Yuejie Chi

My research focuses on the theoretical and algorithmic aspects of data science and machine learning, motivated by the challenge of extracting useful information and making reliable decisions from large-scale and high-dimensional data, particularly in sample-starved or resource-starved environments. Using tools in high-dimensional statistics, large-scale optimization, signal processing, sampling and information theory, we develop provably efficient algorithms, both statistically and computationally, for applications in sensing systems, imaging science, and biomedical domains.

Here is a video that highlights some of our research.

Here are some links to our collaborative projects across application domains including wireless, materials and more.

• NSF RINGS: Learning-Enabled Ground and Air Integrated Networks (GAINs)

• AFRL/AFOSR University Center of Excellence: Agile Waveform Design for Communication Networks in Contested Environments

• AFRL/AFOSR University Center of Excellence: Data-Driven Discovery Of Optimized Multifunctional Material Systems

Research Support

Our group gratefully acknowledges ongoing and past support from NSF, AFOSR, ONR, NIH, ARO, AFRL, DARPA, FHWA, Center for Surveillance Research, ORAU, Simons Foundation, Google and Microsoft.