Zhi (Jackie) Yao joined the Georgia Tech School of Electrical and Computer Engineering as an assistant professor in 2026. She earned a B.S. in Electrical Engineering: Photonics from Zhejiang University in 2012 and M.S. and Ph.D. degrees in Electrical and Computer Engineering from UCLA in 2014 and 2017.
After postdoctoral training at UCLA, she joined Lawrence Berkeley National Laboratory as a Luis W. Alvarez Fellow in 2019 and became a Career Research Scientist in 2022.
Her work combines electromagnetics, ferroic materials, microelectronic devices, and high-performance multiphysics computing. She has developed multiferroic RF devices, open-source simulation tools, and co-design methods that connect material behavior to device and system performance. Her research at Georgia Tech focuses on programmable wave-material systems for communications, sensing, and computing.
• Ph.D., Electrical and Computer Engineering, University of California, Los Angeles, 2017
• M.S., Electrical and Computer Engineering, University of California, Los Angeles, 2014
• B.S., Electrical Engineering: Photonics, Zhejiang University, 2012
Professor Yao studies how electromagnetic waves interact with magnetic, ferroelectric, multiferroic, and acoustically active materials. Her group combines predictive modeling, artificial intelligence (AI), fabrication, and measurement to develop adaptive hardware for communications, sensing, and computing across radio-frequency, millimeter-wave, and terahertz technologies. Current interests include tunable linear and nonlinear filters, resonators, antennas, nonreciprocal components that control signal flow, and devices that use material dynamics to process information. Her long-term goal is to turn controllable material states into programmable circuit elements, enabling smaller, more energy-efficient electronic systems that can adapt to changing signal environments.
Electromagnetics and wave propagation; RF, microwave, and millimeter-wave circuits and systems; antennas; computational electromagnetics; multiphysics modeling; emerging electronic devices; and AI-assisted engineering design.
- Lawrence Berkeley National Laboratory Director's Award for Exceptional Scientific Achievement, Early Career category, 2023
- Luis W. Alvarez Postdoctoral Fellowship in Computing Sciences, Lawrence Berkeley National Laboratory, 2019-2022
- Rising Star in EECS, University of Illinois Urbana-Champaign, 2019
- First Place, Best Student Paper Competition, IEEE International Microwave Symposium (IMS), 2017
- Qualcomm Innovation Fellowship, 2015-2016
- UCLA Electrical Engineering Best Master's Thesis Award, 2014
- Z. Yao et al., “Bulk Acoustic Wave-Mediated Multiferroic Antennas: Architecture and Performance Bound,” IEEE Transactions on Antennas and Propagation, vol. 63, no. 8, pp. 3335–3344, 2015. DOI
- Z. Yao et al., “Harnessing the Power of HPC and AI for Beyond-CMOS Microelectronics Device” (invited paper), in 2025 IEEE International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2025, pp. 1–4. DOI
- J. Song et al., “HPC-Driven Modeling with ML-Based Surrogates for Magnon–Photon Dynamics in Hybrid Quantum Systems,” arXiv preprint arXiv:2510.22221, 2025. DOI
- X. Huang et al., “Manipulating Chiral Spin Transport with Ferroelectric Polarization,” Nature Materials, vol. 23, pp. 898–904, 2024. DOI
- Y. Tang et al., “A Multimodal Large Language Model for Materials Science,” Nature Machine Intelligence, vol. 8, pp. 588–601, 2026. DOI
Google Scholar Link
https://scholar.google.com/citations?user=0j1c024AAAAJ&hl=en