S5E3

Abstract

The past decade has witnessed rapid advancements of non-invasive functional neuroimaging techniques, which have enabled new insights into our brain’s function and physiology. How can we best acquire and analyze the data to optimize these cutting-edge techniques? And how can we integrate multi-faceted information gathered from different modalities to achieve a holistic view on our brain’s function and physiology in health and disease? This talk will discuss several projects centered around these themes. In the first part of the talk, I will share my explorations into the opportunities and pitfalls of extracting maximal information from functional magnetic resonance imaging (fMRI) data collected at high spatiotemporal resolutions. In the second part of the talk, I will present my past and ongoing studies that integrate fMRI with a novel dynamic Positron Emission Tomography (PET) approach to elucidate the vascular and metabolic correlates of intrinsic brain activity across wake and sleep.

Introduction of speaker

I am an Instructor and incoming Assistant Professor at the Martinos Center for Biomedical Imaging at Massachusetts General Hospital (MGH) and Harvard Medical School. I received my PhD from Stanford University, with a major in Electrical Engineering and a minor in Statistics. My lab advances computational approaches and neuroimaging techniques to probe various neuronal, vascular, energetic and neuromodulatory mechanisms underlying brain functional dynamics.

Abstract

Understanding the earthquake machinery with the potential of predictability, have been the objective of multiple fields, experimental, and theoretical studies. Numerical models capable of capturing the wide range of observations during earthquake cycles is important in providing detailed physical bases for understanding mechanics governing earthquake nucleation, propagation, and reoccurrences. However, due to computational cost and complexity models are often limited to single dynamic ruptures, or simplification of some stages of the fault behavior. In this talk, I will introduce a computational framework capable of modeling earthquake cycles efficiently and accurately while incorporating off fault physical models with non-linearities, including but not limited to material, geometrical and rheological complexities. I will show through this numerical approach that incorporating high resolution fault zone physics can alter substantially the evolution of earthquakes. The proposed numerical framework has provided insights on some of the seismological observations, and the associated hazards of earthquakes. I will describe recent efforts in incorporating non-elastic rheology in physics-based predictive models of earthquakes, and how the co-evolution of inelastic strain and fault slip can alter the nature of the observations. I will also briefly talk about our efforts to utilize physics-based models to study the hazard associated with tsunamigenses during earthquakes. To conclude, I will discuss the importance of computational tools capable of capturing the full extent of the physical behavior governing the earthquake cycle and providing predictive potential to reduce the impact of these events and for enabling better preparedness plans.

Introduction of speaker

I started my PhD at University of Illinois at Urbana Champaign in 2018. During my PhD I worked on developing physics-based numerical models for large scale problems such as earthquakes and tsunamis to better understand the driving mechanisms for such natural hazards. I have developed and expanded on a computational framework (FEBE) that can model sequences of earthquakes and aseismic slip with efficiency, while incorporating nonlinear source physics. In addition, I have contributed to the development of a physics-based model for earthquake-induced tsunamis to answer questions pertaining to the hazardous nature of tsunamis generated by strike-slip faulting. I obtained my master’s degree from UIUC in 2017, and bachelor’s degree from British University in Egypt in 2013. I will be joining Caltech as a postdoctoral researcher in December 2022.