Motasem Alfarra

PhD Candidate - Electrical and Computer Engineering

KAUST

Biography

I am a Ph.D. candidate at KAUST in Saudi Arabia. I am part of the Image and Video Understanding Lab (IVUL) advised by Prof. Bernard Ghanem. I obtained my M.Sc degree in Electrical Engineering from KAUST, and my undergraduate degree in Electrical Engineering from Kuwait University. I am interested in test-time adaptation and continual learning. Previously, I worked on assessing and enhancing network robustness and leveraging robust models for different applications.

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Interests

Test Time Adaptation
Continual Learning
Adversarial Robustness
Computer Vision and Machine Learning

Education

PhD in Electrical and Computer Engineering, 2020-Present
KAUST
MSc in Electrical Engineering, 2019-2020
KAUST
BSc in Electrical Engineering, 2014-2018
Kuwait University

Experience

Research Internship

Qualcomm AI Research

May 2023 – Sep 2023 Amsterdam, Netherlands

Research internship at the federated learning team in Qualcomm AI Research.

Research Internship

Intel

Aug 2022 – Jan 2023 Münich, Germany

Research internship at the Embodied AI Lab at Intel supervised by Matthias Müller.

Research Internship

University of Oxford

Oct 2021 – Feb 2022 Oxford, United Kingdom

Research visit to the Torr Vision Group (TVG) supervised by Prof. Philip Torr.

Teacher Assistant

KAUST

Jan 2021 – May 2021 Saudi Arabia

I was a TA for the Ph.D course “Introduction to Computer Vision”.

Guest Lecturer

Universidad Panamericana

Jul 2020 – Jul 2020 Mexico

I gave one lecture titled “Adversarial Attacks and Network Robustness”.

Research Assistant

Kuwait University

Jul 2017 – May 2018 Kuwait

Developed algorithms and implemented network simulations.

Featured Publications

SimCS: Simulation for Domain Incremental Online Continual Segmentation

We leverage simulated data to mitigate forgetting in domain incremental continual segmentation.

Motasem Alfarra, Zhipeng Cai, Adel Bibi, Bernard Ghanem, Matthias Müller

SimCS: Simulation for Domain Incremental Online Continual Segmentation

Revisiting Test Time Adaptation under Online Evaluation

We propose a novel online evaluation protocol for Test Time Adaptation (TTA) methods, which penalizes slower methods by providing them with fewer samples for adaptation.

Motasem Alfarra, Hani Itani, Alejandro Pardo, Shyma Alhuwaider, Merey Ramazanova, Juan C. Pérez, Zhipeng Cai, Matthias Müller, Bernard Ghanem

Revisiting Test Time Adaptation under Online Evaluation

ANCER: Anisotropic Certification via Sample-wise Volume Maximization

We extend randomized smoothing to anisotropic distributions and optimize the anisotropic smoothing parameters per input point in randomized smoothing.

Motasem Alfarra, Francisco Eiras, M. Pawan Kumar, Philip H. S. Torr, Puneet K. Dokania, Bernard Ghanem, Adel Bibi

ANCER: Anisotropic Certification via Sample-wise Volume Maximization

On the Robustness of Quality Measures for GANs

We assess the adversarial robustness of Inception Score and Frechet Inception Distance (FID) and propose a robustified version of FID.

Motasem Alfarra, Juan C. Pérez, Anna Frühstück, Philip H. S. Torr, Peter Wonka, Bernard Ghanem

On the Robustness of Quality Measures for GANs

3DeformRS: Certifying Spatial Deformations on Point Clouds

We design the anti-adversary layer that enhances the robustness of pretrained models against strong adversarial attacks.

Motasem Alfarra, Gabriel Pérez, Juan C. Pérez, Silvio Giancola, Bernard Ghanem

3DeformRS: Certifying Spatial Deformations on Point Clouds

Combating Adversaries with Anti-Adversaries

We design the anti-adversary layer that enhances the robustness of pretrained models against strong adversarial attacks.

Motasem Alfarra, Juan C. Pérez, Ali Thabet, Adel Bibi, Philip H. S. Torr, Bernard Ghanem

Combating Adversaries with Anti-Adversaries

DeformRS: Certifying Input Deformations with Randomized Smoothing

We extend randomized smoothing to certify image deformations such as rotation, translation, scaling, and affine.

Motasem Alfarra, Adel Bibi, Naeemullah Khan, Philip H. S. Torr, Bernard Ghanem

DeformRS: Certifying Input Deformations with Randomized Smoothing

Gabor Layers Enhance Network Robustness

We replace the first convolutional layer in deep neural networks with a Gabor layer to enhance networks robustness.

Motasem Alfarra, Juan C. Pérez, Guillaume Jeanneret, Adel Bibi, Ali Thabet, Bernard Ghanem, Pablo Arbeláez

On the Decision Boundaries of Neural Networks: A Tropical Geometry Perspective

We characterizes the decision boundaries of neural networks using tropical geometry, and leverage this characterization into several applications.

Motasem Alfarra, Adel Bibi, Hasan Hammoud, Mohamed Gaafar, Bernard Ghanem

On the Decision Boundaries of Neural Networks: A Tropical Geometry Perspective

Recent Publications

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Kumail Alhamoud, Hasan Abed Al Kader Hammoud, Motasem Alfarra, Bernard Ghanem (2023). Generalizability of Adversarial Robustness Under Distribution Shifts. In TMLR [Featured].

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Joachim Houyon, Anthony Cioppa, Yasir Ghunaim, Motasem Alfarra, Anais Halin, Maxim Henry, Bernard Ghanem, Marc Van Droogenbroeck (2023). Online Distillation with Continual Learning for Cyclic Domain Shifts. In CVPRW'23.

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Juan C. Pérez, Motasem Alfarra, Ali Thabet, Pablo Arbeláez, Bernard Ghanem (2023). Towards Assessing and Characterizing the Semantic Robustness of Face Recognition. In CVPRW'23.

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Andrés Villa, Juan León Alcázer, Motasem Alfarra, Kumail Alhamoud, Julio Hurtado, Fabian Caba Heilbron, Alvaro Soto, Bernard Ghanem (2023). PIVOT: Prompting for Video Continual Learning. In CVPR'23.

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Yasir Ghunaim, Adel Bibi, Kumail Alhamoud, Motasem Alfarra, Hasan Hammoud, Ameya Prabhu, Philip H. S. Torr, Bernard Ghanem (2023). Real-Time Evaluation in Online Continual Learning: A New Hope. In CVPR'23.

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Contact

motasem.alfarra@kaust.edu.sa
KAUST, Thuwal, 23955
Building 1 - level 2 - Desk 2106-WS14