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MasterThesis
You need to share our love for running code and operational systems.
All thesis projects are exploratory research projects 45 ECTS master thesis. We offer a very wide range of topics: Web3, decentralised learning, blockchains, digital identity, digital Euros, personal data vaults, digital trust, etc.
PageRank is the defining centralised algorithm of Google. A small field is investigating architectures for decentralised machine learning. One of the initial works in this field is from Delft, G-Rank: Unsupervised Continuous Learn-to-Rank for Edge Devices in a P2P Network. The goal of this master thesis is to understand, improve, and implement the first true decentralised machine learning algorithm.
As a general intro, read the Wikipedia entry on decentralised search engines. Early work from 2005 by Delft provides a simple and realistic experimental approach to the problem of media discovery and recommendation, you are required to understand the basic algorithm of semantic clustering (e.g. taste buddies). A paper from 2012 proposes a model where mobile phones use gossip learning to compute a linear model, without revealing local models and without storing the full data set. Another classic attempt from 2003 onwards is the decentralised YaCy search engine with a web crawler, complex hashing, and reverse word index.
You master thesis task is to design and deploy a Euro coin with true gold value. For several years we have building prototypes at Delft for the upcoming digital Euro. See the latest offline Euro work by a team of master students for 5 ECTS. By using a small amount of antique gold it is possible to back a digital stable coin. The GoldEuro is an ownership token for actual physical gold. As such, it is stable, well understood legally, and easy to deploy. Going back to the gold standard has significant implication for payment systems and central banks. Money again has intrinsic value, limiting commercial money creation by banks. With GoldEuro citizens take back power in the global economy.
See example: https://arxiv.org/search/?query=pouwelse+survey&searchtype=all&source=header Approach: read 30+ papers, put them in a table, call this a taxonomy, write code, make screenshot, include this, DONE.