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Ismail Elezi, Ph.D.

Hi, I'm Ismail. I am a Principal Research Scientist at Huawei Noah's Ark in London, working with Jiankang Deng, where I am leading one of the multi-modality learning teams.

After finishing my bachelor studies at the University of Prishtina, Kosovo, I obtained both my master's and Ph.D. degree at Ca' Foscari University of Venice, Italy, advised by professors Marcello Pelillo and Thilo Stadelmann. Then, I worked as a postdoctoral researcher with professor Laura Leal-Taixé at Technical University of Munich and interned with Jose M. Alvarez at NVIDIA, Santa Clara.

If you have a first author paper in a top ML/CV conference, and want to do an internship with me, please send me an email (find it in my CV). My interns/mentees usually author papers with me and go on to great companies or PhD programs.

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News

November 2025: One paper accepted to AAAI 2026. Congratulations to the team for ViCToR.
July 2025: Two papers accepted to ICCV 2025. Congratulations to the team for Semanticist and RICE (highlight)! Aloha Hawaii.
April 2025: Got chosen as Area Chair for NeurIPS 2025. First time I am doing this for a top-tier conference. #grownUp
February 2025: Got a paper accepted to CVPR 2025. Congratulations to Kostas.
January 2025: Finally got a paper accepted to ICLR. Congratulations to my former intern Prannay and see you in Singapore
September 2024: One paper accepted to NeurIPS 2024. Congratulations to Roy for VeLoRA. See you in Vancouver.
February 2024: Two papers accepted to CVPR 2024. Congratulations to Prady for G3DR and Roy for VKD! See you at Seattle.
November 2023: One paper got accepted to AAAI 2024. Congratulations to Chencheng!
April 2023: Started a new position as a Senior Research Scientist at Huawei Noah's Ark lab, working with Jiankang Deng. Very excited for the new work and for moving to London!
February 2023: One paper got accepted to CVPR 2023. Congratulations to Jenny!
September 2022: Two papers accepted to NeurIPS 2022. Congratulations to Vlad and Peter. Happy to be back to the US after covid.

Students and Interns Supervised

Ye Mao (Imperial College London, 2025)
Mohammad Sadil Khan (University of Kaiserslautern, 2025)
Yura Choi (Imperial College London, 2025)
Ye-Bin Moon (POSTECH, 2025)
Xin Wen (University of Hong Kong, 2024-2025)
Aysim Toker (Technical Unversity of Munich, 2024-2025)
Tatiana Gaintseva (Queen Mary University, 2024-2025)
Bingchen Zhao (University of Edinburgh, 2024)
Changrui Chen (Warvick University, 2024) → Research Scientist at Huawei
Prannay Kaul (University of Oxford, VGG, 2024)→ Applied Scientist at Amazon
Roy Miles (Imperial College London, 2023) → Research Scientist at Huawei
Konstantinos Alexandridis (King's College London, 2023) → Research Scientist at Huawei
Yunqi Miao (Warwick University, 2023) → Research Scientist at Huawei
Chencheng Ma (Chinese Academy of Sciences, 2023) → Research Scientist at Kunlun
Volodymyr Fomenko (Master thesis at TUM, 2022) → Technical Staff at OpenAI
Jenny Seidenschwarz (Master thesis and Ph.D. student at TUM, 2020-2023) → Ph.D. student at TUM
Franziska Gerken (Ph.D. student at TUM, 2020-2023) → Ph.D. student at TUM
Peter Kocsis (Master thesis at TUM, 2022) → Ph.D. student at TUM
Peter Sukenik (Guided Research at TUM, 2021) → Ph.D. student at IST Austriat
Feliks Hibraj (Research Intern at TUM, 2021) → Computer vision software engineer at SNAP
Laurin Wagner (Master thesis at TUM, 2020) → Machine learnign software engineer myReha

Service

Area Chair (AC) for WACV 2021, NeurIPS 2025.
Reviewer for top conferences and journals in Computer Vision and Machine Learning: CVPR, ECCV, ICCV, NeurIPS, ICML, ICLR, IJCV, TMLR, etc. I even managed to get outstanding reviewer awards in CVPR 2021 and ICCV 2021
I co-organized Deep Visual Similarity and Metric Learning tutorial in CVPR 2022.

