Publications

Publications with my students and collaborators. For the most up-to-date list and citation counts, see my Google Scholar profile. * denotes equal contribution.

2026

• Conformable Convolution for Topologically Constrained Learning of Complex Anatomical Structures

  Y. Yeganeh, G. Güvercin, N. Navab, A. Farshad

  AAAI Conference on Artificial Intelligence (AAAI) 2026 AAAI

• Predicting Postprandial Glycemic Response from Meal Images, Clinical Variables, and Gut Microbiome Information

  V. Kondratyeva, K. Zaripova, N. Navab, A. Farshad

  Workshop on Multimodal Learning with Medical Tabular Data, 2026 Workshop

• Millimeter-Wave Imaging for Anthropometric Body Measurement

  M. Senne, B.D. Killeen, C. Baur, N. Navab, A. Farshad

  arXiv preprint, 2026 Preprint

2025

• HieraSurg: Hierarchy-Aware Diffusion Model for Surgical Video Generation

  D. Biagini, N. Navab, A. Farshad

  MICCAI 2025 MICCAI

• DeepAF: One-Shot Spatiospectral Auto-Focus Model for Digital Pathology

  Y. Yeganeh, M. Frantzen, M. Lee, K.-H. Yu, N. Navab, A. Farshad

  MICCAI 2025 MICCAI

• Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis

  Y. Yeganeh, I. Charisiadis, M. Hasny, M. Hartenberger, B. Ommer, N. Navab, A. Farshad, E. Adeli

  CVPR 2025 CVPR

• Surgical Flow Masked Autoencoder for Event Recognition

  M. Lotfy Mostafa, A. Alperovich, D. Fedotov, G. Ghazaei, S. Saur, A. Farshad, N. Navab

  Medical Imaging with Deep Learning (MIDL) 2025 MIDL

• Self-Supervised 3D Medical Image Segmentation by Flow-Guided Mask Propagation Learning

  A. Bitarafan, M. Mozafari, M.F. Azampour, M.S. Baghshah, N. Navab, A. Farshad

  Medical Image Analysis, 2025 Journal

• Semantic Scene Editing for Cholecystectomy Surgery

  Ç. Köksal, Y. Yeganeh, N. Navab, A. Farshad

  International Workshop on Collaborative Intelligence and Autonomy in Image-Guided Surgery, 2025 Workshop

• MoViS: Motion-Guided Video Generation for Laparoscopic Surgery

  Y. Yeganeh, N. Navab, A. Farshad

  CREATE Workshop @ MICCAI 2025 · 🏆 Best Paper Award MICCAI

• PhenoKG: Knowledge Graph-Driven Gene Prioritization and Patient Insights from Phenotypes Alone

  K. Zaripova, E. Özsoy, N. Navab, A. Farshad

  arXiv preprint, 2025 Preprint

• Knowledge Graph Sparsification for GNN-Based Rare Disease Diagnosis

  P. Cara, K. Zaripova, D. Bani-Harouni, N. Navab, A. Farshad

  arXiv preprint, 2025 Preprint

• Stress-Aware Resilient Neural Training

  A. Shakarami, Y. Yeganeh, A. Farshad, L. Nicolè, S. Ghidoni, N. Navab

  arXiv preprint, 2025 Preprint

• Unit-Based Histopathology Tissue Segmentation via Multi-Level Feature Representation

  A. Shakarami, A. Farshad, Y. Yeganeh, L. Nicolè, P. Schüffler, S. Ghidoni

  arXiv preprint, 2025 Preprint

• VeLU: Variance-Enhanced Learning Unit for Deep Neural Networks

  A. Shakarami, Y. Yeganeh, A. Farshad, L. Nicolè, S. Ghidoni, N. Navab

  arXiv preprint, 2025 Preprint

2024

• PRISM: Progressive Restoration for Scene Graph-Based Image Manipulation

  P. Jahoda, Y. Yeganeh, E. Adeli, N. Navab, A. Farshad

  ECCV 2024 ECCV

• VISAGE: Video Synthesis Using Action Graphs for Surgery

  Y. Yeganeh, R. Lazuardi, A. Shamseddin, E. Dari, Y. Thirani, N. Navab, A. Farshad

  EARTH Workshop @ MICCAI 2024 · 🏆 Best Paper Award MICCAI

• Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis

  S. Löpke, Y. Yeganeh, E. Adeli, N. Navab, A. Farshad

  MICCAI 2024 MICCAI

• AMONuSeg: A Histological Dataset for African Multi-Organ Nuclei Semantic Segmentation

  H. Zerouaoui, G.P. Oderinde, R. Lefdali, K. Echihabi, S.P. Akpulu, N.A. Agbon, A.S. Musa, Y. Yeganeh, A. Farshad, N. Navab

  MICCAI 2024 MICCAI

• SANGRIA: Surgical Video Scene Graph Optimization for Surgical Workflow Prediction

