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My research interests include building a solid mathematical foundation for difference approximations to partial differential equations and using mathematical models to better understand and predict the spread of epidemics. Most of my publications are in mathematical modeling and I have passion for writing quality software for numerical differentiation, interface tracking, adaptive grid generation, and the iterative solutions of nonlinear systems.
Dr. Xue's research focuses on creating and analyzing mathematical modeles for the spread of infectious diseases. Her research ranges from mosquito-borne diseases, such as dengue fever, Zika, and chikungunya, to the modeling the spread of the Ebola Virus disease.
My current research interests include data assimilation algorithms, numerical methods for time-dependent PDEs, hyperbolic conservation laws and numerical analysis. My current project is on data assimilation by combining the underlying time-dependent PDE model and interpolation from scattered spatial observations to improve future predictions.
My current research under the supervision of both Dr. Hyman and Qu places emphasis on the use of mathematics and graph/network theory to understand stochastic processes such as the spread of epidemics. Specifically, we determine at what point an epidemic model such as an SI, SIR, and SIS becomes predictable. In other words, at what point does a deterministic model dictate the behavior of the epidemic? Other areas of research interest include using uncertainty quantification and parameter estimation for network modeling and fitting data.
I am a third year Phd student, working with Dr. James (Mac) Hyman, in the Department of Mathematics of Tulane University in New Orleans, LA. My current research interests are machine learning, deep learning, optimization and Stochastic Process.
My current research projects involve in the type 2 diabetes related physiology experiments and computational modeling. Specifically, I am doing these procedures on rats pancreas to seek an explanation to why by-pass surgery can cure type 2 diabetes patients in clinic. Meanwhile, I’m using a computational model to predict the binding effects between calcium channel and re-design blockers.
I am currently a Master's student at Tulane in the Computational Sciences Program. My research experience is in epidemic and ecological modeling. The projects I have worked on include modeling the spread of such diseases as chikungunya and Zika in the Caribbean, and studying the effects of an invasive species on the saguaro cacti in the Sonoran Desert. My current area of focus is in uncertainty quantification and parameter identification in mathematical modeling.
I am a Ph.D. candidate in Math Department of Tulane University. My current research interests are high dimensional data analysis, especially integrative analysis of neuroimaging or genomic data.
I am an undergraduate student at Tulane University pursuing a Bachelor of Science degree in Mathematics and Chemistry. My research interests include exploring the results that different network structures have in regards to SIR, SIS, and SI epidemic models. Specifically, the stochastic and deterministic stages that these epidemics can be broken down into to better understand their time-dependent spread through a population.
I am an undergraduate student at Tulane University majoring in Mathematics and Public Health with a minor in Arabic. My research interests include using mathematical models to study the transmission of zoonotic infectious diseases and disease emergence. My current research is on modeling the transmission of the infectious agent for Chagas Disease in the New Orleans area and estimating human risk. I am also an alumnus of Arizona State University’s Mathematical and Theoretical Biology Institute (MTBI) where I studied reducing human Lyme Disease cases by vaccinating mice near housing developments.