TaxoMine
Mining taxonomic knowledge from the scientific literature
Continues our work with biologists on extracting information about species from published papers, organised by taxonomy.
Joseph has been a researcher at IDSIA since September 2020. His interests include NLP for the biomedical domain, information extraction, summarisation and social media mining.
He holds a bachelor’s degree in computer science from Heinrich Heine University Düsseldorf and a master’s degree in neural systems and computation from the University of Zurich and ETH Zurich. Before IDSIA he was a research assistant at the Department of Computational Linguistics, University of Zurich.
Projects
AutoDischarge
Semi-automated generation of discharge summaries
Helps doctors write discharge letters faster by drafting them from the patient record, for the doctor to check and complete.
M2P2
Medical, multilingual and privacy-preserving NLP in the clinical domain
Makes modern language technology usable in Swiss hospitals: across the country's languages and without exposing patient data.
QUADRATIC
NLP in support of pharmacovigilance: Quality Adverse Drug Reaction Active Control
Finds reports of adverse drug reactions in clinical text, to support drug-safety monitoring.
DAG-MTSM
Detecting misinformation and machine-generated text
Developed and tested ways to detect misleading content and text written by language models. Produced the BUST benchmark.
Mini-MUSE
AI-based visualisation methods to explore digitised publications
Built interactive visual tools to explore large collections of digitised historical publications.
ArthroTraitMine
Mining arthropod traits from the literature
Built text-mining workflows and a database of traits of arthropods (insects, spiders, crustaceans and relatives) collected from the scientific literature.
INCdid
Dialect identification in noisy text
Developed methods to identify dialects in short, noisy texts, especially between closely related language varieties.
MisInfoCOV
Misinformation in social media during COVID-19
Studied how to identify misinformation on social media, and public stance towards health policies, during the pandemic.
COVID-19 Twitter Monitor
Social media mining for health
Combined ten methods for analysing COVID-19 tweets into one public platform with interactive visualisations.
Patient insights from social media
Mining patient insights in social media conversations
With Roche, extracted information from patient conversations online to support patient-centred drug development.
Publications with the group
- CANE is a Format: Rethinking Output Formats for Few-Shot LLM-Based Named Entity Recognition
- Presenting LLMs' Collective Intelligence Approach for Multilingual Hallucination Detection