# Seminar Archive - 2017

Our regular seminar program covers a broad range of topics from applied mathematics, pure mathematics and statistics. All staff and students are welcome.
A complete list of past seminars can be accessed via the left-hand menu.

*Andrew Hone - University of Kent (UK) and UNSW*

There are relatively few transcendental numbers for which the continued fraction expansion is explicitly known. Here we present two new families of continued fractions for Engel series - sums of...

*Michela Castagnone - University of New South Wales*

The ability to generate uniformly random graphs is useful in many real world applications. For example, we may model a given social network as a graph, and determine its key properties. In order...

*Miriam Greenbaum - UNSW Mathematics and Statistics*

Banks currently use a scoring model to assess whether or not to accept a loan. This model assigns points for lack of derogatory information and deducts points for factors such as bankruptcies, late...

*Aidan Wong - UNSW Mathematics and Statistics*

The principal-agent problem is a well-known problem in economics, in which one party (the “agent”) acts on behalf of another party (the “principal”). In many cases, the agent has incentive to act...

*Peter Wu - UNSW Mathematics and Statistics*

In the era of big data, large scale structured non-convex and non-smooth optimization problem can be found in various contemporary applications such as engineering, machine learning and signal...

*Daniel Picone - UNSW Mathematics and Statistics*

4D Cone Beam Computed Tomography is an important medical imaging technique, with particular applications in lung cancer radiotherapy. Determining when and where the camera takes images is of high...

*Geordie Williamson - University of Sydney*

This will be a talk about the representation theory of finite groups. Over the last forty years there have been fascinating developments in the theory of modular (i.e. characteristic p)...

*Kenny Lau - UNSW Mathematics and Statistics*

While a priori error estimates tell us about the convergence rate of the numerical method, they do not give a quantitative estimate on the size of the error, which a posteriori error estimates...

*Aaron Kaw - UNSW Mathematics and Statistics*

The identification of a dominant mode in the delivery of proteins to a cell's membrane can strongly suggest the processes taking place throughout the cell, with particular regard to energy and...

*Professor Junbin Gao - University of Sydney*

The geometry of a given space characterizes the proximity between data and plays a key role in machine learning. The traditional methods of simply and naively treating data spaces as "flat" Euclidean...