ΑΙhub.org
 

Cynthia Rudin wins AAAI Squirrel AI Award


by
15 October 2021



share this:
Cynthia Rudin

Cynthia Rudin, professor of computer science at Duke University, USA, has become the second recipient of the AAAI Squirrel AI Award. She was awarded the 2022 prize for pioneering scientific work in the area of interpretable and transparent AI systems in real-world deployments, the advocacy for these features in highly sensitive areas such as social justice and medical diagnosis, and serving as a role model for researchers and practitioners.

Cynthia talks about the prize, and what inspires her work, in this short video from Duke University:

Cynthia has worked on a variety of research topics during her career. The first applied project used machine learning to predict which manholes in New York City were at risk of exploding due to degrading and overloaded electrical circuitry.

An area of particular focus for Cynthia is interpretable machine learning, which she has applied in different settings. She, and her collaborators, designed a simple point-based system that can predict which patients are most at risk of having destructive seizures after a stroke or other brain injury. She also works on interpretable models in the field of criminal justice.

About the AAAI Squirrel AI Award

The AAAI Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity recognizes positive impacts of artificial intelligence to protect, enhance, and improve human life in meaningful ways with long-lived effects. The award is given annually at the conference for the Association for the Advancement of Artificial Intelligence (AAAI), and is accompanied by a prize of $1,000,000 plus travel expenses to the conference. Financial support for the award is provided by Squirrel AI. The award was given for the first time in 2021.

Cynthia Rudin biography

Cynthia earned undergraduate degrees in mathematical physics and music theory from the University at Buffalo before completing her PhD in applied and computational mathematics at Princeton. She then worked as a National Science Foundation postdoctoral research fellow at New York University, and as an associate research scientist at Columbia University. She became an associate professor of statistics at the Massachusetts Institute of Technology before joining Duke’s faculty in 2017, where she holds appointments in computer science, electrical and computer engineering, biostatistics and bioinformatics, and statistical science.

You can read the AAAI press release here.



tags: ,


Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

What’s on the programme at #AIES2026?

  12 Oct 2026
The ninth conference on AI, ethics, and society is taking place in Malmö from 12-14 October.

Generative AI has changed mathematics forever. Where to from here?

  12 Oct 2026
Large language models such as ChatGPT and Claude are creating disruptions in all parts of the mathematical community.

Cybersecurity, evolutionary game theory, and AI safety: an interview with Adeela Bashir

  09 Oct 2026
In the latest of our interviews with the IJCAI-ECAI 2026 doctoral consortium participants, we learn about how cybersecurity attack and defence behaviours evolve.

2026 AAAI / ACM SIGAI Doctoral Consortium interviews compilation

  08 Oct 2026
We collate our interviews with the 2026 cohort of doctoral consortium participants.

Machine learning for clinical time-series forecasting: an interview with Mayra Elwes

  07 Oct 2026
Our series hearing from the IJCAI-ECAI doctoral consortium participants continues.

Can you teach yourself to detect AI writing? Maybe

  06 Oct 2026
Before generative AI, we could generally assume that written text had been composed by a human. This is no longer the case. So how can we spot AI-written text?

Interview with William Yijiang Li: vision language models and the physical world

  05 Oct 2026
How effective are vision language models at understanding how the physical world changes over time?

Forthcoming machine learning and AI seminars: October 2026 edition

  02 Oct 2026
A list of free-to-attend AI-related seminars that are scheduled to take place in the next couple of months.


↑


AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence