From f02843eeb06cd9f5725d24d36a817c5ad25dcb42 Mon Sep 17 00:00:00 2001 From: Daniel Hladek Date: Fri, 24 Jul 2026 13:14:56 +0200 Subject: [PATCH] zz --- pages/interns/dries_huybens/README.md | 37 +++++++++++++++++++++++++++ 1 file changed, 37 insertions(+) create mode 100644 pages/interns/dries_huybens/README.md diff --git a/pages/interns/dries_huybens/README.md b/pages/interns/dries_huybens/README.md new file mode 100644 index 00000000..4e541089 --- /dev/null +++ b/pages/interns/dries_huybens/README.md @@ -0,0 +1,37 @@ +--- +title: Dries Huybens +published: true +taxonomy: + category: [erasmus] + tag: [nlp, ie, rag, medical] + author: Daniel Hladek +--- + +ERASMUS Intern Summer 2026, 20 July - 30 August + +Topic: + +Multilingual Knowledge Graphs from medical data + +Goal: + +- Construct a knowledge graph from medical package inserts in multiple languages +- Utilize the graph in an intelligent agent that recommends medication. + +Tasks: + +- Continue project of [Bogdan Paul Chis](/interns/bogdan_paul_chis) +- Study repositories: + - https://github.com/chis-facultate/erasmus-kosice + - https://github.com/hladek/mul-me-kg + - https://github.com/hkuds/lightrag + +- Learn intelligent agents and generative models - OpenAI API, Agent frameworks, RAG systems. +- Learn about knowledge graphs and GraphRAG. Read several research papers. +- Prepare a Python based workflow, use git code repository +- Visualize the graph +- Prepare an agent that utilizes the unstructured data and graph-data. +- Evaluate the agent using DeepEval or RAGAS. +- Write a report +- Put all code to GIT +