Machine and Hybrid
Intelligence Lab
Lab workspace

Machine and Hybrid Intelligence Lab

We study machine learning and human–AI collaboration for medical image analysis. Our research spans image segmentation, disease characterization, interpretable learning, and evaluation across clinical settings.

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Northwestern University

Research areas

Research across medical imaging, machine learning, and the role of human expertise in clinical decisions.

We investigate how clinicians’ visual attention can inform image analysis, model training, and human–AI interaction.

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Connected work

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Research schematics illustrate the methods; primary sources are linked in each research area.

Selected publications

Selected publications from the lab and our collaborators.

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2026

IPMN risk assessment with subregional radiomics and deep learning

Andrea Mia Bejar, Eminenur Sen Tasci, Max Nelson, Halil Ertugrul Aktas, Katie Wu, Ziliang Hong, Elif Keles, Muhammed Enes Tasci, Frank H Miller, Michael B Wallace, Rajesh N Keswani, Gorkem Durak, Ulas Bagci

MAYO CLINIC INNOVATIONS IN GASTROENTEROLOGY AND HEPATOLOGY 2026: ARTIFICIAL INTELLIGENCE AND BEYOND

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Dr. Ulas Bagci

Principal investigator

Ulas Bagci, PhD

Dr. Bagci leads the Machine and Hybrid Intelligence Lab. His research examines artificial intelligence for medical image analysis, with an emphasis on interpretable methods and the integration of human expertise.

The lab brings together researchers in machine learning, medical imaging, and clinical science.

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Research opportunities

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