Prof. Zhao's research focuses on the development and application of mass spectrometry-based proteomics, combined with chemical biology and other biological approaches, to uncover and study previously undescribed cellular pathways. His current work emphasizes protein post-translational modifications (PTMs) and their roles in epigenetic regulation. Over the past 18 years, his laboratory has discover...

讲座摘要 This talk will present a novel non-linear model reduction method: Probabilistic Manifold Decomposition (PMD), which provides a powerful framework for constructing non-intrusive reduced-order models (ROMs) by embedding a high-dimensional system into a low-dimensional probabilistic manifold and predicting the dynamics. Through explicit mappings, PMD captures both linearity and non-linearity...

Rare event evaluation is ubiquitious in modern system design. With growing complexity at the nano age, aleatory and epistemic uncertainty render system stochastic and its rare event evaluation, such as failure probability, increasingly prohibitive. To address such challenge, academia and industry have developed on various sampling technique and surrogate models. In this talk, we will present three...

Natural products have served as an invaluable source of both drugs and chemical tools to explore a variety of biological processes for chemical biologists. Rapamycin, FK506 and cyclosporin A (CsA) are macrocycles that have played important roles in unraveling cellular pathways and treatments of organ transplants, cancer and other diseases. These macrocycles have a unique and extraordinary mode of ...

We developed a machine learning model to predict left ventricular ejection fraction (LVEF/EF) from parasternal long-axis (PLAX) echocardiographic videos. Because public datasets with labeled PLAX videos are virtually non-existent, our work focuses on an innovative data generation strategy to overcome this scarcity. By leveraging a time-based correlation between clinical notes and echocardiographic...

讲座简介：How do non-elite founding teams attract capital? Building on signaling theory, we propose that disclosing advisory relationships, or formal ties to prominent entrepreneurs, experts, or public figures, can serve as input-based signals of capability and credibility. We predict that disclosed advisor affiliations may substitute for missing input-based signals but are less likely to replace ...