Our Mission
We focus on omni language AI research, advancing human language technologies, pushing forwards multimodal learning capabilities, and fostering societal impact through outreach efforts. Our work bridges technical sophistication with real-world applications, exploring fundamental research questions in natural language processing and multimodal AI while building large language models for societal impacts.
Our dynamic group consists of researchers, students and visitors from ELLIS Institute Finland, University of Turku (TurkuNLP group), and other collaborative institutions.
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Are you passionate about advancing NLP research and contributing to impactful societal applications? Although we currently do not have funded positions available, we welcome highly motivated Master’s students and visiting researchers to collaborate with us through external funding or self-supported programs.
Alumnus
Institution: Technical University of Darmstadt, Germany
Project: DYNAMIC (Dynamic Network Approach of Mental Health to Stimulate Innovations for Change)
Publications:
• Roleplaying with Structure: Synthetic Therapist-Client Conversation Generation from Questionnaires (arXiv 2025)
Institution: University of Helsinki, Finland
Project: MaLA-LM (Massive Language Adaptation of Large Language Models)
Publications:
• EMMA-500: Enhancing Massively Multilingual Adaptation of Large Language Models (arXiv 2024)
• Massively Multilingual Adaptation of Large Language Models Using Bilingual Translation Data (arXiv 2025)
Institution: University of Helsinki, Finland (jointly with Metsä Group)
Thesis: Integrating Open-Source Retrieval-Augmented Generation with Large Language Models for Business, Market and Responsibility Insights
Institution: Aalto University, Finland
Thesis: Joint entity and relation extraction via contrastive learning on knowledge-augmented graph embeddings
Publications:
• Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection (LREC-COLING 2024)
• Contextualized Graph Embeddings for Adverse Drug Event Detection (ECML-PKDD 2022)
Institution: Aalto University, Finland (jointly with HUS)
Thesis: Natural Language Processing with Topic Models for Clinical Texts of Prostate Cancer Patients
Publications:
• Weak Supervision and Clustering-Based Sample Selection for Clinical Named Entity Recognition (ECML-PKDD 2023)
Institution: Aalto University, Finland (jointly with HUS)
Thesis: Extracting Medical Entities from Radiology Reports with Ontology-based Distant Supervision
Publications:
• A Unified Review of Deep Learning for Automated Medical Coding (ACM Computing Surveys 2024)
• Weak Supervision and Clustering-Based Sample Selection for Clinical Named Entity Recognition (ECML-PKDD 2023)
• Multitask Balanced and Recalibrated Network for Medical Code Prediction (TIST 2022)
• Multitask Recalibrated Aggregation Network for Medical Code Prediction (ECML-PKDD 2021)