1. CAUSAL INFERENCE
Focused on applying many of the principles & approaches outlined by Judea Pearl in his book Causality: Models, reasoning, and inference (2000, Cambridge University Press) in the context of machine learning.
2. SOCIALLY RESPONSIBLE, SUSTAINABLE MACHINE INTELLIGENCE & INTEGRATION
Focused primarily on how to develop, refine, implement, and maintain machine intelligence (includes conventional curve-fitting, machine learning, and artificial intelligence) in a socially responsible & sustainable way within large enterprises. A key characteristic of this research considers each step & component of end-to-end enterprise systems.
3. REINFORCEMENT LEARNING
Focused on a wide range of reinforcement learning approaches primarily addressing problems in banking, insurance, and asset management.
4. CREDIT RISK
Focused on developing better credit risk assessment models both for individual credit risk management and credit portfolio risk management.