University of Calgary

A video of this event is available on mathtube.org. Many problems in science and engineering require the reconstruction of an object - an image or signal, for example - from a collection of measurements. Due to time, cost or other constraints, one is...

Sustained oscillations occur in complex networks in contexts as diverse as physiology, gene regulatory networks and neural networks. Despite intensive research effort, important questions remain about the sources of oscillations in large networks...

Many studies have shown that the most important factor in investment success is asset allocation, as opposed to stock picking. At its most basic level, this amounts to the choice of how much to allocate to bonds and stocks.In this talk, I will...

The classical theorem of Edouard Helly (1913) is a masterpiece of geometry. In the simplest form it states that if a family $\Gamma$ of convex sets in $R^n$ has the property that every $n+1$ of the sets have a non-empty intersection, then all the...

Dennis Gabor was a Hungarian/British physicist who invented holography, for which he received the 1971 Nobel Prize. However, in the world of seismic data analysis, he is best known for the Gabor transform, a special case of the short-time Fourier...

Mathematical models of wind turbine blade aerodynamics have provided valuable limits on the performance for actual wind turbines. The simplest and best known is the Betz limit on power production. It is less well-known that this limit applies only at...

It is typically used to study evolutionary scenarios in low-dimensional phenotype spaces, such as the important phenomenon of evolutionary branching (adaptive diversification). I will briefly recall the basic theory of evolutionary branching and...

Over $Q$ there do not exist any non-zero abelian varieties with good reduction everywhere. However, over all but six real quadratic fields they actually do exist. In this talk we determine, for certain small real quadratic fields $F$, the set of...

Machine learning is a powerful computer science technique that can derive knowledge from big data and make predictions/decisions. Since nanometer VLSI design and manufacturing have extremely high complexity and gigantic data, there is great...