I develop novel machine learning solutions for natural language understanding problems. I build AI applications that interact with and learn from people.
My research interest has been under the following themes:

Self-supervised Learning and Few-shot Learning: Zero/few-shot learning with large-scale language models.
Neural Symbolic Representation and Reasoning: Learning representation that jointly encodes textual and symbolic knowledge to support reasoning in downstream tasks.
Natural Language Interfaces: Learning to map user utterances to executable machine instructions in complex scenarios; building natural language powered software interfaces.
Fairness and Accountability: Mitigating unwanted model biases; improving model robustness; uncovering social biases via text analysis.