Browsing CSE PhD Theses by Title
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3D organ property mapping using freehand ultrasound scans
(Massachusetts Institute of Technology, 2020)3D organ property mapping has gained a considerable amount of interest in the recent years because of its diagnostic and clinical significance. Existing methods for 3D property mapping include computed tomography (CT), ... 
A new way to do epidemic modeling
(Massachusetts Institute of Technology, 202209)The Coronavirus respiratory disease 2019 originating from the virus SARSCOV2 led to a global pandemic, leading to more than 500 million confirmed global cases and approximately 6 million deaths in more than 50 countries. ... 
An adaptive spacetime discontinuous Galerkin method for reservoir flows
(Massachusetts Institute of Technology, 2018)Numerical simulation has become a vital tool for predicting engineering quantities of interest in reservoir flows. However, the general lack of autonomy and reliability prevents most numerical methods from being used to ... 
An efficient algorithm for sensitivity analysis of chaotic systems
(Massachusetts Institute of Technology, 202109)How does longterm chaotic behavior respond to small parameter perturbations? Using detailed models, chaotic systems are frequently simulated across disciplines – from climate science to astrophysics. But, an efficient ... 
Analyzing cities' complex socioeconomic networks using computational science and machine learning
(Massachusetts Institute of Technology, 2018)By 2050, it is expected that 66% of the world population will be living in cities. The urban growth explosion in recent decades has raised many questions concerning the evolutionary advantages of urbanism, with several ... 
Applications of Deep Learning to Scientific Inverse Problems
(Massachusetts Institute of Technology, 202109)The first part of this thesis introduces an endtoend deep learning architecture, called the wideband butterfly network (WideBNet), which comprehensively solves the inverse wave scattering problem across all length scales. ... 
Atomistic engineering of fluid Structure at the fluidsolid interface
(Massachusetts Institute of Technology, 2019)Under extreme confinement, fluids exhibit a number of remarkable effects that cannot be predicted using macroscopic fluid mechanics. These phenomena are especially pronounced when the confining length scale is comparable ... 
Bayesian learning for highdimensional nonlinear dynamical systems : methodologies, numerics and applications to fluid flows
(Massachusetts Institute of Technology, 2020)The rapidlygrowing computational power and the increasing capability of uncertainty quantification, statistical inference, and machine learning have opened up new opportunities for utilizing data to assist, identify and ... 
CFD simulation of long slender offshore structures at high Reynolds number
(Massachusetts Institute of Technology, 2019)Slender cylindrical structures are common in many offshore engineering applications such as floating wind turbines and subsea risers. These structures are vulnerable to flowinduced vibrations under certain environmental ... 
Combining numerical simulation and machine learning  modeling coupled solid and fluid mechanics using mesh free methods
(Massachusetts Institute of Technology, 2020)The prediction and understanding of physical systems is largely divided into two camps, those based on data, and those based on the numerical models. These two approaches have long been developed independently of each ... 
A containerbased lightweight fault tolerance framework for high performance computing workloads
(Massachusetts Institute of Technology, 2019)According to the latest world's top 500 supercomputers list, ~90% of the top High Performance Computing (HPC) systems are based on commodity hardware clusters, which are typically designed for performance rather than ... 
Continuous lowrank tensor decompositions, with applications to stochastic optimal control and data assimilation
(Massachusetts Institute of Technology, 2017)Optimal decision making under uncertainty is critical for control and optimization of complex systems. However, many techniques for solving problems such as stochastic optimal control and data assimilation encounter the ... 
Covariance estimation on matrix manifolds
(Massachusetts Institute of Technology, 2020)The estimation of covariance matrices is a fundamental problem in multivariate analysis and uncertainty quantification. Covariance matrices are an essential modeling tool in climatology, econometrics, model reduction, ... 
Design and optimization of shared mobility on demand : dynamic routing and dynamic pricing
(Massachusetts Institute of Technology, 2021)Mobility of people and goods has been critical to urban life ever since cities emerged thousands of years ago. With the ushering in CyberPhysical Systems enabled by the development of smart mobile devices, telecommunication ... 
Development and assessment of a physicsbased model for subcooled flow boiling with application to CFD
(Massachusetts Institute of Technology, 2020)Boiling is an extremely efficient mode of heat transfer and is the preferred heat removal mechanism in power systems in general and, more recently, in electronics cooling. Physicsbased models that describe boiling heat ... 
Development of macroscopic nanoporous graphene membranes for gas separation
(Massachusetts Institute of Technology, 2017)Separating components of a gas from a mixture is a critical step in several important industrial processes including natural gas purification, hydrogen production, carbon dioxide sequestration, and oxycombustion. For such ... 
Development of the random ray method of neutral particle transport for highfidelity nuclear reactor simulation
(Massachusetts Institute of Technology, 2018)A central goal in computational nuclear engineering is the highfidelity simulation of a full nuclear reactor core by way of a general simulation method. General full core simulations can potentially reduce design and ... 
A deviational Monte Carlo formulation of ab initio phonon transport and its application to the study of kinetic effects in graphene ribbons
(Massachusetts Institute of Technology, 2014)We present a deviational Monte Carlo method for solving the Boltzmann equation for phonon transport subject to the linearized ab initio 3phonon scattering operator. Phonon dispersion relations and transition rates are ... 
Direct and adaptive quantification schemes for extreme event statistics in complex dynamical systems
(Massachusetts Institute of Technology, 2017)Quantifying extreme events is a central issue for many technological processes and natural phenomena. As extreme events, we consider transient responses that push the system away from its statistical steady state and that ... 
Efficient multiscale methods for micro/nanoscale solid state heat transfer
(Massachusetts Institute of Technology, 2015)In this thesis, we develop methods for solving the linearized Boltzmann transport equation (BTE) in the relaxationtime approximation for describing smallscale solidstate heat transfer. We first discuss a Monte Carlo (MC) ...