Cynthia Rudin

[3] Rudin graduated summa cum laude from the University at Buffalo with a double major in mathematical physics and music theory in 1999.

[16] She received the 2013 INFORMS Innovative Applications in Analytics Award for her work on electrical grid reliability, the 2016 INFORMS Innovative Applications in Analytics Award for work on interpretable machine learning models for assessing cognitive decline, and the 2019 INFORMS Innovative Applications in Analytics Award for work on interpretable machine learning models for seizure prediction in critically ill patients, leading to the 2HELPS2B score used in intensive care units.

[19] Rudin has given keynotes talks at KDD (2014 and 2019) [20], AISTATS [21], and the Nobel Conference (2021) Starting in 2007, Rudin was the lead scientist on a collaborative project between Columbia University and Con Edison to use machine learning to maintain New York City's secondary electrical distribution network.

Series Finder was built into the Patternizr algorithm [23] used by the NYPD to detect patterns of crime committed by the same individual(s).

Rudin's work on scoring systems with former student Berk Ustun was used for developing medical scoring systems for sleep apnea screening and diagnosis, for seizure prediction in ICU patients, for ADHD screening in adults, and for detection of cognitive decline using handwriting analysis (the Clock Drawing test).

Her PhD thesis answered a well-studied question of whether AdaBoost maximizes the L1 margin, which is a type of distance between a decision boundary and the data observation closest to it.