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Molinaroli College of Engineering and Computing

Faculty and Staff

Ahmed A. Alshareef

Title: Assistant Professor, Mechanical Engineering, Biomedical Engineering
Department: Mechanical Engineering, Biomedical Engineering
Molinaroli College of Engineering and Computing
Office: Room A111
300 Main
Resources: Google Scholar
Ahmed Alshareef headshot


Dr. Alshareef's research interests include injury biomechanics, experimental characterization of biological tissue, computational biomechanics, and magnetic resonance imaging (MRI). Prior to joining USC, he was a scientist in the radiology department at the NIH Clinical Center (2022) after a postdoctoral fellowship at Johns Hopkins University (2019-2021), where he studied the biomechanics of traumatic brain injury using specialized, non-invasive MRI techniques.

Dr. Alshareef completed his B.S. at Duke University in biomedical engineering in 2014, with a focus on biomechanics and tissue engineering. He then received his PhD in BME at the University of Virginia in 2019, with a dissertation focused on experimental and computational investigations of brain deformation in humans during head impact. His lab's current research interests are aimed at using advanced experimental and computational techniques to measure and model the biomechanics of biological tissue for injury and disease prevention.


  • Ph.D., Biomedical Engineering, University of Virginia, 2014-2019
  • B.S., Biomedical Engineering, Duke University, 2010-2014


Virginia Engineering Foundation Graduate Fellowship  - 2018
Anthony Marmarou Award from the National Neurotrauma Society - 2017

Research Overview

Biomechanics plays an important role in understanding, preventing, and healing injury and disease in the human body. A fundamental understanding of the mechanics of biological tissues allows us to employ experimental and computational methods to assess mitigation strategies, as well as tailor patient-specific surgical and therapeutic interventions. Our lab's current research is aimed at:

  • Experimental characterization of biological tissue deformation and mechanics
  • Multi-physics biomechanics simulations of injury and disease using finite element models
  • Biomechanical ‘digital twins’ through patient-specific simulations to inform safety design and clinical decision-making
  • Statistical filtering and data-driven reduction methods to supplement sparse data and improve model prediction

Challenge the conventional. Create the exceptional. No Limits.