  Ç. Köksal, G. Ghazaei, F. Holmé, A. Farshad

  GRAIL Workshop @ MICCAI 2024 · 🏆 Best Paper Award MICCAI

2023

• SceneGenie: Scene Graph Guided Diffusion Models for Image Synthesis

  A. Farshad, Y. Yeganeh, Y. Chi, C. Shen, B. Ommer, N. Navab

  SG2RL Workshop @ ICCV 2023 · 🏆 Best Paper Award ICCV

• Transformers Pay Attention to Convolutions: Leveraging Emerging Properties of ViTs by Dual Attention-Image Network

  Y. Yeganeh, A. Farshad, P. Weinberger, S.-A. Ahmadi, E. Adeli, N. Navab

  ICCV 2023 Workshops ICCV

• SCOPE: Structural Continuity Preservation for Retinal Vessel Segmentation

  Y. Yeganeh, G. Güvercin, R. Xiao, A. Abuzer, E. Adeli, A. Farshad, N. Navab

  MICCAI 2023 MICCAI

• VISA-FSS: A Volume-Informed Self-Supervised Approach for Few-Shot 3D Segmentation

  M. Mozafari, A. Bitarafan, M.F. Azampour, A. Farshad, N. Navab, M.S. Baghshah

  MICCAI 2023 MICCAI

• Anatomy-Aware Masking for Inpainting in Medical Imaging

  Y. Yeganeh, A. Farshad, N. Navab

  ShapeMI Workshop @ MICCAI 2023 MICCAI

• Representation Learning for Semantic Scene Understanding

  A. Farshad

  Hybrid Human-Artificial Intelligence (HHAI) 2023 HHAI

• Learning to Learn in Medical Applications: A Journey Through Optimization

  A. Farshad, Y. Yeganeh, N. Navab

  Meta Learning with Medical Imaging and Health Informatics Applications (Elsevier), 2023 Chapter

• Few-Shot Segmentation of 3D Medical Images

  A.G. Roy, S. Siddiqui, S. Pölsterl, A. Farshad, N. Navab, C. Wachinger

  Meta Learning with Medical Imaging and Health Informatics Applications (Elsevier), 2023 Chapter

2022

• Y-Net: A Spatiospectral Dual-Encoder Network for Medical Image Segmentation

  A. Farshad*, Y. Yeganeh*, P. Gehlbach, N. Navab

  MICCAI 2022 MICCAI

• DisPositioNet: Disentangled Pose and Identity in Semantic Image Manipulation

  A. Farshad, Y. Yeganeh, H. Dhamo, F. Tombari, N. Navab

  BMVC 2022 BMVC

• MetaMedSeg: Volumetric Meta-Learning for Few-Shot Organ Segmentation

  A. Farshad, A. Makarevich, V. Belagiannis, N. Navab

  DART Workshop @ MICCAI 2022 MICCAI

• FedAP: Adaptive Personalization in Federated Learning for Non-IID Data

  Y. Yeganeh, A. Farshad, J. Boschmann, R. Gaus, M. Frantzen, N. Navab

  DeCaF Workshop @ MICCAI 2022 MICCAI

2021

• Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information

  Y. Zhang, A. Khakzar, Y. Li, A. Farshad, S.T. Kim, N. Navab

  NeurIPS 2021 NeurIPS

• Unconditional Scene Graph Generation

  S. Garg, H. Dhamo, A. Farshad, S. Musatian, N. Navab, F. Tombari

  ICCV 2021 ICCV

• MIGS: Meta Image Generation from Scene Graphs

  A. Farshad, S. Musatian, H. Dhamo, N. Navab

  BMVC 2021 BMVC

• Meta-K: Towards Unsupervised Prediction of Number of Clusters

  A. Farshad, S. Hamidi, N. Navab

  ICLR 2021 Workshops ICLR

2020

• Semantic Image Manipulation Using Scene Graphs

  H. Dhamo*, A. Farshad*, I. Laina, N. Navab, G.D. Hager, F. Tombari, C. Rupprecht

  CVPR 2020 CVPR

• Inverse Distance Aggregation for Federated Learning with Non-IID Data

  Y. Yeganeh, A. Farshad, N. Navab, S. Albarqouni

  DART Workshop @ MICCAI 2020 MICCAI

Earlier

• Adversarial Network Compression

  V. Belagiannis*, A. Farshad*, F. Galasso

  ECCV 2018 Workshops ECCV

• SigmoRep: A Robust Reputation Model for Open Collaborative Environments

  A.A. Kardan, R. Salarmehr, A. Farshad

  IEEE TrustCom 2014 IEEE

Theses & Patents

• Learning to Learn Neural Representations with Limited Data and Supervision

  A. Farshad

  PhD Dissertation, Technical University of Munich, 2023 (summa cum laude) · 🏆 BVM 2025 Best Dissertation Award Thesis

• Neural Network Compression

  A. Farshad

  MSc Thesis, Technical University of Munich, 2018 Thesis

• Method for Producing a Compressed Version of an Artificial Neural Network

  V. Belagiannis, A. Farshad, F. Galasso

  Patent, 2018 Patent

Publication titles link to Google Scholar.