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Eric Wong is a researcher focused on reliable machine learning, optimization, explainability, and robustness. His work explores provable defenses against adversarial examples and develops methods for debugging and enhancing the reliability of machine learning models. Wong has contributed significantly to the field through numerous publications addressing challenges in adversarial training and performance metrics for machine learning systems. His research has implications for the deployment of machine learning in critical applications where safety and security are paramount.
Wharton Doctoral programs cover fields like Finance, Marketing, Management, and Operations, Information and Decisions.