About

David B. Camarillo is an Associate Professor of Bioengineering, and by courtesy, of Neurosurgery and Mechanical Engineering at Stanford University. He holds a B.S.E. in Mechanical and Aerospace Engineering from Princeton University, a Ph.D. in Mechanical Engineering from Stanford University, and completed postdoctoral fellowships in Biophysics at UCSF and Biodesign Innovation at Stanford. Dr. Camarillo has industry experience working in surgical robotics at Intuitive Surgical and Hansen Medical before establishing his laboratory at Stanford in 2012. His current research focuses on precision human measurement across multiple clinical and physiological areas, including the brain, heart, lungs, and reproductive system. He has received several honors such as the Hellman Fellowship and the Office of Naval Research Young Investigator Program award, and his work has been recognized with multiple best paper awards in brain injury and robotic surgery. His research has been funded by prominent organizations including the NIH, NSF, DoD, as well as corporations and private philanthropy. His lab’s research has been featured in various media outlets, including NPR, The New York Times, The Washington Post, Science News, ESPN, and TED.com.

Research topics

• Computer Science
• Artificial Intelligence
• Physical therapy
• Simulation
• Medicine
• Geology
• Physics
• Engineering
• Machine Learning
• Structural engineering
• Geography
• Geodesy
• History
• Statistics
• Mathematics
• Physical medicine and rehabilitation

Selected publications

• The effect of coupling a helmet and shoulder pads on head and neck loading in American football impacts

  Proceedings of the Institution of Mechanical Engineers Part P Journal of Sports Engineering and Technology · 2026-05-14

  article

  Novel technologies that mitigate head impact severity can contribute to reducing TBI risk in helmeted activities. This study evaluated the efficacy of prototype equipment that couples a helmet and shoulder pads during head impacts representative of American football. A custom test fixture accelerated the head, neck, torso, and pelvis of an anthropomorphic test device (ATD) into a second, stationary ATD so that head and neck loading could be assessed for both players involved in an impact. Three equipment configurations were tested, each at 6.7 m/s and 4.4 m/s: (i) both ATDs wore a standard helmet and shoulder pads, (ii) the accelerated ATD wore the prototype while the stationary ATD wore a standard helmet and shoulder pads, and (iii) both ATDs wore the prototype. The prototype yielded significant reductions in peak linear accelerations of the head for both ATDs at 6.7 m/s, but only one ATD at 4.4 m/s. Reductions in angular head kinematics were inconsistent across the different equipment configurations and test conditions. Significant reductions in upper neck loading (both force and moment) were reduced in both ATDs as a result of wearing the coupled equipment in all but one scenario.

  PublisherDOI

• Linear Acceleration Is a Primary Risk Factor for Concussion and a Target for Prevention.

  PubMed · 2026-03-24

  articleSenior author

  Head impacts can cause concussion, but the precise biomechanical conditions that produce injury remain uncertain. Rotational acceleration has long been posited as the primary cause and has guided concussion prevention strategies. Using instrumented mouthguards to record head kinematics of diagnosed concussions, we directly tested this hypothesis and found that linear acceleration predicted injury with greater precision than rotational acceleration, while rotational velocity provided additional predictive value. Injury risk functions derived from these measurements indicated substantial predicted concussion risk during typical impacts to an American football helmet. Introducing a liquid-filled helmet pad designed to attenuate linear acceleration reduced predicted risk by up to 52%. These results indicate that effective concussion prevention requires targeting linear acceleration.

  Publisher

• AI-Based Identification of Head Impact Locations, Speeds, and Force Based on Head Kinematics Simulations

  IEEE Transactions on Biomedical Engineering · 2025-06-19 · 3 citations

  articleSenior author

  OBJECTIVE: With the development of wearable sensors, head kinematics data have become widely available. However, key impact information-such as impact direction, speed, and force-which is crucial for helmet development, is still not being directly measured. This study presents a deep learning model designed to accurately predict these head impact parameters from head kinematics during helmeted impacts. METHODS: Leveraging a dataset of 16,000 simulated helmeted head impacts using the Riddell helmet finite element model, we implemented a Long Short-Term Memory (LSTM) network to process the head kinematics: linear accelerations and angular velocities. RESULTS: In the simulated dataset, the models accurately predict the impact information describing impact direction, speed, and the impact force profile with $R^{2}$ exceeding 70% for all tasks. Further validation was conducted using an on-field dataset recorded by instrumented mouthguards and videos, consisting of 79 head impacts in which the impact location can be clearly identified. The deep learning model significantly outperformed existing methods, achieving a 79.7% accuracy in identifying impact locations, compared to lower accuracies with traditional methods (the highest accuracy of existing methods is 49.4%). CONCLUSION: The precision on simulations underscores the model's potential in enhancing helmet design and safety in sports by providing more accurate impact data. Future studies should test the models across various helmets and sports on large in vivo datasets to validate the accuracy of the models, employing techniques like transfer learning to broaden its effectiveness.

