Cynthia D. Rudin

Cynthia D. Rudin is the Gilbert, Louis, and Edward Lehrman Distinguished Professor of Computer Science at Duke University. She is also a Professor of Electrical and Computer Engineering, Professor of Statistical Science, Professor of Biostatistics and Bioinformatics (Joint). Her research focuses on interpretable machine learning and its applications, including algorithms for sparse models, interpretable neural networks, and dimension reduction for data visualization. Her lab applies these techniques to critical societal problems in healthcare, criminal justice, and other domains. She directs the Interpretable Machine Learning Lab and has received numerous awards, including the INFORMS Society on Data Mining Prize and the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity.

Cynthia Rudin is a Professor of Computer Science, ECE, Statistics, and Biostatistics & Bioinformatics at Duke University. Her research focuses on machine learning interpretability, data science, and the development of interpretable models for high-stakes decisions. Rudin's work emphasizes the importance of transparency in AI systems, particularly in domains such as healthcare and public policy. She has published extensively on the limitations of black-box models and the benefits of using interpretable alternatives. Her research also explores the application of machine learning in areas like medical scoring systems, case-based reasoning, and data visualization techniques.