Dr. Vera Schmitt

Dr. Vera Schmitt

Head of XplaiNLP Research Group at Technische Universität Berlin and guest researcher at Speech and Language Technology at the German Research Center for Artificial Intelligence (DFKI)

About me

Research Interest of the XplaiNLP Research Group: Advancing Transparent and Trustworthy AI for Decision Support in High-Stakes Domains

At XplaiNLP research group, we are shaping the future of Intelligent Decision Support Systems (IDSS) by developing AI that is explainable, trustworthy, and human-centered. Our research spans the entire IDSS pipeline, integrating advances in natural language processing (NLP), large language models (LLM), explainability (XAI), evaluation, legal frameworks, and human-computer interaction (HCI) to ensure AI-driven decision-making aligns with ethical and societal values.

We focus on high-risk AI applications where human oversight is critical, including disinformation detection, social media analysis, medical data processing, and legal AI systems. Our interdisciplinary research tackles the following key challenges:

Our Methods: Advancing AI for Responsible Decision Support

We develop and refine AI methodologies that improve decision-making under uncertainty, including:

  • Retrieval-Augmented Generation (RAG) & Knowledge Retrieval: Enhancing the factual accuracy and reliability of AI-generated content by integrating structured and unstructured knowledge sources.
  • Natural Language Processing (NLP) & Large Language Models (LLM): Developing specialized language models for domain-specific tasks, with a focus on robustness, fairness, and generalization.
  • Explainable AI (XAI) for NLP: Creating methods that enhance model interpretability and user trust, ensuring that AI explanations are meaningful, especially in high-stakes environments.
  • Human-Computer Interaction (HCI) & Legal-AI Alignment: Designing AI systems that are usable, legally compliant, and human-centered, optimizing decision workflows for expert and non-expert users.
  • Evaluation & Safety of AI Models: Establishing rigorous performance assessment frameworks to measure bias, reliability, and long-term impact of AI systems in real-world applications.

Our Applications: Tackling High-Risk AI Challenges

We apply our AI advancements to critical, real-world decision-making scenarios, including:

  • Disinformation Detection & Social Media Analysis: Investigating misinformation, hate speech, and propaganda using advanced NLP and XAI methods. We analyze how AI-driven detection changes over time and how human perception of AI explanations evolves.
  • Medical Data Processing & Trustworthy AI in Healthcare: Developing AI tools that simplify access to medical information, improve faithfulness and factual consistency in medical text generation, and support clinicians in interpreting AI-generated recommendations.
  • Legal & Ethical AI for High-Stakes Domains: Ensuring AI decision support complies with regulatory standards, enhances explainability in legal contexts, and aligns with ethical AI principles.

Through interdisciplinary collaboration, hands-on research, and mentorship, XplaiNLP is at the forefront of shaping AI that is not only powerful but also transparent, fair, and accountable. Our goal is to set new standards for AI-driven decision support, ensuring that these technologies serve society responsibly and effectively.