Teaching

Summer 2022: Lecturer for IN2375: Computer Vision III: Detection, Segmentation and Tracking (CV3DST) (TU Munich)
Summer 2022: Lecturer for IN2346: Introduction to Deep Learning (I2DL) (TU Munich)
Winter 2021: Lecturer for IIN2375: Computer Vision III: Detection, Segmentation and Tracking (CV3DST) (TU Munich)
Winter 2021: Lecturer for IN2389: Advanced Deep Learning for Computer vision (ADL4CV) (TU Munich)
2019-2023: Lecturer for Introduction to Deep Learning with PyTorch (Datacamp). Around 30K students took the course before it got retired in 2023.
I have a few lectures online in Transformers, Semi-Supervised Learning, and Active Learning. They are a couple of years old so relatively outdated.

Selected Publications

Y. Xie, K. Yang, P.Liang, X. An, Y.Zhao, Y. Wang, Z. Feng, R. Miles, I. Elezi, J. Deng: : ViCToR: Improving Visual Comprehension via Token Reconstruction for Pretraining LMMs , Conference on Artificial Intelligence (AAAI), 2026.
paper

X. Wen, B. Zhao, I. Elezi, J. Deng, X. Qi : “Principal Components” Enable A New Language of Images , International Conference on Computer Vision (ICCV), 2025.
paper

Y. Xie, K. Yang, X. An, K. Wu, Y. Zhao, W. Deng, Z. Ran, Y. Wang, Z. Feng, R. Miles, I. Elezi, J. Deng: Region-based Cluster Discrimination for Visual Representation Learning , International Conference on Computer Vision (ICCV), 2025.
paper

K. Alexandridis, I. Elezi, J. Deng, A. Nguyen, S. Luo: Fractal Calibration for long-tailed object detection, Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
paper

P. Kaul, C. Ma, I. Elezi, J. Deng: From Attention to Activation: Unraveling the Enigmas of Large Language Models, International Conference on Learning Representations (ICLR), 2025.
paper

R. Miles, P.Reddy, I. Elezi, J. Deng: VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections, Neural Information Processing Systems (NeurIPS), 2024.
code paper

P. Reddy*, I. Elezi*, J. Deng: G3DR: Generative 3D Reconstruction in ImageNet, Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
page code paper

R. Miles, I. Elezi, J. Deng: VkD: Improving Knowledge Distillation using Orthogonal Projections, Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
code paper

C. Ma, I. Elezi, J. Deng, W. Dong, C. Xu: Three Heads Are Better Than One: Complementary Experts for Long-Tailed Semi-supervised Learning, Conference on Artificial Intelligence (AAAI), 2024.
code paper

J. Seidenschwarz, G. Braso, V. Serrano, I. Elezi, L. Leal-Taixé: Simple Cues Lead to a Strong Multi-Object Tracker, Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
code paper video

I. Elezi*, J. Seidenschwarz*, L. Wagner*, S. Vascon, A. Torcinovich, M. Pelillo, L. Leal-Taixé: The group loss++: A deeper look into group loss for deep metric learning, Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2023.
paper

V. Fomenko, I. Elezi, D. Ramanan, L. Leal-Taixé, A. Ošep: Learning to Discover and Detect Objects, Neural Information Processing Systems (NeurIPS), 2022.
page poster video code paper

P. Kocsis, P. Sukenik, G. Braso, M. Niessner, L. Leal-Taixé, I. Elezi: The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes, Neural Information Processing Systems (NeurIPS), 2022.
page code paper

I. Elezi, Z. Yu, A. Anandkumar, L. Leal-Taixé, J. Alvarez: Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object Detection, Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
code paper

J. Choi, I. Elezi, H. Lee, C. Farabet, J. Alvarez: Active Learning for Deep Object Detection via Probabilistic Modeling, International Conference on Computer Vision (ICCV), 2021.
code paper video

J. Seidenschwarz, I. Elezi, L. Leal-Taixé: Learning Intra-Batch Connections for Deep Metric Learning, International Conference on Machine Learning (ICML), 2021.
code paper video

I. Elezi, S. Vascon, A. Torcinovich, M. Pelillo, L. Leal-Taixé: The Group Loss for Deep Metric Learning, European Conference on Computer Vision (ECCV), 2020.
page code paper video

M. Maximov*, I. Elezi*, L. Leal-Taixé: CIAGAN: Conditional Identity Anonymization Generative Adversarial Networks, Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
code paper video

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