Machine Learning in Battery Estimation: This covers methods and theoretical developments for estimating the state of charge (SOC) and state of health (SOH) of batteries in electric vehicles.
Thermal Runaway Safety: Papers exploring the triggers, consequences, and mitigation methods for thermal runaway in lithium-ion batteries.
Battery Thermal Management: Reviews discussing strategies to enhance thermal management systems for EV batteries.
Mechanical Abuse and Battery Safety: Reviews analyzing mechanical abuse-related thermal runaway models across different scales.
Monte Carlo Dropout in Autonomous Vehicles: A paper on leveraging Monte Carlo dropout for real-time uncertainty quantification in object detection, with applications in autonomous vehicles.
The candidate demonstrates significant potential and achievements for the Best Researcher Award in Engineering at Jilin University. Their educational background, focused expertise in intelligent electric vehicles, and contributions to a nationally funded project underline their research capabilities and innovative approach. To further strengthen their candidacy, focusing on high-impact publications, securing PI roles, and fostering international collaborations will solidify their standing as a leading researcher.