CIS & MINDS Seminar - Minglang Yin, PhD

<p>Recorded Seminar:</p><p><a href="https://wse.zoom.us/rec/share/bkt7Zta2B8lGXzBG8fJU4mfv7NskKWokXy-aD3cxvC... Zoom Meeting:</p><p><a href="https://wse.zoom.us/j/93822965644?pwd=dDNHYVZGY096QU9Dem45STBsQWQ2dz09">...“Scientific Machine Learning forVascular Biomechanics and </b><b>Cardiac Electrophysiology”</b></p><p><b></b></p><p><b>Minglang Yin</b><b>, PhD</b></p><p>Postdoc Fellow</p><p></p><p>Johns Hopkins University</p><p><b>Abstract:</b><span> </span><span> </span><span>Cardiovascular diseases continue to be the leading cause ofdeath in the US and worldwide. Current development of machine learning isreshaping the landscapes in both cardiovascular research and in cardiology. Inthis talk, I am going to discuss novel machine learning models in vascularbiomechanics and translational cardiac electrophysiology. Topics willinclude deep learning for 1) inferring biomaterial properties, 2) predictingbiomaterial failure, 3) personalized planning for catheter ablationprocedures, and 4) patient stratification for risk of sudden cardiacdeath based on multimodality data.</span><br></p><p><b>Biography:</b><span> </span><span> </span><span>MinglangYin is a postdoc fellow in the department of biomedical engineering at JohnsHopkins University, with an appointment in the Alliance for CardiovascularDiagnostic and Treatment Innovation (ADVANCE). He completed his Ph.D. at BrownUniversity in Biomedical Engineering (2022). His research interests spanscientific machine learning, cardiovascular mechanics, computational mechanics,multi-scale modeling, and uncertainty quantification. His works involvedeveloping novel machine learning and computational models for the prognosisand diagnosis of cardiovascular diseases.</span><br></p><p></p><p> </p>