Below are the main research topics for the KASTLE lab. Current, past, and possible independent studies or research project opportunities are listed below each topic. We are currently welcoming Independent Studies and Master’s Theses pertaining to the below topics listed as “OPEN”.
Generally pertaining to the methodologies for developing of knowledge graphs, data integration, and ontology alignment, using human action.
Generally pertaining to the development of tools, frameworks, and methods for automatically constructing ontologies, as well as conducting data integration, semantic harmonization, schema alignment, and visualization.
Generally pertaining to the extraction of formal knowledge from unstructured natural language, which is subsequently used to inform downstream tasks.
Generally pertaining to the combination of symbolic knowledge representation and reasoning with the power of neural learning systems. These topics tend to bridge between many categories.
Generally pertaining to methods where knowledge graphs and semantic technologies are used to promote open science, improve reproducibility and replicability, discovery of long-tail data.
Generally pertaining to the methods for effective pedagogy of computer science, data science, knowledge graphs, Semantic Web, and knowledge engineering. Generally, this involves the following resources.
There is only a single topic, but it is quite variable, where contributing some set of articles based on interest could constitute an independent study.