UT Austin ECE ยท Reliable learning systems

Mohamad Chehade

Reliable machine learning for risk, constraints, and decisions.

I am a Ph.D. student in Electrical and Computer Engineering at The University of Texas at Austin, advised by Prof. Hao Zhu. My research develops risk-aware and verifiable learning methods for decision-making under uncertainty, with applications in reinforcement learning, large language models, and power systems.

I received my B.Eng. in Electrical and Computer Engineering, with a minor in Mathematics, from the American University of Beirut, where I worked with Prof. Rabih Jabr and Prof. Sami Karaki. I have also interned at Los Alamos National Laboratory with Dr. Wenting Li, Dr. Brian Bell, and Dr. Russell Bent.

Research

Research directions

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If intelligence is a cake, the bulk of the cake is self-supervised learning, the icing on the cake is supervised learning, and the cherry on the cake is reinforcement learning.
Yann LeCun on the role of learning paradigms in AI

Selected Publications

Recent papers

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News

Recent updates

Two papers accepted to the 2026 IEEE Power & Energy Society General Meeting.
NEO-Grid accepted to HICSS 2026.
Papers LEVIS and SITAlign accepted to ICML 2025.
Awarded Best Graduate Presentation Award at NAPS 2024.