Jonathan Zia, MD, PhD

EDUCATION

Undergraduate: Arizona State University (2016)

MD: Emory University (2022)

PhD: Georgia Institute of Technology (2020)

Internship: Stanford University (2023)

CLINICAL AND RESEARCH INTERESTS

• Artificial Intelligence
• Computer Science
• Medical Devices

PUBLICATIONS

First Author Journal Publications:

J. Zia, J. Kimball, C. Rolfes, J.-O. Hahn, O. T. Inan. Enabling the assessment of trauma-induced hemorrhage via smart wearable systems. Science Advances 6, eabb1708 (2020).

J. Zia, J. Kimball, C. J. Rozell and O. T. Inan. Harnessing the manifold structure of cardiomechanical signals for physiological monitoring during hemorrhage. IEEE Transactions on Biomedical Engineering, vol. 68, no. 6, pp. 1759-1767, June 2021.

J. Zia, J. Kimball, S. Hersek and O. T. Inan. Modeling consistent dynamics of cardiogenic vibrations in low-dimensional subspace. IEEE Journal of Biomedical and Health Informatics, vol. 24, no. 7, pp. 1887-1898, July 2020.

J. Zia, J. Kimball, S. Hersek, M. M. H. Shandhi, B. Semiz and O. T. Inan. A unified framework for quality indexing and classification of seismocardiogram signals. IEEE Journal of Biomedical and Health Informatics, vol. 24, no. 4, pp. 1080-1092, April 2020.

Contributing Author Journal Publications:

M. Nikbakht, A. Gazi, J. Zia, S. An, D. Lin, O. T. Inan, R. Kamaleswaran. Synthetic seismocardiogram generation using a transformer-based neural network. Journal of the American Medical Informatics Association 30, no. 7 (2023): 1266-1273.

Y. R. Chalumuri, J. Kimball, A. Mousavi, J. Zia, C. Rolfes, J. D. Parreira, O. T. Inan, J.-O. Hahn. Classification of blood volume decompensation state via machine learning analysis of multi-modal wearable-compatible physiological signals. Sensors 22, no. 4 (2022): 1336.

D. Lin, J. Kimball, J. Zia, O. T. Inan. Reducing the impact of external vibrations on fiducial point detection in seismocardiogram signals. IEEE Transactions on Biomedical Engineering 69, no. 1 (2021): 176-185.

J. Kimball, J. Zia, et al. Unifying the estimation of blood volume decompensation status in a porcine model of relative and absolute hypovolemia via wearable sensing. IEEE Journal of Biomedical and Health Informatics 25, no. 9 (2021): 3351-3360.

L. Rosa, J. Zia, O. T. Inan, G. Sawicki. Machine learning to extract muscle fascicle length changes from dynamic ultrasound images in real-time. PLOS One, vol 15, no. 5, e0246611 (2021).

D. Whittingslow, J. Zia, et al. Knee acoustic emissions as a digital biomarker of disease status in juvenile idiopathic arthritis. Frontiers in Digital Health, vol. 2, November 2020.

Conference Proceedings, Posters, Abstracts:

J. Zia, J. Kimball, C. Rolfes, J.-O. Hahn, O. T. Inan. Enabling the assessment of trauma-induced hemorrhage via smart wearable systems. Emory Medical Student Research Day, 2022. – Best Poster Award Winner.

Y. R. Chalumuri, J. Kimball, A. Mousavi, J. Zia, C. Rolfes, J. D. Parreira, O. T. Inan, J.-O. Hahn.  “Classification of blood volume state via wearable physiological sensing and machine learning,” IEEE International Conference on Biomedical and Health Informatics (BHI’ 21)

J. Zia, J. Kimball and O. T. Inan, "Localizing placement of cardiomechanical sensors during dynamic periods via template matching," 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020, pp. 473-476.

J. Zia, J. Kimball, J. -O. Hahn and O. T. Inan, "Mitigating hypovolemia-induced miscalibration of photoplethysmogram-derived blood pressure," 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020, pp. 5288-5291.

J. Kimball, J. Zia, C. Rolfes, J.-O. Hahn, O. T. Inan. “Preliminary evaluation of a noninvasive approach for monitoring severe hemorrhagic shock based on wearable technology in a porcine model,” Shock, vol. 53, pp. 71.

J. Zia, J. Kimball, M. H. Shandhi and O. T. Inan, "Automated identification of persistent time-domain features in seismocardiogram signals," 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 2019, pp. 1-4.

J. Zia., A. Tadayon, T. McDaniel, S. Panchanathan. Utilizing neural networks to predict freezing of gait in Parkinson's patients. Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility - ASSETS '16, pp. 333-334, October 2016.

J. Kimball, J. Zia, S. An, C. Rolfes, J.-O. Hahn, M. Sawka, O. T. Inan, “Preclinical Evaluation of Wearable Sensors and Machine Learning for Continuous Estimation of Hypovolemic Status,” IEEE International Conference on Biomedical and Health Informatics (BHI’ 21) Special Session: Opportunities for Machine Learning and Noninvasive Sensing to Impact Emergency Cardiovascular Care. Virtual, July 28, 2021.

O. T. Inan, J. Kimball, D. Lin, J. Zia. “Wearable Technologies for Pre-Hospital Trauma Care,” 2021 

IEEE 17th International Conference on Wearable and Implantable Body Sensor Networks (BSN) Special Session: Wearable Sensing for Detecting and Monitoring Shock. Virtual, July 30, 2021.

Peer-Reviewed Book Chapters:

R. Tadayon, T. McDaniel, M. Goldberg, P. M. Robles-Franco, J. Zia, M. Laff, M. Geng, S. Panchanathan, "Interactive Motor Learning with the Autonomous Training Assistant: A Case

Study," HCI International 2015, Los Angeles, CA.A. Tadayon, J. Zia, T. McDaniel, N. Krishnamurthi, M. Goldberg, L. Anantuni, S. Panchanathan, "A Shoe Mounted System for Parkinsonian Gait Detection and Real-Time Feedback," HCI International 2015, Los Angeles, CA.

HONORS AND AWARDS

National Institutes of Health Training Grant (T32), Emory University

Flinn Scholar, Arizona State University