Wendi Guo

Short presentation

Dr. Wendi Guo develops digital twin–driven design frameworks that treat battery lifetime and performance as a priori design targets rather than outcomes revealed through long-term testing. Her work bridges physical and virtual domains by integrating electrochemical modelling, experimental validation, and physics-informed AI to establish explicit links between design parameters and lifetime-relevant health indicators.

Keywords

• digital twins
• physics informed AI
• battery design
• smart charging protocols

Biography

Dr. Wendi Guo received her B.Sc. in Safety Engineering and M.Eng. in Reliability Engineering from Beihang University, Beijing, China, in 2018 and 2021, respectively. She obtained her Ph.D. from Aalborg University, Denmark, where her research focused on physics-informed machine learning for lithium-ion battery degradation prediction.

She is currently a Postdoctoral Fellow working on degradation mitigation and safe operation of batteries in Vehicle-to-Grid (V2G) systems. Her research centres on digital twin–enabled, lifetime-aware design by integrating electrochemical modelling, experimental insights, and physics-informed AI.

Dr. Guo has held visiting research positions at Chalmers University of Technology, Imperial College London, and Technical University of Munich. She received the Best Poster Award at the IPEMC ECCE Asia Conference 2024 and travel grants for early-career researchers at the ECS Conference 245th and ECS Conference 248th.

She actively contributes to the academic community as a reviewer for 16 leading journals and as a contributor to the white paper “Power Semiconductors for an Energy-Wise Society.”

Research

Her research focuses on developing digital twin–enabled design frameworks that integrate multiphysics modelling, physics-informed AI, and experimental validation to enable lifetime-aware energy storage systems.

Media

https://bemars.dk/

https://www.linkedin.com/company/esa-bic-denmark/posts/?feedView=images&viewAsMember=true