- Published multiple papers, including DAC'25, CPAL'25, ASPLOS'24, etc.
- Filed one patent and received one NSF award
- Developed an ultra-lightweight VSA classifier library for tiny microcontrollers, MicroVSA
- Explored the application of low-dimensional computing classifiers in brain-computer interfaces
- Proposed a learning-based hyperdimensional computing classifier, LeHDC
Research Experience
- Participated in multiple research projects, such as Ultra-Lightweight Binary Vector Symbolic Architecture (VSA)
- Collaborated with Prof. Shaolei Ren at UCR to advance VSA in machine learning
- Worked with Prof. Yunsi Fei and Prof. Aidong Ding at NEU on graph structure representation using cross-correlation autoencoders
Education
- Ph.D.: Northeastern University, Department of Computer Engineering, under the supervision of Prof. Xiaolin Xu
- Master's Degree: University of Illinois, Chicago, with a focus on machine learning, convex optimization, and robotic algorithms
Background
- Research Interests: Efficient Machine Learning (software-hardware co-design), Machine Learning Security and Privacy, Graph Machine Learning, Quantum Learning, and other related topics
- Field: Computer Engineering
- Introduction: Currently pursuing a Ph.D. at Northeastern University, focusing on machine learning, convex optimization, and robotic algorithms.