Sima Noorani
Ph.D. student at the University of Pennsylvania
Advised by
Hamed Hassani.
and
George J. Pappas
I am a Ph.D. student at the University of Pennsylvania working at the intersection of machine learning, uncertainty quantification, and conformal prediction. I am broadly interested in how to produce reliable uncertainty estimates for modern ML systems, including generative models, as well as how these ideas extend to human–AI interactions where people and AI collaboratively reason and make decisions. Prior to graduate school, I studied electrical engineering and computer science and interned at Lockheed Martin, Comcast, and Bristol Myers Squibb.
News & Talks
- Nov 2025 Here are my slides on "Uncertainty Quantification for Generative & Collaborative AI" presented at Max Planck Institute for Software Systems. slides
- Nov 2025 Here are my slides on “Human–AI Collaborative Uncertainty Quantification” presented at the Berkeley ANSR Reading Group. slides
- Oct 2025 “Conformal Prediction Beyond the Seen” accepted to NeurIPS 2025. SlidesLive
Papers
Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models
Neural Information Processing Systems (NeurIPS), 2025.
Also accepted to the R2-FM Workshop at ICML 2025.
[pdf]
Conformal Risk Minimization with Variance Reduction
In submission. Also accepted to the R2-FM Workshop at ICML 2025.
[pdf]
Human–AI Collaborative Uncertainty Quantification
arXiv:2510.23476, 2025.
[pdf]