Subject areas: Deep Learning, Machine Learning, Decision-Making under Stochasticity and Uncertainty, Healthcare Data Mining.
Keywords/Tags: AI, reinforcement learning, deep learning, learning to control, big data, transfer learning, machine learning, decision making, stochastic optimization, computational statistics.
- Algorithm Design and Theoretical Analysis of Reinforcement Learning and Sequential Decision-Making
- Trustworthy, Interpretable, and Risk-aware Machine Learning
- Adaptive and Robust Learning, Control, and Optimization
His primary research area covers decision-making under uncertainty, human-aided machine learning, symbolic AI, trustworthiness and interpretability in machine learning, and their numerous applications to BIGDATA, autonomous driving, and healthcare informatics.
His primary research area covers interactive machine learning, especially reinforcement learning, bandits, explainable AI, stochastic optimization, and their numerous applications to AI and BIGDATA.
My major research focus is interactive machine learning (such as reinforcement learning, human-aided learning) and trustworthy AI (such as interpretable AI, safe and risk-aware AI, fairness in AI, etc.).