cart@itu.dk
This thesis looks to address how data analysis and geographic information systems can be used to track and predict epidemics, with a focus on the ebola epidemic in West Africa. With the use of data, especially when collected under time pressure, the importance of data reliability and validity follows. This is why we have to discuss and understand, how culture, demography and politics affects the outcomes of geographic analysis – and how we can close these data gaps.
mtx923@alumni.ku.dk
Wikipedia is the largest source of information ever collected and has huge influence around the globe, which enables certain narratives to control historical knowledge through language and culture. Using Wikipedia data, this project will investigate who is writing articles, in what languages and from where in the world. In a complementary qualitative analysis, I will seek to understand how the idea of Wikipedia may not fit the many types of diverse knowledge which exist around the world.
joser@itu.dk
My project concerns the methodological challenge within ethnography of accessing and investigating groups in society that are “hard to reach”, exploring the possibilities of materializing absence. The inspiration comes from my fieldwork in Costa Rica, where girls often go under the diagnostical radar. Since this group appears absent in a clinical and societal setting, I also want to investigate how to group comes to be in other spaces than those immediately accessible to the ethnographer.
mstp@itu.dk
How is it possible to mitigate the problem of hate speech on social media when the sheer amount is too large to go through manually? One approach is automated text classification. Stefan’s project attempts exactly that – to detect hate speech on Danish social media through deep learning methods. The main challenges are the lack of Danish data sets, the ambiguity of text, and the subjectivity of definitions and annotations.
ieja@itu.dk
Data Science enthusiast, studying MSc Software Development program at ITU and writing Master Thesis related to deep learning techniques. Striving to combine knowledge in human and artificial intelligence. At ETHOS, executing research of Neural Networks ‘Neuropsychology and Artificial Intelligence: Understanding Neural Networks via Cognitive Psychology’. Analyzing the complexity of AI decision making processes, introducing the explanations based on parallels between concept of AI and processes of cognitive psychology and raising the discussion about ethical questions.
lgro@itu.dk
I’m investigating creativity in relations to AI by asking the question: Can creativity be fostered by artificial means? For this, I will conduct interviews with different types of artists. Furthermore, I will do an auto-ethnographic study where I implement two types of deep learning art producing frameworks; A poetry and painting generator. The thesis will be essayistic and experimental in nature, influenced by a variety of philosophers, artists, and scientists.
Climate change is here, but necessary radical changes to unsustainable consumer lifestyles in the west, are not happening. Engineering advancements in energy-efficient products have been cancelled out by consumers, simply using more energy. A lot of design proposals has focused on making consumers ‘aware’ of their consumption patterns, but recent research indicates that awareness in itself does not have an effect on behavior. This project seeks to illuminate the reasons for this, and point at new design strategies that could have a more substantial impact.
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