Hamed Karimi

Machine Learning Researcher @TorontoMet
Trustworthy AI and Machine Learning | Uncertainty Quantification in Deep Learning

[Hamed Karimi @thehdmx]

Many thanks to my co-authors and Prof. @RezaSamavi for the excellent collaboration.

Paper: https://t.co/z7sYiKNFfe
Code: https://t.co/yUkCBKTJbj

#TrustworthyAI #RobustAI #AdversarialRobustness #CertifiedRobustness #DeepLearning #MachineLearning

5/5

[Hamed Karimi @thehdmx]

Robust AI should not only resist adversarial perturbations; it should provide certifiable guarantees that its predictions remain stable under carefully crafted attacks.

Our paper, “CEAR: Certified Ensemble Adversarial Robustness in DNNs,” was accepted at Canadian AI 2026.

1/5

[Hamed Karimi @thehdmx]

CEAR combines model diversity, ensemble consensus, and randomized-smoothing-based certification to improve robustness beyond purely empirical defenses.

Our experiments show improved certified accuracy, larger robustness radii, and reduced adversarial transferability.

4/5

[Reza Samavi @RezaSamavi]

Conformal Prediction (CP) is a nice and (almost) assumption-free framework for quantifying uncertainty by constructing prediction sets with finite-sample coverage guarantees. @thehdmx

[Reza Samavi @RezaSamavi]

Another well-organized and successful ML Security and Privacy workshop. Active TAILab participation with posters on Uncertainty quantification (@thehdmx @Hirad_Daneshvar) and Certified robustness (@MrezaMaleki_95) . Thanx to @VectorInst @thegautamkamath @TMU_ecbe

[Andrei Manolache @ ICML @andreimano2]

@habib__slim 🧵1/n
Good question! My process is usually:
1) Skim the paper, take some notes;
2) Do an in-depth read and start writing strengths/weaknesses/questions (at this point I usually know the score);
3) Sleep on it and re-visit after a few days to write the final review.

[Hamed Karimi @thehdmx]

Special thanks to Dr. Simone Vantini and @DrMatteoFontana

Paper Link: https://t.co/NplbDvNne8

The 13th Symposium on Conformal and Probabilistic Prediction with Applications (COPA2024)
https://t.co/zHAFxqN6jQ

[Hamed Karimi @thehdmx]

Thrilled to present our paper "Evidential Uncertainty Sets in Deep Classifiers Using Conformal Prediction" with @RezaSamavi at COPA2024 in @polimi, Milan! Grateful for the opportunity to discuss our work on Uncertainty Quantification in #DeepLearning.

#ConformalPrediction #AI