Moein Heidari

I'm a

About

Hi, I’m Moein! 👋

I'm a curious researcher who loves to explore the frontiers of Computer Vision, Machine Learning, and Deep Learning. My area of interest includes but is not limited to Transformers, medical image analysis, generative models, implicit neural representations, and object recognition. It is always my pleasure to discuss topics related to research. Feel free to email me! [My CV]

Experience


  • Remote Research Assistant, RWTH University, Aachen, Germany
  • Co-founderAIR Center, Tehran, Iran
  • B.Sc. in Electrical Engineering, Iran University of Science and Technology, Iran
  • Mar. 2022 - Present
  • Jul. 2020 - Jul. 2022
  • Sep. 2017 - Feb. 2022

News

Publications

  • INCODE: Implicit Neural Conditioning with Prior Knowledge Embeddings

Moein Heidari, Reza Azad, Alireza Hosseini, Dorit Merhof, Ulas Bagci

Conference: IEEE/CVF WACV 2024

Project Page | Paper | GitHub

  • Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation

Reza Azad, Leon Niggemeier, Michael Huttemann, Moein Heidari, Ehsan Khodapanah Aghdam, Yury Velichko, Ulas Bagci, Dorit Merhof

Conference: IEEE/CVF WACV 2024

Paper | GitHub

  • Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection

Reza Azad, Moein Heidari, Babak Azad, Ehsan Khodapanah Aghdam, Yury Velichko, Ulas Bagci, Dorit Merhof

Conference: MICCAI 2023

Paper | GitHub

  • Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in Transformers

Reza Azad, Moein Heidari, Alaa Sulaiman, Afshin Bozorgpour, Ehsan Khodapanah Aghdam, Abin Jose, Dorit Merhof

Conference: MICCAI 2023 MLMI Workshop

Paper | GitHub

  • DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation

Afshin Bozorgpour*, Yousef Sadegheih*, Moein Heidari*, Reza Azad, Dorit Merhof

Conference: MICCAI 2023 PRIME Workshop

Paper | GitHub

  • Self-supervised Semantic Segmentation: Consistency over Transformation

Sanaz Karimijafarbigloo, Reza Azad, Moein Heidari, Yury Velichko, Ulas Bagci, Dorit Merhof

Conference: ICCV 2023 CVAMD Workshop

Paper | GitHub

  • Implicit neural representation in medical imaging: A comparative survey

Amirali Molaei, Amirhossein Aminimehr, Armin Tavakoli, Moein Heidari, Bobby Azad, Reza Azad, Dorit Merhof

Conference: ICCV 2023 CVAMD Workshop

Paper | GitHub

  • Diffusion models in medical imaging: A comprehensive survey

Moein Heidari, Ehsan Khodapanah Aghdam, Moein Heidari, Reza Azad, Mohsen Fayyaz, Ilker Hacihaliloglu, Dorit Merhof

Journal: Medical Image Analysis (MedIA)

Paper | GitHub

  • Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review

Reza Azad, Moein Heidari, Moein Heidari, Ehsan Khodapanah Aghdam, Amirali Molaei, Yiwei Jia, Abin Jose, Rijo Roy, Dorit Merhof

Journal: Medical Image Analysis (MedIA)

Paper | GitHub

  • DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation

Reza Azad, René Arimond, Ehsan Khodapanah Aghdam, Moein Heidari, Dorit Merhof

Conference: MICCAI 2023 PRIME Workshop

Paper | GitHub

  • MS-Former: Multi-Scale Self-Guided Transformer for Medical Image Segmentation

Sanaz Karimijafarbigloo, Reza Azad, Moein Heidari, Dorit Merhof

Conference: MIDL 2023 | Oral presentation

Paper | GitHub

  • MMCFormer: Missing Modality Compensation Transformer for Brain Tumor Segmentation

Sanaz Karimijafarbigloo, Reza Azad, Moein Heidari, Saeed Ebadollahi, Dorit Merhof

Conference: MIDL 2023 | Oral presentation

Paper | GitHub

  • HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentation

Moein Heidari*, Moein Heidari*, Milad Soltany*, Reza Azad, Ehsan Khodapanah Aghdam, Julien Cohen-Adad, Dorit Merhof

Conference: IEEE/CVF WACV 2023

Paper | GitHub

  • An Intelligent Modular Real-Time Vision-Based System for Environment Perception

Moein Heidari, Amirhossein Heydarian, Milad Soltany, Aida Mohammadshahi, Abbas Omidi, Saeed Ebadollahi

Conference: NeurIPS 2022 Workshop on Machine Learning for Autonomous Driving

Paper | GitHub

Contact

For inquiries or feedback on my research, don't hesitate to reach out. I’m always happy to hear from you and exchange ideas.