Teaching and Learning Concurrent Programming in the Shared Memory Model
Modern computers contain an increasing number of cores. As such, students of
computer science need to be familiar with concurrent programming in order to be
able to write correct and performant programs for these systems. In his PhD
thesis Filip Strömbäck investigates what areas of concurrent programming
students struggle with, and suggests ways in which teachers can help students
to better understand the subject.
Bayesian Models for Spatiotemporal Data from Transportation Networks
In this thesis, we develop Bayesian models with applications to transportation.
We specifically focus on models that can be trained on spatiotemporal data
coming from transport networks to make predictions on, e.g., bus delays or the
actual network topology. Special attention has been given to model scalability
issues and uncertainty quantification. We have used real-world data from
transportation systems in every study to keep a balance between statistical
rigor, novelty, and applicability.
Network-based Anomaly Detection for SCADA systems
Supervisory Control and Data Acquisition (SCADA) systems monitor critical
infrastructures such as power grid. As SCADA systems start adapting to the
Internet, cyber attacks against them become an attractive goal for attackers.
In her PhD thesis Chih-Yuan Lin presents new approaches for intrusion detection
that exploits the inherent timing characteristics present in a running system
and alert when anomalies arise.
Successful student collaboration for future material supply in health care.
The students in the project course for I and SVP (TDDC88) have developed
solutions for future inventory management of consumables in healthcare in a
Vinnova project with Region Östergötland, Rise, Mjärdevi Science Park and
Linköping and Kinda municipalities. An external evaluation shows, among other
things, high satisfaction among end users.
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