Events Calendar

CS Colloquium: Muhao Chen (USC ISI) - Knowledge Acquisition with Transferable Representation Learning

Speaker: Muhao Chen, USC

Talk Title: Knowledge Acquisition with Transferable Representation Learning

Abstract: Multi-relational data provide structural and actionable knowledge representations for various AI systems. As constructing such structural knowledge is often costly and has relied on extensive human effort, there is a pressing need for approaches to automate knowledge acquisition. In this talk, I will summarize two lines of my research to accomplish this mission: (i) transferable representation learning, and (ii) constrained and indirect supervision. Transferable representation learning can automatically capture the association of knowledge across different data sources with minimal supervision, therefore holds the promise of creating a universal representation scheme to support the synchronization of knowledge. Meanwhile, constrained and indirect supervision methods could develop more reliable learning systems for knowledge acquisition from unstructured data, particularly in cases without sufficient training labels. Based on these two lines of research, I will also discuss several applications for a wide range of tasks in areas of knowledge base construction, natural language understanding and computational biology.

This talk satisfies requirements for CSCI 591: Research Colloquium

Join Zoom Meeting
https://usc.zoom.us/j/96706950791?pwd=cXp3TWlhRmo5ZDB0bnA0a0lOQ1VVdz09

Meeting ID: 967 0695 0791
Passcode: 808248


Biography: Muhao Chen joined as a computer scientist at USC ISI in Fall 2020. Prior to that, he was a postdoctoral fellow at UPenn, hosted by Dan Roth. He received his Ph.D. in Computer Science from UCLA in 2019, and B.S. in Computer Science from Fudan University in 2014. His research focuses on data-driven machine learning approaches for processing structured data, and knowledge acquisition from unstructured data. Particularly, he is interested in developing knowledge-aware learning systems with generalizability and requiring minimal supervision, and with concrete applications to natural language understanding, knowledge base construction, computational biology and medicine. Muhao has published over 40 papers in leading AI, NLP and Comp. Bio/med venues. His work has received a best student paper award at ACM BCB, and best paper award nomination at CoNLL. Additional information is available at https://muhaochen.github.io/

Host: CS Department

Audiences: Everyone Is Invited

Contact: Cherie Carter