Graduate Study
University of Illinois at Urbana-Champaign
- Master of Science in Electrical and Computer Engineering (Aug. 2017 - Dec. 2019).
- Doctor of Philosophy in Electrical and Computer Engineering (Jan. 2020 - Present).
- GPA: 3.95/4.00.
Key Courses
- Digital Signal Processing II
- Vector Space Signal Processing
- Random Processes
- Detection and Estimation Theory
- Information Theory
- Statistical Learning
- Statistical Learning Theory
- Pattern Recognition
- Computational Inference
Teaching Experience
- Teaching assistance: Probability with Engineering Applications
Reseach Accomplishments
- Proposed a novel method to enable high-resolution mapping of metabolites and neurotransmitters of the brain in 12 minutes. This is the first technology that provides this unprecedented capability for non-invasive brain mapping. Preliminary results have been presented at the International Society of Magnetic Resonance in Medicine 2020.
- Proposed a new method for reconstruction of high-resolution and high-SNR tissue sodium concentration maps. This provides a significant improvement over the-state-of-art sodium imaging techniques, and has the potential for various clinical applications including accurate interrogation of small anatomic targets like hippocampus in Alzheimer’s disease and detection of spatially heterogeneous responses of tumor to treatment. A Rapid Communication paper has been published in Magnetic Resonance in Medicine.
- Solved several key technical problems to enable clinical applications of 3D ultrafast high-resolution MR spectroscopic imaging (MRSI). The resulting technology laid the foundation for several clinical studies (by Prof. Yao Li’s and Prof. Jie Luo’s groups), which resulted in more than 20 papers accepted for oral presentation at the International Society of Magnetic Resonance in Medicine 2019 to 2022 and a cover feature article in Brain.
Master Thesis
- Accelerated J-Resolved Proton Magnetic Resonance Spectroscopic Imaging [Link]