Welcome to VisAI Lab!

We study how people can better interact with artificial intelligence, with special emphasis on biomedical applications.

Research Themes

Human–AI Collaboration

Effective teamwork between AI and human, such as scientists and clinicians

Data Visualization

Interactive visualization for complex data analysis and discovery

Biomedical Applications

Visualization and AI for biomedical science, education, and healthcare

AI for Science

AI co-scientists and autonomous science systems that accelerate scientific discovery

AI Interpretability

Interactive visualizations for interpreting, inspecting, and reasoning about AI models

	Automatic Synthesis of Visualization Design Knowledge Bases Hyeok Kim, Sehi L'Yi, Nils Gehlenborg, Jeffrey Heer CHI 2026 25.3% acceptance rate
	Learnable and Expressive Visualization Authoring Through Blended Interfaces Sehi L'Yi, Astrid van den Brandt, Etowah Adams, Huyen N. Nguyen, Nils Gehlenborg TVCG 2025 (VIS 2024) Best Paper Honorable Mention 23.2% acceptance rate
	Chromoscope: interactive multiscale visualization for structural variation in human genomes Sehi L'Yi, Dominika Maziec, Victoria Stevens, Trevor Manz, Alexander Veit, Michele Berselli, Peter J Park, Dominik Głodzik, Nils Gehlenborg Nature Methods 2023 Innovation In Cancer Informatics Major Grant Award 2023
	GenoREC: A Recommendation System for Interactive Genomics Data Visualization Aditeya Pandey, Sehi L'Yi**, Qianwen Wang, Michelle A Borkin, Nils Gehlenborg TVCG 2023 (VIS 2022) IEEE InfoVis Best Poster Research Award 26.5% acceptance rate
	Gosling: A Grammar-based Toolkit for Scalable and Interactive Genomics Data Visualization Sehi L'Yi, Qianwen Wang, Fritz Lekschas, Nils Gehlenborg TVCG 2022 (VIS 2021) ISMB/ECCB BioVis Best Abstract Award 25.8% acceptance rate