Honors & Awards


  • Innovators Under 35, Global List, MIT Technology Review (2019/06)
  • Young Investigator Award, American Chemistry Society DIC (2018/08)
  • Siebel Scholar, Thomas and Stacey Siebel Foundation (2016/10)
  • Dan David Prize Scholarship, Dan David Foundation (2016/05)
  • MRS Graduat Students Award, Materials Research Society (2014/04)

Professional Education


  • Master of Science, Fudan University (2012)
  • Doctor of Philosophy, University of California San Diego (2017)

All Publications


  • Electronic skins and machine learning for intelligent soft robots SCIENCE ROBOTICS Shih, B., Shah, D., Li, J., Thuruthel, T. G., Park, Y., Iida, F., Bao, Z., Kramer-Bottiglio, R., Tolley, M. T. 2020; 5 (41)
  • Intrinsically stretchable electrode array enabled in vivo electrophysiological mapping of atrial fibrillation at cellular resolution. Proceedings of the National Academy of Sciences of the United States of America Liu, J., Zhang, X., Liu, Y., Rodrigo, M., Loftus, P. D., Aparicio-Valenzuela, J., Zheng, J., Pong, T., Cyr, K. J., Babakhanian, M., Hasi, J., Li, J., Jiang, Y., Kenney, C. J., Wang, P. J., Lee, A. M., Bao, Z. 2020

    Abstract

    Electrophysiological mapping of chronic atrial fibrillation (AF) at high throughput and high resolution is critical for understanding its underlying mechanism and guiding definitive treatment such as cardiac ablation, but current electrophysiological tools are limited by either low spatial resolution or electromechanical uncoupling of the beating heart. To overcome this limitation, we herein introduce a scalable method for fabricating a tissue-like, high-density, fully elastic electrode (elastrode) array capable of achieving real-time, stable, cellular level-resolution electrophysiological mapping in vivo. Testing with acute rabbit and porcine models, the device is proven to have robust and intimate tissue coupling while maintaining its chemical, mechanical, and electrical properties during the cardiac cycle. The elastrode array records epicardial atrial signals with comparable efficacy to currently available endocardial-mapping techniques but with 2 times higher atrial-to-ventricular signal ratio and >100 times higher spatial resolution and can reliably identify electrical local heterogeneity within an area of simultaneously identified rotor-like electrical patterns in a porcine model of chronic AF.

    View details for DOI 10.1073/pnas.2000207117

    View details for PubMedID 32541030

  • Morphing electronics enable neuromodulation in growing tissue. Nature biotechnology Liu, Y., Li, J., Song, S., Kang, J., Tsao, Y., Chen, S., Mottni, V., McConnell, K., Xu, W., Zheng, Y. Q., Tok, J. B., George, P. M., Bao, Z. 2020

    Abstract

    Bioelectronics for modulating the nervous system have shown promise in treating neurological diseases1-3. However, their fixed dimensions cannot accommodate rapid tissue growth4,5 and may impair development6. For infants, children and adolescents, once implanted devices are outgrown, additional surgeries are often needed for device replacement, leading to repeated interventions and complications6-8. Here, we address this limitation with morphing electronics, which adapt to in vivo nerve tissue growth with minimal mechanical constraint. We design and fabricate multilayered morphing electronics, consisting of viscoplastic electrodes and a strain sensor that eliminate the stress at the interface between the electronics and growing tissue. The ability of morphing electronics to self-heal during implantation surgery allows a reconfigurable and seamless neural interface. During the fastest growth period in rats, morphing electronics caused minimal damage to the rat nerve, which grows 2.4-fold in diameter, and allowed chronic electrical stimulation and monitoring for 2 months without disruption of functional behavior. Morphing electronics offers a path toward growth-adaptive pediatric electronic medicine.

    View details for DOI 10.1038/s41587-020-0495-2

    View details for PubMedID 32313193

  • A wireless body area sensor network based on stretchable passive tags NATURE ELECTRONICS Niu, S., Matsuhisa, N., Beker, L., Li, J., Wang, S., Wang, J., Jiang, Y., Yan, X., Yuri, Y., Burnetts, W., Poon, A. Y., Tok, J., Chen, X., Bao, Z. 2019; 2 (8): 361–68