Our research group Data Science and Language Technologies focuses on three key areas: 

1. PERSONALIZATION and ALIGNMENT 
In this research area, we investigate methods to personalize user experiences and align them with individual preferences and needs. This involves developing algorithms and models that adapt to user behavior, context, and feedback to deliver tailored recommendations, content, and services.

2. KNOWLEDGE AUGMENTATION
Our group explores techniques to enhance and augment knowledge bases, language models, and information retrieval systems. We aim to advance the capabilities of these systems by incorporating structured and unstructured data sources, improving semantic understanding, and enabling effective knowledge extraction and representation.

3. ROBUSTNESS, FAIRNESS and EFFICIENCY
We address challenges related to the robustness, fairness, and efficiency of data-driven systems and language technologies. This includes developing methods to mitigate biases, ensure fairness in algorithmic decision-making, enhance system robustness against adversarial attacks, and optimize computational efficiency for real-world deployment.

Through interdisciplinary collaboration and cutting-edge research methodologies, we strive to advance the state-of-the-art in data science and language technologies, with a focus on addressing real-world problems and societal challenges.

For more information about our ongoing projects, publications, and opportunities for collaboration, please explore the respective sections of our website or reach out to our team members directly. We welcome inquiries from researchers, students, and industry partners interested in joining us on our mission to push the boundaries of knowledge and innovation in these exciting research areas.