Guang Cheng
Professor at UCLA
Guang Cheng is a Professor of Statistics and Data Science & Computer Science at UCLA and leads the Trustworthy AI Lab. His work centers on establishing reliable trust layers between humans and artificial intelligence, specializing in Agentic AI, Tabular AI, and high-stakes applications in finance, medicine, and gaming. A former member of the Institute for Advanced Study in Princeton, Professor Cheng is an IMS Fellow and a Simons Fellow in Mathematics.
Talks
Data Con LA 2026
Arbitrage and Insider Trading in Polymarket: Evidence and Implications
Empirical evidence on arbitrage, market efficiency, and insider trading in prediction markets, and what it means for their future design and regulation.
Data Con LA 2024
Towards Trustworthy Data Collaborations in GenAI Era
This talk explores Trustworthy Data Collaboration in the GenAI era, focusing on how Data Clean House enables secure data sharing across industries such as digital marketing, finance, and healthcare. With GDPR compliance and privacy-preserving technologies like confidential computing, it ensures collaborations without compromising data privacy.