Academic Qualifications
- M.S., Diplôme d'Ingénieur, Information Technology and Biomedical Engineering, Telecom Physique Strasbourg(Strasbourg, France), 2015
- M.S., Imaging Robotics and Bioengineering - Imaging track, Université de Strasbourg (Strasbourg, France), 2015
Biography
Lea Melki, originally from Lebanon, was born in Luxembourg. After doing her preparatory classes in Paris, she began studying Information Technology and Biomedical Engineering in Strasbourg in 2012. She also enrolled in a dual Master's Degree at the Université de Strasbourg in 2013 to strengthen her knowledge in Medical Imaging. She was awarded both Master's degrees in 2015.
As of Fall 2015, she is a Biomedical Engineering student in the Ph.D. program at Columbia University. As part of her final Master's Research project, she worked on Blood Flow Imaging, and Tissue Doppler Imaging sequences for cardiac deformation assessment. Lea's main research interests include cardiac ultrasound imaging techniques to non-invasively assess the electrical and mechanical activity of the heart and Electromechanical Wave Imaging to characterize arrhythmia and improve treatment planning.
Awards and Prizes
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Featured in the Women in EP Networking Luncheon: Supporting and Promoting Women Investigators, 40th Heart Rhythm Society Annual Scientific Sessions, May 2019, San Francisco, CA, among the eight nominees for best abstract by a woman first-author.
Title: Characterizing macroreentrant atrial flutter with Electromechanical Wave Imaging.
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Student Paper Competition Finalist and Student Travel Award, IEEE International Ultrasonics Symposium, September 2017, Washington, DC.
Title: 3D rendering of Electromechanical Wave Imaging for the characterization and optimization of biventricular pacing conditions in heart failure patients undergoing cardiac resynchronization therapy.
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Student awards session - 3rd place, 15th International Tissue Elasticity Conference, October 2016, Lake Morey, VT.
Title: Reproducibility and angle independence of Electromechanical Wave Imaging for the measurement of electromechanical activation during sinus rhythm in healthy humans.