Carol Mak

Carol's research interest spans several areas of computer science:

• Agentic workflows: designing systems that can automatically plan and execute complex tasks;
• Generative machine learning: advancing techniques to create models that generate unseen contents;
• Foundation models: investigating the capabilities and limitations of deep neural networks trained on vast amounts of data;
• Theory of computation: exploring the theoretical foundations of computations and algorithms;
• Probabilistic programming languages: developing new algorithms to inference complex probabilistic models.