression-based estimators of cartel overcharges—the forecasting approach and the fully interacted approach—and extends it in multiple directions. Dr. Deng concludes that there are good reasons the former approach is the more robust and cost-effective option. In his second article, “When Machines Learn to Collude: Lessons from a Recent Research Study on Artificial Intelligence,” Dr. Deng extends his examination of antitrust issues to the concerns regarding algorithmic collusion. Examining a recent research study on artificial intelligence, he offers insights and lessons for the antitrust community.