His research focuses on efficient deep learning, TinyML, embedded systems, and memory/storage systems. Wei-Chen has received several accolades for his work, including the ACM/IEEE CODES+ISSS Best Paper Award, the IEEE NVMSA Best Paper Award, and the Best Poster Award at the NSF Athena AI Institute. In addition, he received first place (among 150 teams) in the flash consumption track of the ACM/IEEE TinyML Design Contest at ICCAD 2022. His research has received over 1,300 stars on GitHub, and his work "On-device training under 256KB memory" (MCUNetV3) was highlighted by the MIT homepage.