AI and Machine Learning
NICO researchers spanning disciplines from engineering to business to biology and more utilize artificial intelligence and machine learning tools in identifying new and promising avenues for their research. Leveraging cutting-edge AI applications such as natural language processing, computer vision, and deep learning algorithms, they analyze complex datasets to uncover patterns, make predictions, and derive insights crucial to both their respective fields and society at large.
Faculty
NICO faculty members working in this area:
- Luis Amaral
- Rosemary Braun
- Steven Franconeri
- Matt Groh
- Ágnes Horvát
- Malcolm MacIver
- Todd Murphey
- Brian Uzzi
- Uri Wilensky
Select Publications
Read the following publications from NICO Faculty:
- Groh, Matt, Omar Badri, Roxana Daneshjou, Arash Koochek, Caleb Harris, Luis Soenksen, P. Murali Doraiswamy, Rosalind Picard. "Deep learning-aided decision support for diagnosis of skin disease across skin tones", Nature Medicine, February 2024
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Huang, Yitong, Rosemary Braun. "Platform-independent estimation of human physiological time from single blood samples", PNAS, January 2024
- Wu, Youyou, Yang Yang and Brian Uzzi. "A discipline-wide investigation of the replicability of Psychology papers over the past two decades", PNAS, January 2023
Additional Resources
The AI@NU website offers a variety of resources for the AI community at Northwestern.
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