My current research is focused on building deep and large-scale natural language understanding models with limited computational resources and annotated data. Accordingly, some of my focused research topics are on self-supervised, weakly supervised and semi-supervised learning, curriculum learning, knowledge distillation and multi-lingual transfer learning.
Prior to joining MSR, I was leading the information extraction efforts to build the Amazon Product Knowledge Graph, an authoritative knowledge graph for all products in the world. I graduated summa cum laude from the Max Planck Institute for Informatics, Germany with a PhD in 2017. I was awarded the 2018 SIGKDD Doctoral Dissertation Runner-up Award for my thesis on credibility analysis and misinformation. I previously worked at IBM Research on domain adaptation of question-answering systems, sentiment analysis and opinion mining. I published over 40 research papers in top conferences on various topics in natural language understanding and data mining.