Educational Background

Current Courses

BME 4370 Biomedical Control Systems

BME 3240: Computational Methods for Biological Systems

BME 3222 Bio Signals and Systems

BME 4252 Biomedical Measurements and Instrumentation

BME 4253 Biomedical Imaging and Instrumentation Laboratory

Previous courses..

BME 5720 Biomedical Instrumentation

BME 5702 Biomedical Applications in Physiology 

BME 4050 Cardiovascular Engineering

BME 5790 Numerical Modeling in Biomedical Engineering

Selected Publications

Gamage, P. T., Dong, P., Lee, J., Gharaibeh, Y., Zimin, V. N., Bezerra, H. G., ... & Gu, L. (2022). Fractional Flow Reserve (FFR) Estimation from OCT-Based CFD Simulations: Role of Side Branches. Applied Sciences, 12(11), 5573.

Shokrollahi, Y., Dong, P., Gamage, P. T., Patrawalla, N., Kishore, V., Mozafari, H., & Gu, L. (2022). Finite Element-Based Machine Learning Model for Predicting the Mechanical Properties of Composite Hydrogels. Applied Sciences, 12(21), 10835.

Lin, S., Premaraj, T. S., Gamage, P. T., Dong, P., Premaraj, S., & Gu, L. (2022). Upper Airway Flow Dynamics in Obstructive Sleep Apnea Patients with Various Apnea-Hypopnea Index. Life, 12(7), 1080.

Azad M.K., D’Angelo J., Gamage P.T., Ismail S., Sandler R.H., Mansy H.A. (2021) Spatial Distribution ofSeismocardiographic Signals. In: Obeid I., Selesnick I., Picone J. (eds) Biomedical Signal Processing. Springer, Cham.

Gamage, P. T., Dong, P., Lee, J., Gharaibeh, Y., Zimin, V. N., Dallan, L. A., ... & Gu, L. (2021). Hemodynamic alternations following stent deployment and post-dilation in a heavily calcified coronary artery: In silico and exvivo approaches. Computers in Biology and Medicine, 139, 104962.

Khalili, F., Gamage, P. T., Taebi, A., Johnson, M. E., Roberts, R. B., & Mitchell, J. (2021). Spectral Decomposition of the Flow and Characterization of the Sound Signals through Stenoses with Different Levels of Severity. Bioengineering, 8(3), 41.

Khalili, F., Gamage, P. T., Taebi, A., Johnson, M. E., Roberts, R. B., & Mitchel, J. (2021). Spectral Decomposition and Sound Source Localization of Highly Disturbed Flow through a Severe Arterial Stenosis. Bioengineering, 8(3), 34.

Gamage P.T., Azad M.K., Taebi A., Sandler R.H., Mansy H.A. (2020) Clustering of SCG Events Using Unsupervised Machine Learning. In: Obeid I., Selesnick I., Picone J. (eds) Signal Processing in Medicine and Biology. Springer, Cham.

Sandler, R. H., Gamage, P., Azad, M. K., Dhar, R., Spiewak, A., Raval, N. Y., ... & Mansy, H. (2020). Computational and Mechanical Modeling of SCG Signals. Journal of Cardiac Failure, 26(10), S88.

 Sandler, R., Gamage, P., Azad, M. K., Dhar, R., Raval, N., Mentz, R., & Mansy, H. (2020). Potential SCG Predictors of Heart Failure Readmission. Journal of Cardiac Failure, 26(10), S87.

 Sandler, R. H., Azad, M. K., D'Angelo, J., Gamage, P., Raval, N. Y., Mentz, R. J., & Mansy, H. A. (2020). Documenting Spatial Variation of SCG Signals for Optimal Sensor Placement. Journal of Cardiac Failure, 26(10), S92.

Sandler, R. H., Azad, K., Rahman, B., Taebi, A., Gamage, P., Raval, N., ... & Mansy, H. A. (2019). Minimizing Seismocardiography Variability by Accounting for Respiratory Effects. Journal of Cardiac Failure, 25(8), S185.

 Khalili, F., Gamage, P., Sandler, R., & Mansy, H. (2018). Adverse hemodynamic conditions associated with mechanical heart valve leaflet immobility. Bioengineering, 5(3), 74.

 Azad, M. K., Gamage, P. T., & Sandler, R. H. (2018). Detection of respiratory phase and rate from chest surface measurements. J Appl Biotechnol Bioeng, 5(6), 359-362.

 Gamage, P. P.T., Khalili, F., Khurshidul Azad, M. D., and Mansy, H. A. (March 19, 2018). "Modeling Inspiratory Flow in a Porcine Lung Airway." ASME. J Biomech Eng. June 2018; 140(6): 061003

 Gamage, P., Khalili, F., & Mansy, H. A. (2018). Aero-acoustics in constricted pipe flow at low Mach number. J Appl Biotechnol Bioeng, 5(5), 306-309.

Azad, M. K., Mansy, H. A., & Gamage, P. T. (2016). Geometric features of pig airways using computed tomography. Physiological reports, 4(20), e12995.

Research

Dr. Gamage's research focus is on the advancement of non-invasive, cost-effective diagnostic and monitoring strategies for diseases. By utilizing a combination of computational modeling, instrumentation, signal processing, and AI techniques, Dr. Gamage aims to gain a deeper understanding of physiological and pathological conditions and enhance healthcare outcomes.