The Information Systems Research Lab focuses on the following areas of research:
1. Data Storage: Selecting the best storage solution for a given business case, ranging from centralized (SQL and NoSQL) to decentralized databases (DLT). Our highly experienced team has successfully deployed applications in both areas. The Blockchain Lab (a sub-entity of the Information Systems Research Lab) exclusively focuses on realizing Web 3 projects. These projects rely on Distributed Ledger Technology, including research into scalability, consensus building, Self-Sovereign Identity, privacy preservation and governance (DAOs).
2. Data Curation: This area is concerned with acquiring high-quality raw data from relevant sources and removing irrelevant and corrupt entries. Other tasks include data cleaning and merging and standardization to establish a cohesive dataset, which, if necessary, is enriched with labels and metadata in a final step. Our research aims to build these kinds of pipelines and to automate the relevant stages, providing a high-quality basis to build accurate and efficient machine learning-based applications.
3. Reliable Models: We excel at fine-tuning and evaluating state-of-the-art machine learning models while considering the requirements and constraints imposed by business applications or regulations. This allows us to tailor our models to specific use cases. What is more, we apply the latest research to explain model predictions, to prevent hallucinations and to ensure automated identification of low-quality outputs before they reach the customer. Visit the subsite dedicated to Natural Language Processing for more details.
4. Data Analysis: Another area of expertise within our lab is finding patterns, trends and other relevant information in datasets by using various state-of-the-art techniques and algorithms.
The list of all publications on the topic Distributed Ledger Technology on the Microsite des Blockchain Labs.
