Research Expertise and Interest
unsupervised language acquisition, efficient algorithms for NLP, linguistically rich models of language, integrating symbolic and statistical methods for NLP, organization of the web, machine translation, information extraction
Research Description
Dan Klein is a Professor of Computer Science. His research focuses on the automatic organization of natural language information. Some topics of interest to him are:
- Unsupervised language acquisition
- Machine translation
- Efficient algorithms for NLP
- Information extraction
- Linguistically rich models of language
- Integrating symbolic and statistical methods for NLP
- Historical linguistics
His group is the Berkeley Natural Language Processing Group. He is also interested in AI more broadly.
In the News
Bakar Fellows Program Names Seven New Spark Award Recipients
Scientists create automated ‘time machine’ to reconstruct ancient languages
Ancient languages hold a treasure trove of information about the culture, politics and commerce of millennia past. Yet, reconstructing them to reveal clues into human history can require decades of painstaking work. Now, scientists at the University of California, Berkeley, have created an automated “time machine,” of sorts, that will greatly accelerate and improve the process of reconstructing hundreds of ancestral languages.