Stefan Bloemheuvel - PhD student
Cicek Güven - Assistant Professor
Jurgen van den Hoogen - PhD student
Dan Hudson - Master student
Rick Mackenbach - Master student
Menno van Leeuwen - Master student
Nikita Semionov - Scientific Programmer
Parisa Shayan - PhD student
Travis Wiltshire - Assistant Professor
Frederique van Leeuwen - Associated Researcher (PhD student, JADS)
The Computational Sensemaking Lab (CSLab) focuses on how to ‘make sense‘ in the context of complex information and knowledge processes from an interdisciplinary perspective.
By collecting and analyzing rich data to transform our understanding of individuals, organizations, and societies, we aim at augmenting human intelligence for assisting the involved actors in all their purposes both online and in the physical world.
This is enabled by developing computational methods and tools for computational sensemaking, focusing on advanced data modeling, explicative analysis, and transparent decision-support.
Our research focuses on:
Di-Plast: Digital Circular Economy for the Plastics Industry (funded by Interreg NWE). Di-Plast improves processes for a more stable rPM material supply and quality: sensoring generates data within supply chains; data analytics provides information about rPM quality, amounts, and supply timing; Value Stream Management improves rPM processes & logistics, environmental assessments validate sustainability.
Resilient Athletes: In this project (funded by ZonMW), a multidisciplinary personalized approach is being developed and applied. We focus on the resilience of athletes, with the aim that athletes can cope with the physical and mental stress factors to which they are exposed.
DIaNE, i.e. the "Deprez Integrated and Networked Environment", aims to make the Deprez-building (where MindLabs is located) "intelligent", using sensors and smart data analytics.
Stefan Bloemheuvel, Martin Atzmueller and Marie Postma: Evolution of Contacts and Communities in Social Interaction Networks of Face-to-Face Proximity Proc. BNAIC 2018, Jheronimus Academy of Data Science, Den Bosch, The Netherlands
Martin Atzmueller, Lisa Thiele, Gerd Stumme, and Simone Kauffeld. Analyzing Group Interaction on Networks of Face-to-Face Proximity using Wearable Sensors. Proc. IEEE International Conference on Future IoT Technologies, IEEE Press, Boston, MA, USA, 2018.
Martin Atzmueller, Daan Kolkman, Werner Liebregts and Arjan Haring. Towards Estimating Happiness using Social Sensing: Perspectives on Organizational Social Network Analysis. Proc. Workshop on Affective Computing and Context Awareness in Ambient Intelligence, Valencia, Spain, 2018
Martin Atzmueller, Benjamin Kloepper, Hassan Al Mawla, Benjamin Jäschke, Martin Hollender, Markus Graube, David Arnu, Andreas Schmidt, Sebastian Heinze, Lukas Schorer, Andreas Kroll, Gerd Stumme, and Leon Urbas. Big Data Analytics for Proactive Industrial Decision Support: Approaches & First Experiences in the Context of the FEE Project. atp edition, (58)9 2016.
Lukas Eberhard, Christoph Trattner, and Martin Atzmueller. Predicting Trading Interactions in an Online Marketplace through Location-Based and Online Social Networks. Information Retrieval Journal, 22(2), 2019.
Grzegorz J. Nalepa, Martijn van Otterlo, Szymon Bobek and Martin Atzmueller: From Context Mediation to Declarative Values and ExplainabilityProc. FAIM/FIX/IJCAI 2018 Workshop on Explainable Artificial Intelligence (XAI), IJCAI 2018, Stockholm, Sweden.
The CSLab provides the VIKAMINE project for subgroup discovery and analytics, and the ConnectU software platform for enhancing physical and digital interactions, for connecting things, people, and minds.
VIKAMINE is an extensible open-source rich-client environment and platform for pattern mining and analytics. VIKAMINE features several powerful and intuitive visualizations complemented by fast automatic mining methods; it is provided as Open Source, under the GNU Lesser General Public License (LGPL). The R subgroup package (rsubgroup R package) provides a wrapper around the VIKAMINE core.
ConnectU is based on Ubicon -- an extensible framework for building and hosting applications targeting both social and ubiquitous environments (see Conferator, EveryAware).
Ubicon provides a powerful platform featuring several components and mechanisms in order to handle heterogeneous (Big) data in a scalable way. The source code of Ubicon is available as Open Source, see code.ubicon.eu. The main module of Ubicon is licensed under the GNU AGPL, while several modules are also licensed under GNU LGPL (see the URL above for details).