Paper accepted for Stapp Car Crash Conference 2024

Paper title “Micromechanics of axonal injury in rapid tension and compression”. This is an extension work of our sex-specific axonal injury model. To be orally presented by Chaokai Zhang in Columbus, OH.

A new NIH R21 award

A new NIH award to study the biomechanical basis of sex differences in concussion and subconcussion. This is a collaborative work with colleagues at the University of British Columbia. This will allow continual development of the axonal injury models to study micromechanics of traumatic brain injury.

PI Dr. Ji co-chairing special session in CMBBE Symposium 2024

AI based brain biomechanics The session is on the recent research advances in brain biomechanics, especially image and machine-learning based brain biomechanics research. Topics include both tissue and cellular level studies on brain biomechanics, such as using multimodal imaging or deep-learning techniques for characterization and modelling of brain. https://www.cmbbe-symposium.com/2024/cmbbe-main-topics/  

ABME Best Paper Award, awarded at BMES 2023 in Seattle, WA

Collaborative work with colleagues at Virginia Tech on concussion mitigation effectiveness of helmets: [1] K. Ghazi, M. Begonia, S. Rowson, S. Ji, American Football Helmet Effectiveness Against a Strain-Based Concussion Mechanism, Ann. Biomed. Eng. 50 (2022) 1498–1509. https://doi.org/10.1007/s10439-022-03005-z.

PI Dr. Ji awarded Sigma Xi Outstanding Senior Faculty Award

  Sigma Xi Outstanding Senior Faculty Award

Two papers published in Journal of Neurotrauma back to back

One on sex differences in axonal behaviors in head impact. This study would complement our WHIM global head model to provide a new dimension of investigation on the biomechanical basis of concussion at the cellular level. Kudos to Chaokai after two-years of hard working! [1] C. Zhang, S. Ji, Sex differences in axonal dynamic responses […]

Pioneered the use of deep learning (“AI”) in brain injury modeling

Dr. Ji’s group pioneered the use of deep learning into brain injury impact modeling. The technique transcends the earlier pre-computation method also developed in the lab. It has the potential to shifting future brain injury biomechanical studies from focusing on impact accelerations to tissue strain-based investigation and analysis. [5] N. Lin, S. Wu, S. Ji, […]

PI Dr. Ji co-leads a community-wide consensus paper on brain injury modeling

Great collaboration with brain injury modelers around the world! One of the five consensus statements is to promote the use of deep learning, a.k.a., “AI” in future brain injury model development and applications. It is largely based on recent work in Dr. Ji’s lab. [1] S. Ji, M. Ghajari, H. Mao, H. Kraft, Reuben, M. […]