Oğuzhan Fatih Kar

I am a Ph.D. student in computer science at the Swiss Federal Institute of Technology (EPFL), where I am advised by Amir Zamir. My current research interests are in building robust, adaptive, and multi-modal perception systems that can operate in the real world. My recent works on this topic are BRAVE, 4M, Rapid Network Adaptation, 3D Common Corruptions, and Cross-Domain Ensembles.

I received the B.S. and M.S. degrees in electrical engineering at METU, where I have worked with Figen Oktem. My M.S. work had focused on developing high-resolution and compressive reconstruction techniques for computational imaging.

Email / CV / Google Scholar / Github / LinkedIn / Twitter

Education

Ph.D. in Computer Science, 2024 (Expected)
EPFL

M.S. in Electrical and Electronics Engineering, 2019
METU (GPA:3.93/4.00) / Thesis

B.S. in Electrical and Electronics Engineering, 2017
METU (GPA:3.90/4.00)

News

Nov, 2023: I started my student researcher position at Google Zurich! I'll be focusing on multi-modal foundational models.

Feb, 2023: I gave a talk at KAUST Rising Stars in AI Symposium.

Dec, 2022: I gave a talk at AIP RIKEN TrustML Young Scientist Seminar.

Recent Work

	BRAVE: Broadening the visual encoding of vision-language models O.F. Kar, A. Tonioni, P. Poklukar, A. Kulshrestha, A. Zamir, F. Tombari arXiv, 2024 [Website]
	4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities O.F. Kar, R. Bachmann, D. Mizrahi, A. Garjani, M. Gao, D. Griffiths, J. Hu, A. Dehghan, A. Zamir arXiv*, 2024 (coming soon) [Website]
	Unraveling the Key Components of OOD Generalization via Diversification H. Benoit, L. Jiang, A. Atanov, O.F. Kar, M. Rigotti, A. Zamir ICLR*, 2024 [arXiv]
	4M: Massively Multimodal Masked Modeling D. Mizrahi, R. Bachmann, O.F. Kar, T. Yeo, M. Gao, A. Dehghan, A. Zamir NeurIPS, 2023 [Spotlight, Top 4%] [Website]
	Rapid Network Adaptation: Learning to Adapt Neural Networks Using Test-Time Feedback T. Yeo, O.F. Kar, Z. Sodagar, A. Zamir ICCV, 2023 [Website]
	3D Common Corruptions and Data Augmentation O.F. Kar, T. Yeo, A. Atanov, A. Zamir CVPR, 2022 [Oral, Top 4%] [Website] [Code] [Video] [Live Demo] [TrustML Talk]
	Robustness via Cross-domain Ensembles O.F. Kar, T. Yeo, A. Zamir ICCV, 2021 [Oral, Top 3%] [Website] [Code] [Video] [Slides]
	Robust Learning Through Cross-task Consistency A. Zamir, A. Sax, T. Yeo, O.F. Kar, N. Cheerla, R. Suri, Z. Cao, J. Malik, L. Guibas Arxiv, 2020. CVPR, 2020 [Best Paper Award Nominee, Oral] [Live Demo] [Visuals] [Website] [Code] [ECCV 2020 Demo Video]

Misc

Robustness and uncertainty estimation for visual perception

This is a presentation I made on the relation between robustness and uncertainty in computer vision. The video also includes an overview of three important papers in uncertainty estimation in deep learning models.

[Slides] [Paper #1] [Paper #2] [Paper #3]

M.S. Work (2018-2021)

(Complete list on Google Scholar)

	High-resolution Multi-spectral Imaging with Diffractive Lenses and Learned Reconstruction F.S. Oktem, O.F. Kar, C. D. Bezek, F. Kamalabadi IEEE Transactions on Computational Imaging, 2021 [Arxiv]
	Compressive Spectral Imaging with Diffractive Lenses O.F. Kar, F.S. Oktem Optics Letters, 2019 [arXiv]
	Real-time Compressive Video Reconstruction for Spatial Multiplexing Cameras O.F. Kar, A. Gungor, H.E. Guven IEEE GLOBALSIP, 2019 [Visuals]
	Learning-based Regularization for Spatial Multiplexing Cameras O.F. Kar, A. Gungor, H.E. Guven IEEE GLOBALSIP, 2019
	A Transform Learning-based Deconvolution Technique with Super-resolution and Microscanning Applications A. Gungor, O.F. Kar IEEE ICIP, 2019
	A Matrix-free Reconstruction Method for Compressive Focal Plane Array Imaging A. Gungor, O.F. Kar, H.E. Guven IEEE ICIP, 2018

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