**Plenaries**

## From ozone measurements to pensions

**Barbara D'Ambrogi-Ola**, Ilmarinen Mutual Pension Insurance Company

Once upon a time a young mathematician was enchanted by aurora borealis….

This
was the start of a journey going through Gibbs samplers, ozone
measurements, teaching, fractional Brownian motions, utility functions
and Black-Scholes equation. The current chapter of the story is taking
place in a pension insurance company. So, what does a mathematician do
in an insurance company? And does an insurance company need somebody
with a PhD in math? Finally a small survival kit for working in industry
will be provided.

## Number theory meets digital television

**Camilla Hollanti**, Aalto University

In this talk I will
explain how digital TV broadcasting can benefit from algebraic number
theory via using so-called space-time codes. We will see how to
translate purely practical questions into equivalent purely number
theoretic questions

## Luzin's condition (N)

**Pekka Koskela**, University of Jyväskylä

For a model of elastic deformations to be realistic, one must among other things rule out creation of matter.

In mathematical terms, this means that the mapping representing the change of positions of particles should not

map
any set of volume zero onto a set of positive volume. This is called
Luzin's condition (N) after Nikolai Luzin, who is more famous for his
theorem on quasicontinuity of measurable functions.

I will review recent research on Luzin's condition (N).

## Games, analytics, business, academia – how do they mix together?

**Ville Suur-Uski**, Supercell

What’s the value of a scientific education at Supercell, a mobile games company?

The
work a researcher does in academia shares some common features to being
a data scientist analysing Clash of Clans. The speech will have
examples of skills needed in both trades, examples where mathematics is
just a must and what do statistics mean for a game designer.

## Mathematics in Patient Monitoring

**Kimmo Uutela**, GE Healthcare

GE Healthcare is a
multinational medical device manufacturer. GE Healthcare Finland is
developing patient monitors for hospitals. The patient monitor measures
signals from the patient and calculates indicators that help the
caregivers in their work. The monitor uses signal processing, estimation
methods and statistical methods to provide useful and reliable
information for clinical decision making. The presentation includes
examples of development tasks where mathematical methods have been used.

## Reasons behind cost overruns – systematic bias, selection bias, or both?

**Eeva Vilkkumaa**, Aalto University

Projects that are
selected for implementation based on uncertain cost estimates often end
up costing considerably more than estimated. For instance, cost overruns
have occurred
in 90% of large transportation infrastructure projects worldwide with
an average overrun of 28%. Cost overruns are typically attributed to a
systematic downward bias in the projects’ cost estimates. However, even
if the cost estimates among project proposals
are unbiased but only those projects with the lowest estimates are
implemented, cost overruns are to be expected due to selection bias. We
develop a model for systematic bias and selection bias in project
selection, and show how the relative magnitudes of
these biases can be determined using an Expectation Maximization
algorithm. Furthermore, we show how the model can be used to mitigate
cost overruns resulting from both biases.