Xing Liu has completed his B.S. degree in Microelectronics in June 2022 from Fudan University, China. During his undergraduate studies, he served as the Academic Department Head of the School of Microelectronics and received several honors and scholarships. He was a visiting student in the Center of Excellence in Biomedical Research on Advanced Integrated-on-chips Neurotechnologies (CenBRAIN Neurotech) of Westlake University from September 2021 to April 2022. He is now a Ph.D. student in CenBRAIN Neurotech.

Xing Liu focuses on the design of analog circuits for biomedical applications, specifically targeting the introduction of user-friendly biomedical monitoring and therapeutic devices. Key research topics of his activities include low-power energy management, hybrid energy harvesting, and self-powered systems. He strives to optimize power consumption, explore multiple energy sources for sustainable operation, and design self-sufficient systems that can acquire and utilize energy from the environment. He aims to implement effective devices that improve healthcare outcomes for patients and professionals.

[1] Wu, H., Liu, X., Yang, J., & Sawan, M. (2022, October). A Power-Efficient Source-Follower Based Tunable Pseudo-RC Low-Pass Filter for Wearable Biomedical Applications. In 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS) (pp. 178-182). IEEE.

[2] Chen, J., Wu, H., Liu, X., Eskandari, R., Tian, F., Zou, W., ... & Sawan, M. (2023, June). NeuroBMI: A New Neuromorphic Implantable Wireless Brain Machine Interface with A 0.48 µW Event-Driven Noise-Tolerant Spike Detector. In 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS) (pp. 1-5). IEEE.

[3] Wu, H., Chen, J., Liu, X., Zou, W., Yang, J., & Sawan, M. (2023). An Energy-Efficient Small-Area Configurable Analog Front-End Interface for Diverse Biosignals Recording. IEEE Transactions on Biomedical Circuits and Systems.