  PublisherDOI

• Evaluation of brain response to head impact in youth girls’ soccer using an atlas-based finite element model

  Computer Methods in Biomechanics & Biomedical Engineering · 2025-10-24

  article

  The current study examines head impact exposure in youth soccer and quantifies the relationship between impact location, impact magnitude and brain deformation using data previously collected with an instrumented mouthpiece in combination with a high-resolution brain finite element (FE) model. This study demonstrates that maximum principal strain (MPS) varies by impact source. The largest strains were observed when the ball was kicked prior to the header and the smallest strains were observed resulting from impacts when the headed ball was received from another header.

  PublisherDOI

• Longitudinal Cognitive Performance and Cerebral Perfusion in High and Low-Contact Sport Athletes

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

  article

  Motivation: Head impact in contact sports is linked to long-term cognitive decline, but etiology and mechanism remain unclear. Goal(s): To define the relationship between longitudinal cognitive performance and cerebral blood flow associated with high-contact sports. Approach: We assessed longitudinal cerebral blood flow and cognitive performance in collegiate athletes using arterial spin labeling (ASL) and the ImPACT test. Results: Visual motor speed declined over time in high-contact athletes. Significant CBF-time interactions indicate decreasing occipital CBF and higher thalamic CBF are associated with declining visual motor speed. Visual and verbal memory decline and symptoms over time are associated with higher deep-gray CBF. Impact: This research provides critical insights into how cerebral blood flow patterns are associated with cognitive performance and symptom progression in high-contact athletes.

  PublisherDOI

• Linear Acceleration Is a Primary Risk Factor for Concussion and a Target for Prevention

  arXiv (Cornell University) · 2025-07-12

  preprintOpen accessSenior author

  Head impacts can cause concussion, but the precise biomechanical conditions that produce injury remain uncertain. Rotational acceleration has long been posited as the primary cause and has guided concussion prevention strategies. Using instrumented mouthguards to record head kinematics of diagnosed concussions, we directly tested this hypothesis and found that linear acceleration predicted injury with greater precision than rotational acceleration, while rotational velocity provided additional predictive value. Injury risk functions derived from these measurements indicated substantial predicted concussion risk during typical impacts to an American football helmet. Introducing a liquid-filled helmet pad designed to attenuate linear acceleration reduced predicted risk by up to 52%. These results indicate that effective concussion prevention requires targeting linear acceleration.

  PublisherOA PDFDOI

• Volumetric Histology via High-Fidelity Coregistration with MRI

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

  article

  Motivation: Corroborating findings in 3D from ex-vivo MRI with densely-sampled histology is essential to biomarker development, but challenging due to nonlinear 3D deformations. Goal(s): Reconstructing volumetric histology by accurately aligning densely-sampled histological images with post-mortem MRI data to enhance validation of 3D pathological findings. Approach: We built and optimized a novel pipeline integrating advanced imaging with precise registration algorithms to link high-resolution MRI via blockface imaging to volumetric 3D histology aligned. Results: Our optimized blockface volumes contain minimal artifacts and were precisely aligned with MRI, facilitating the coregistration of multi-slice histology, and demonstrating accurate correspondences between MRI and histology slides in 3D. Impact: This study introduces an advanced correlative MRI-histology pipeline to reconstruct volumetric histology, promising to enhance our understanding of neurodegenerative diseases and contribute to the evolution of MRI-based disease biomarkers.

