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Project
Scalable Software Solutions for Visualization and Analysis of Complex Data
My research concerns hypothesis-free exploration and visualization of high-dimensional data sets. One of the goals is to implement a quality-metric guided visualization pipeline that guides the user through the different stages of exploring hidden structures embedded in the plethora of dimensions of the data. This pipeline leverages recent advances in the field of distributed resource-sharing and computation platforms. We aim to test and apply this pipeline on data sets from the biological domain.
Date:19 Jun 2015 → 31 Jan 2019
Keywords:scalable, machine learning, visualisation
Disciplines:Applied mathematics in specific fields, Computer architecture and networks, Distributed computing, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences, Modelling, Biological system engineering, Signal processing, Control systems, robotics and automation, Design theories and methods, Mechatronics and robotics, Computer theory
Project type:PhD project