# Cynthia Rudin
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Cynthia Diane Rudin (born 1976) is an American computer scientist and statistician specializing in machine learning and known for her work in interpretable machine learning. She is the director of the Prediction Analysis Lab at Duke University, where she is a professor of computer science, electrical and computer engineering, and statistical science.
== Education and career ==
Rudin graduated summa cum laude from the University at Buffalo with a double major in mathematical physics and music theory in 1999.
082 - What the 2021 $1M Squirrel AI Award Winner Wants You To Know About Designing Interpretable Machine Learning Solutions w/ Cynthia Rudin
Episode Description
As the conversation around AI continues, Professor Cynthia Rudin, Computer Scientist and Director at the Prediction Analysis Lab at Duke University, is here to discuss interpretable machine learning and her incredible work in this complex and evolving field. To begin, she is the…
Data Science for Criminal Justice: Can We Avoid Black Box Algorithms for High-Stake Decisions?
In this episode we examine the use of secret or black box algorithms for high-stake decisions, particularly in the criminal justice system. How do they factor in the decisions made every day by state and federal courts concerning bail, sentencing, and parole? Are black box algorithms fair and unbia…
Search versus design by Alex Flint
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio.
This is: Search versus design, published by Alex Flint on the AI Alignment Forum.
This work was supported by OAK, a monastic community in the Berkel…
Do Simpler Models Exist and How Can We Find Them?
Cynthia Rudin (Duke University) gives a OxCSML Seminar on Friday 14th May 2021. Abstract: While the trend in machine learning has tended towards more complex hypothesis spaces, it is not clear that this extra complexity is always necessary or helpful for many domains. In particular, models and the…
Do Simpler Models Exist and How Can We Find Them?
Cynthia Rudin (Duke University) gives a OxCSML Seminar on Friday 14th May 2021. Abstract: While the trend in machine learning has tended towards more complex hypothesis spaces, it is not clear that this extra complexity is always necessary or helpful for many domains. In particular, models and the…
AF - Encultured AI, Part 1 Appendix: Relevant Research Examples by Andrew Critch
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Encultured AI, Part 1 Appendix: Relevant Research Examples, published by Andrew Critch on August 8, 2022 on The AI Alignment Forum.
Also av…
AF - Encultured AI, Part 1 Appendix: Relevant Research Examples by Andrew Critch
Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Encultured AI, Part 1 Appendix: Relevant Research Examples, published by Andrew Critch on August 8, 2022 on The AI …
The Understandable Cynthia Rudin - 65th Conversation
Cynthia Rudin, the Earl D. McLean, Jr. Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics,and Biostatistics & Bioinformatics at Duke University (🔗, 🔗, 🔗), joins Michael and Dave for a fast and feisty conversation about how to make machines we can un…
Behind the scenes with the #INFORMS2024 Plenaries: AI Fireside Chat
We're continuing our countdown to the 2024 INFORMS Annual Meeting, in Seattle, Washington, October 20-23, when more than 6,000 INFORMS members, students, prospective employers and employees, and academic and industry experts will share the ways O.R. and analytics are fueling Smarter Decisions for …
Cynthia Rudin - Episode 86
In this episode of ACM ByteCast, Rashmi Mohan hosts 2025 ACM Fellow Cynthia Rudin, the Gilbert, Louis, and Edward Lehrman Distinguished Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics, and Biostatistics and Bioinformatics at Duke University, wher…
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