Daniel Haehn

Daniel Haehn is an Assistant Professor of Computer Science specializing in biomedical imaging and visualization research. His work focuses on developing computational methods to accelerate biological and medical research through web-based tools, machine learning, and interactive visualization systems.

Research Interests:
Dr. Haehn's research spans biomedical imaging, data visualization, machine learning applications in healthcare, web-based medical tools, human-computer interaction, reinforcement learning, and computer graphics. His work particularly emphasizes creating accessible web-based solutions for medical image processing and scientific visualization.

Awards and Recognition:

• Best Paper Award at IEEE VIS 2021
• Best Paper Award at IEEE VIS 2018
• Best Paper Award at IUI 2023