  PublisherDOI

• A porcine model of realistic closed-head impacts with multiple-timepoint MRI

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

  article

  Motivation: Mild traumatic brain injury (mTBI) is a global health challenge, yet its mechanism is not understood. Human post-impact imaging is multi-factorial and variable. Studies to unveil the local brain injury cascade are needed. Goal(s): To present a porcine model of realistic human-mimicking head impacts with multiple MRI timepoints and histologic validation. Approach: A linear impactor delivers a head impact leading to high rotational accelerations. We record biomechanics and perform detailed pre-/post-impact MR on a human scanner, ex vivo MR, coregistered histology, and finite-element modeling (FEM). Results: We identify injury on in vivo and ex vivo MRI, predict with FEM, and validate with pathology. Impact: Our novel large-animal linear-impact head impact model can detect injury with pre- and post-impact in vivo and ex vivo MRI, pathology, and finite-element modeling. This paradigm can uncover the microstructural, biomechanical, and molecular mechanism of head impact-induced brain injury.

  PublisherDOI

• Precise MRI-Histology Coregistration of Paraffin-Embedded Tissue with Blockface Imaging

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-06-05

  preprintOpen access

  translation. Coregistering the two is key for the 3D-embedding of histological details, validating pathological MRI findings, and finding quantitative imaging biomarkers of neurodegenerative diseases. However, coregistration is challenging due to non-linear distortions of the tissue from histological processing and sectioning leading to microscopic and macroscopic nonlinear 3D deformations between specimen MRI and stained histology sections. To address this, we developed a novel pipeline, named Brewster's Blockface Quantification (BBQ), integrating robust optical approaches with innovative 2D and 3D registration algorithms to achieve precise volumetric alignment of specimen MRI data with histological images. On a variety of brain tissue specimens from distinct anatomical regions and across multiple species, our methodology generated blockface volumes with minimal distortion and artifacts. Using these blockface volumes as an intermediary, we achieve a precise alignment between MRI and histology slides, yielding registration results with an overlapping Dice score of ~90% for whole tissue alignment between MRI and blockface volumes, and >95% for 2D MRI-histology registration. This correlative MRI-histology pipeline with robust 2D and 3D coregistration methods promises to enhance our understanding of neurodegenerative diseases and aid the development of MRI-based disease biomarkers.

  PublisherOA PDFDOI

• Precise MRI-histology coregistration of paraffin-embedded tissue with blockface imaging

  Imaging Neuroscience · 2025-01-01

  articleOpen access

  translation. Coregistering the two is key for the 3D embedding of histological details, validating pathological MRI findings, and identifying quantitative imaging biomarkers of neurodegenerative diseases. However, coregistration is challenging due to non-linear distortions of the tissue from histological processing and sectioning leading to microscopic and macroscopic nonlinear 3D deformations between specimen MRI and stained histology sections. To address this, we developed a novel pipeline, named Brewster's Blockface Quantification (BBQ), integrating robust optical approaches with innovative 2D and 3D registration algorithms to achieve precise volumetric alignment of specimen MRI data with histological images. On a variety of brain tissue specimens from distinct anatomical regions and across multiple species, our methodology generated blockface volumes with minimal distortion and artifacts. Using these blockface volumes as an intermediary, we achieve a precise alignment between MRI and histology slides, yielding registration results with an overlapping Dice score of ~90% for whole tissue alignment between MRI and blockface volumes, and >95% for 2D MRI-histology registration. This correlative MRI-histology pipeline with robust 2D and 3D coregistration methods promises to enhance our understanding of neurodegenerative diseases and aid the development of MRI-based disease biomarkers.

  PublisherDOI

Recent grants

• Investigation of an Instrumented Mouthguard for Measuring Head Impact Exposure

  NIH · $28k · 2013–2015

• Investigation of an Instrumented Mouthguard for Measuring Head Impact Exposure

  NIH · $458k · 2013–2015

• Disseminating a validated mouthguard sensor to investigate the effect of head impacts on brain health

  NIH · $1.1M · 2017–2022

Frequent coauthors

• Gerald A. Grant

  Stanford University

  85 shared

• Michael Zeineh

  82 shared

• Yuzhe Liu

  Fudan University

  54 shared

• Maged Goubran

  Stanford University

  42 shared

• Sohrab Sami

  37 shared

• Max Wintermark

  University of Maryland, Baltimore

  37 shared

• Xianghao Zhan

  Stanford University

  36 shared

• Marios Georgiadis

  36 shared

Labs

• CamlabPI

  Precision human measurement for multiple clinical and physiological areas including the brain, heart, lungs, and reproductive system.

Awards & honors

• Hellman Fellowship
• Office of Naval Research Young Investigator Program award