Postdocs and Visitors

Meet our exceptional postdocs and visitors:

Michael Jauch

Michael Jauch
Postdoctoral Associate

Frank H T Rhodes Hall, Room 657 
maj225@cornell.edu

My research focuses on statistical methodology for multivariate data. I’m interested in time series, functional data, covariance modeling, dimension reduction, etc. My dissertation work addressed challenges arising in Bayesian analyses of statistical models with orthogonal matrix parameters, including computation and prior specification, and other topics related to random orthogonal matrices.

Research website

Nate Veldt

Nate Veldt
Postdoctoral Associate

Frank H T Rhodes Hall, Room 657 
lnv22@cornell.edu

My research is on models, algorithms, and complexity results for problems arising in network science and data mining. A recent focus of my research has been the design and implementation of algorithms for graph clustering and hypergraph clustering. More broadly, I'm interested in mathematical foundations of data science. Projects I work on tend to combine aspects of graph theory, mathematical optimization, numerical linear algebra, machine learning, and theoretical computer science.

Research website

Jonas Lybker Juul

Jonas Lybker Juul
Postdoctoral Associate

Frank H T Rhodes Hall, Room 657 
jsj85@cornell.edu

I am interested in networks and how things spread in networked systems. My work addresses applied and theoretical questions in data science. In my most recent work I tried to understand how content spreads online. Do the different kinds of content spread differently online? Does false information reach a larger audience than true information? I approach such questions by developing appropriate statistical tools and drawing on methods from probability theory, dynamical systems and network science.

Research website
 

Yuanzhao Zhang

Yuanzhao Zhang 
Postdoctoral Associate

Frank H T Rhodes Hall, Room 657 
yz2783@cornell.edu

My interest lies at the interface of networks and nonlinear dynamics. When microscopic entities interact, they can often coordinate with each other and achieve a macroscopic impact. Think of birds flocking together to confuse predators, cardiac pacemakers beating synchronously to create rhythmic impulses, and the decisions of millions of investors confluence to drive the financial market. My research aims to understand the underlying mechanisms behind such collective behaviors. From quantum networks to circadian clocks, we have much to learn when it comes to the relations between a network’s structure, dynamics, and function. I draw techniques from dynamical systems, graph theory, and statistical mechanics to help uncover the simplicity hidden in those complex interconnected systems.

Research website