Continuous Vital Signs Monitoring with Loose T-Shirt
2025
Loose-fitting continuous ECG sensing T-shift using capacitive sensing
Publications
Journal Articles
Interpreting Earth’s Inner Core Structure via Ultrasonic Scattering Experiments
2025
An experimental study of the scattering of ultrasonic compressional waves in an hcp Zn-Sn alloy, serving as an analog to the Fe alloy in Earth’s inner core to better understand the origin of inner core seismic attenuation.
Recommended citation: Ming Gong, Michael I. Bergman, An experimental ultrasonic method to determine a scattering quality factor, with application to earth's inner core, Physics of the Earth and Planetary Interiors, 2025, 107456, ISSN 0031-9201, https://doi.org/10.1016/j.pepi.2025.107456.
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An Improved Machine Learning Model for Pure Component Property Estimation
2024
A new Gaussian Process-based modeling framework that predicts the physico-chemical properties of chemical species.
Recommended citation: Cao, X., Gong, M., Tula, A., Chen, X., Gani, R., & Venkatasubramanian, V. (2024). An improved machine learning model for pure component property estimation. Engineering, 39, 61–73. https://doi.org/10.1016/j.eng.2023.08.024
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Conference Posters
Deep Learning Loss Function and Data Optimization for A.I. Detection of Thin Film Grain Boundaries
2025
Identify optimal combination of loss function and data to create a model that can generates an automated tracing most consistent with the ground truth
An Experimental Ultrasonic Method to Determine A Scattering Quality Factor, with Application to Earth’s Inner Core
2024
SEDI Poster 2025
Recommended citation: Ming Gong, Michael I. Bergman, An experimental ultrasonic method to determine a scattering quality factor, with application to earth's inner core, Physics of the Earth and Planetary Interiors, 2025, 107456, ISSN 0031-9201, https://doi.org/10.1016/j.pepi.2025.107456.
Download Slides
Research Reports
Loss Function Evaluation
2025
Accurate tracing of grain boundaries in microscopy images is vital in material science, yet current models need more data and a more accurate loss function. In this report, we present a twofold contribution to improving grain-tracing U-nets.