Cynthia Rudin

Cynthia Rudin is a globally celebrated expert in artificial intelligence (AI), recognised for her groundbreaking contributions to interpretable machine learning. As a thought leader in ethical AI, she develops transparent, high-performing machine learning models that empower decision-makers in critical domains such as healthcare, criminal justice, and energy reliability. Her work combines technical precision with a commitment to societal benefit, setting new standards in the field of AI.

Holding the title of Gilbert, Louis, and Edward Lehrman Distinguished Professor of Computer Science at Duke University, she has multidisciplinary appointments in Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics, and Biostatistics & Bioinformatics. She directs the Interpretable Machine Learning Lab, which focuses on designing AI tools to improve decision-making in high-stakes environments. With a PhD in Applied and Computational Mathematics from Princeton University, her academic journey includes prestigious roles at MIT, Columbia University, and NYU.

Her career is marked by transformative achievements in AI. She is best known for her work on interpretable machine learning models, which provide ethical and explainable alternatives to black-box systems. Her innovations, such as optimal scoring systems for ICU seizure prediction, have saved millions in healthcare costs and improved patient outcomes. The Series Finder algorithm, adopted by the NYPD as Patternizr, has revolutionised crime pattern detection in law enforcement. A recipient of the 2022 Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity—equivalent to the Nobel Prize in AI—her impact on the field is unmatched. She also holds a Guggenheim Fellowship and multiple INFORMS Innovative Applications in Analytics Awards.

Cynthia Rudin is a sought-after keynote speaker, captivating audiences with her expertise in interpretable AI and ethical machine learning. She has delivered inspiring presentations at top-tier conferences such as KDD, INFORMS, and the Nobel Conference. Her talks explore the societal implications of AI, the importance of transparency, and the role of machine learning in shaping the future. With an engaging style, she connects with diverse audiences, inspiring action towards responsible AI innovation.