Research Interests

My research interests include data privacy and security, and adversarial machine learning. As a practitioner in this field, I am interested in finding and solving real problems in a pragmatic manner. The following are some research fields that I am currently working on.

• Differential Privacy

  With the prevalence of big data analytics, service providers become increasingly enthusiastic in collecting and analyzing usage data to improve their services. However, the collection of user data comes at the price of privacy risks, not only for users but also for service providers who are vulnerable to internal and external data breaches. As an answer to privacy-preserving data collection and analysis, Differential Privacy, either in its centralized or local setting, has become a de facto standard for individual privacy protection.

• Adversarial Machine Learning

  With the prevalence of Big Data and AI, machine learning models are trained and deployed to facilitate humans in daily life. However, in many hostile environments, the training and deployment of these models can be undermined and their integrity can be severely jeopardized. Adversarial machine learning studies such security issues and aims for the confidentiality, integrity, availability, and accountability of machine learning techniques under malicious and stressful settings.