I am a Research Scientist at Meta AI working on on-device ML and GenAI for photo and video edits.
Before that I was a Deep Learning Engineer at Apple,
and completed my PhD at TU Munich
in the group of Daniel Cremers.
My research interests span depth estimation, RGB-D scene understanding, visual representation learning, responsible AI, and on-device machine learning.
TRCØ
House and techno DJ based in New York City. Turkish lad finding the groove between Istanbul and Brooklyn.
Just getting started.
Datasets
Responsible AI
Casual Conversations v1
Meta AI · 2021
A dataset of 45,186 videos featuring paid participants to help researchers evaluate AI models for fairness across age, gender, and skin tone attributes.
Responsible AI
Casual Conversations v2
Meta AI · 2023
A dataset of 26,467 videos with broader fairness coverage — including age, gender, and physical attributes — for more robust AI model evaluation.
Focal Stack
DDFF 12-Scene
TU Munich · 2017
Large-scale focal stack benchmark with 12 indoor scenes and dense depth ground truth — 25× larger than prior benchmarks, enabling ML-based depth-from-focus research.
RGB-D
TUM-LSI
TU Munich · 2017
Large-scale indoor RGB-D dataset for scene understanding and semantic segmentation research, captured across real-world environments at TU Munich.
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The Bias of Harmful Label Associations in Vision-Language Models
C. Hazirbas, A. Sun, Y. Efroni, M. Ibrahim
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UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling
H. Al-Tahan, Q. Garrido, R. Balestriero, D. Bouchacourt, C. Hazirbas, M. Ibrahim
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ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations
B. Y. Idrissi, D. Bouchacourt, R. Balestriero, I. Evtimov, C. Hazirbas, et al.
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FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-based CNN Architecture
C. Hazirbas†, L. Ma†, C. Domokos, D. Cremers
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FlowNet: Learning Optical Flow with Convolutional Networks
A. Dosovitskiy, P. Fischer, E. Ilg, P. Häusser, C. Hazirbas, et al.
News
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Aug 2020
Joined Meta AI as Research Scientist.
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Jan 2019
Joined Apple as Deep Learning Engineer.
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Sep 2018
DDFF accepted to ACCV 2018, Perth, Australia.
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Jul 2018
Talk at ACM Munich ML Meetup #1 — Delving Deep into Computer Vision. Slides
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May 2018
Invited talk at ML Meetup #1, Munich.
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Feb 2018
Visiting Prof. Ian Reid's lab at ACVT, University of Adelaide.
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Oct 2017
ICCV paper featured in ICCV Daily.
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Sep 2017
Two papers at ICCV 2017. DDFF 12-Scene Benchmark released publicly.
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Apr 2017
Research internship at Disney Research Zurich.
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Jul 2016
Talk at DL Workshop, MPI-ETH — FlowNet.
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Nov 2015
Talk at CIS @LMU — CNNs for Computer Vision.
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Sep 2015
FlowNet accepted to ICCV 2015. Talk at MLSS'15 Kyoto.
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Jul 2015
Talk at Kleine Bayessche AG, Augsburg — CNNs for Computer Vision. Slides
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Jun 2015
Talk at ACM Munich Tech Talk — Deep Learning in Action. Slides