Master Theses in Visual Analytics Research @ VRVis Research Center, 2018
The Visual Analytics group at the VRVis Research Center in Vienna, Austria, consists of currently nine members who enjoy finding innovative solutions in a constructive and friendly atmosphere. We are offering several student positions to conduct master thesis research in Visual Analytics.
We are looking for students (f/m) who will support the group in further developing VRVis’ software “Visplore”, which is used to tackle data-related challenges of our industry partners in fields such as automotive industry (e.g. AVL List), energy production (e.g. Austrian Power Grid), industrial quality control (e.g. RHI Magnesita), and healthcare (e.g. HVB). In addition to mentoring by experienced team members, we offer to compensate for your research after successful completion.
Additional information regarding Visplore can be found at http://goo.gl/wqJ4AS
The following video illustrates an application of Visplore in the industrial sector: http://youtu.be/fpyDfj9sUjk
We are looking for students who are interested in conducting their master thesis in one of the following five areas:
1) Purpose-oriented recommendations for presenting data
When analyzing data it is often not known in advance, which visualizations provide the most interesting insights. The aim of this diploma thesis is to shorten the time for the identification of interesting views on data sets such as energy time series or measurements of industrial processes by recommendations. By combining an automated search for interesting representations with an intuitive overview of the possible options, the user should be led quickly to representations that show outliers, relationships and trends in the data well. Welcome additional skills: OpenGL-knowledge, GUI-programming.
2) Anomaly Detection and Signature Search in Time Series
This topic is about detecting anomalies and user-specified signatures in a variety of time series from the energy, industry, and meteorology sectors. For this purpose, high-performance methods are to be implemented, which detect different types of anomalies and show at which points of the time series certain user-defined patterns, such as noticeable jumps, occur. In addition to the algorithms, the creation of a suitable interface for the input of such signatures and the parameterization of the anomaly detection by the user is also part of the topic. For the representation of distribution and structure of the anomalies, existing visualizations of “Visplore” can be used. Welcome additional skills: Statistics, GUI-programming.
3) Bi-directional data transfer between Visplore and R
For data analysts, the easiest integration of analysis software such as Visplore into their work environment is important - often used is the free statistical software R. This thesis aims at implementing an extension of R with which the Visplore-based dashboards can directly be opened from the R console for certain R objects (such as data matrices). Likewise, it should be possible to update the R objects and define new ones according to user-specified changes of the data in the dashboards. Internally, the communication between the R environment and Visplore should be based on an existing JSON-based protocol, for which, as an illustrative example, an implementation for a
connection to MATLAB has already been performed.
4) Interactive dashboard "cycle analysis"
Many time series from the fields of energy, industrial processes, etc. have a cyclical course. The aim of this diploma thesis is to create an interactive dashboard based on the software Visplore that allows to extract cycles from long time series according to certain criteria and to make these cycles analyzable on the basis of suitable (mostly existing) representations as well as parameters. In order to define these parameters, interaction elements should be implemented in order to e.g. define thresholds or gradients. Welcome additional skills: OpenGL-knowledge, GUI-programming.
5) Automatic generation of web-based dashboards
- Knowledge of C++
- Knowledge of software engineering methods
- Interest in visualization of big data sets
- Welcome additional requirements see above beneath each topic
Contact @ VRVis
For further details and expression of interest (including your CV and your preferred topic(s)) please contact Mr. Harald Piringer at firstname.lastname@example.org
Applications are always welcome. We would like to especially encourage female candidates to apply: Please don't hesitate to get in touch with us.