Siheng Chen

˼ Siheng Chen

Postdoctoral research associate in ECE at CMU

Research

My research interests include graph signal processing, indirect bridge health monitoring and biomedical image analysis. I like to think about problems from both the applied and theoretical perspectives.

Graph Signal Processing

Signal processing on graphs is a theoretical framework that generalizes classical discrete signal processing from regular domains, such as lines and rectangular lattices, to arbitrary, irregular domains commonly represented by graphs. Different from network science, signal processing on graphs focuses on the interplay between the graph structure and the corresponding signals. The goal of this research is to build a theoretical foundation from the perspective of signal processing to handle practical data analysis tasks. The current work focuses on understanding and formulating such a framework for signal representations and signal recovery on graphs.

Random Walker on Tensors

We explore a tensor representation of the knowledge base with millions of subject- verb-object triples, utilize random-walk based algorithms to provide fast online search. The difference between the ordinary search engine and our system is that instead of finding what is the query, we provide interesting knowledge related to the query.

Indirect Bridge Structural Health Monitoring

We explore an indirect measurement approach for bridge structural health monitoring that collects sensed information from the dynamic responses of many vehicles travelling over a bridge and then makes extensive use of advanced signal processing techniques to determine information about the state of the bridge.

Biomedical Image Analysis

We focus on developing automated systems for analysis and interpretation of biomedical images, such as histopathology image segmentation.