Shadi Hamdan — accepted AI-conference papers

2025

ETA: Efficiency through Thinking Ahead, A Dual Approach to Self-Driving with Large Models

Shadi Hamdan, Chonghao Sima, Zetong Yang, Hongyang Li, Fatma Guney

ICCV 2025poster

How can we benefit from large models without sacrificing inference speed, a common dilemma in self-driving systems? A prevalent solution is a dual-system architecture, employing a small model for rapid, reactive decisions and a larger model for slower but more informative analyses. Existing dual-sys…

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2022

Self-Supervised Learning with an Information Maximization Criterion

Serdar Ozsoy, Shadi Hamdan, Sercan O Arik, Deniz Yuret, Alper Tunga Erdogan

NeurIPS 2022accept

Self-supervised learning allows AI systems to learn effective representations from large amounts of data using tasks that do not require costly labeling. Mode collapse, i.e., the model producing identical representations for all inputs, is a central problem to many self-supervised learning approache…

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