Faegheh Sardari

ASG Office

Microsoft Campus

Thames Valley Park

Reading, England, UK

Email: f.sardari@microsoft.com

Hello. Thanks for visiting my webpage! My name is Faegheh (Fay). If you’re not familiar with this name, don’t worry—it’s a rare Persian name meaning “superior” or “distinguished”.

I’m a Senior Scientist at Microsoft, where I focus on developing small multimodal foundation models for Copilot+. Prior to that, I was a Postdoctoral Research Fellow at CVSSP, University of Surrey, working with Prof. Adrian Hilton on AI4me project, a partnership project between the University of Surrey and Lancaster University to leverage AI for personalised media production.

I completed my PhD at VI-Lab (now MaVi), University of Bristol, where I was awarded the university’s most prestigious and competitive PhD scholarship. During my PhD, I was supervised by Prof. Majid Mirmehdi and had the opportunity to collaborate with Prof. Björn Ommer from Ludwig Maximilian University of Munich.

I’m interested in complex video understanding and reasoning. In this context, ‘complex’ refers to the ability to analyse multiple modalities (audio, vision, language), multiple viewpoints, overlapping concepts, and long untrimmed videos. I’m also deeply interested in how advancements in video reasoning can enhance the capabilities of generative AI (GenAI).

News

Oct 01, 2025	I joined Microsoft as a Senior Scientist.
Feb 27, 2025	We secured a £100K grant (50% funded by EPSRC and 50% by Tesco) to advance video understanding for retail.
Feb 20, 2025	Our paper `NarrativeBridge’ is accepted at ICLR-2025.
Nov 28, 2024	We are organizing the 2nd workshop on Video Understanding and Its Application (VUA) at BMVC-2024
Jun 01, 2024	Our paper `CoLeaF’ is accepted at ECCV-2024

Selected Publications

Effective-Efficient

An Effective-Efficient Approach for Dense Multi-Label Action Detection

Faegheh Sardari, Armin Mustafa, Philip JB Jackson, and Adrian Hilton

IJCV, 2025

arXiv Bib

@article{sardari2024effective,
  title = {An Effective-Efficient Approach for Dense Multi-Label Action Detection},
  author = {Sardari, Faegheh and Mustafa, Armin and Jackson, Philip JB and Hilton, Adrian},
  journal = {IJCV},
  year = {2025}
}

RefDense

Reframing Dense Action Detection (RefDense): A Paradigm Shift in Problem Solving & a Novel Optimization Strategy

Faegheh Sardari, Armin Mustafa, Philip JB Jackson, and Adrian Hilton

arXiv, 2025

arXiv Bib HTML

@article{sardari2025deconstruct,
  title = {Reframing Dense Action Detection (RefDense): A Paradigm Shift in Problem Solving & a Novel Optimization Strategy},
  author = {Sardari, Faegheh and Mustafa, Armin and Jackson, Philip JB and Hilton, Adrian},
  journal = {arXiv},
  year = {2025}
}

Narrativebridge

Narrativebridge: Enhancing Video Captioning with Causal-Temporal Narrative

Asmar Nadeem, Faegheh Sardari, Robert Dawes, Syed Sameed Husain, and 2 more authors

In ICLR, 2025

arXiv Bib HTML

@inproceedings{nadeem2024narrativebridge,
  title = {Narrativebridge: Enhancing Video Captioning with Causal-Temporal Narrative},
  author = {Nadeem, Asmar and Sardari, Faegheh and Dawes, Robert and Husain, Syed Sameed and Hilton, Adrian and Mustafa, Armin},
  booktitle = {ICLR},
  year = {2025}
}

CoLeaF

CoLeaF: A Contrastive-Collaborative Learning Framework for Weakly Supervised Audio-Visual Video Parsing

Faegheh Sardari, Armin Mustafa, Philip JB Jackson, and Adrian Hilton

In ECCV, 2024

arXiv Bib HTML

@inproceedings{sardari2024coleaf,
  title = {CoLeaF: A Contrastive-Collaborative Learning Framework for Weakly Supervised Audio-Visual Video Parsing},
  author = {Sardari, Faegheh and Mustafa, Armin and Jackson, Philip JB and Hilton, Adrian},
  booktitle = {ECCV},
  pages = {1--17},
  year = {2024},
  organization = {Springer}
}

ForecasterFlexOBM

ForecasterFlexOBM: A Multi-View Audio-Visual Dataset for Flexible Object-based Media Production

Davide Berghi, Craig Cieciura, Farshad Einabadi, Maxine Glancy, and 7 more authors

In ICME, 2024

Bib HTML

@inproceedings{berghi2024forecasterflexobm,
  title = {ForecasterFlexOBM: A Multi-View Audio-Visual Dataset for Flexible Object-based Media Production},
  author = {Berghi, Davide and Cieciura, Craig and Einabadi, Farshad and Glancy, Maxine and Camilleri, Oliver C and Foster, Philip and Nadeem, Asmar and Sardari, Faegheh and Zhao, Jinzheng and Volino, Marco and others},
  booktitle = {ICME},
  pages = {1--6},
  year = {2024},
  organization = {IEEE}
}

PAT

PAT: Position-Aware Transformer for Dense Multi-Label Action Detection

Faegheh Sardari, Armin Mustafa, Philip JB Jackson, and Adrian Hilton

In ICCV workshop, 2023

arXiv Bib HTML

@inproceedings{sardari2023pat,
  title = {PAT: Position-Aware Transformer for Dense Multi-Label Action Detection},
  author = {Sardari, Faegheh and Mustafa, Armin and Jackson, Philip JB and Hilton, Adrian},
  booktitle = {ICCV workshop},
  pages = {2988--2997},
  year = {2023}
}

VI-Pose-2

Unsupervised View-Invariant Human Posture Representation

Faegheh Sardari, Björn Ommer, and Majid Mirmehdi

In BMVC, 2021

arXiv Bib HTML

@inproceedings{sardari2021unsupervised,
  title = {Unsupervised View-Invariant Human Posture Representation},
  author = {Sardari, Faegheh and Ommer, Bj{\"o}rn and Mirmehdi, Majid},
  booktitle = {BMVC},
  year = {2021}
}

VI-Net

VI-Net: View-Invariant Quality of Human Movement Assessment

Faegheh Sardari, Adeline Paiement, Sion Hannuna, and Majid Mirmehdi

Sensors, 2020

arXiv Bib HTML

@article{sardari2020vi,
  title = {VI-Net: View-Invariant Quality of Human Movement Assessment},
  author = {Sardari, Faegheh and Paiement, Adeline and Hannuna, Sion and Mirmehdi, Majid},
  journal = {Sensors},
  volume = {20},
  number = {18},
  pages = {5258},
  year = {2020},
  publisher = {MDPI}
}

VI-Pose-1

View-Invariant Pose Analysis for Human Movement Assessment from RGB Data

Faegheh Sardari, Adeline Paiement, and Majid Mirmehdi

In ICIAP, 2019

Bib HTML

@inproceedings{sardari2019view,
  title = {View-Invariant Pose Analysis for Human Movement Assessment from RGB Data},
  author = {Sardari, Faegheh and Paiement, Adeline and Mirmehdi, Majid},
  booktitle = {ICIAP},
  pages = {237--248},
  year = {2019},
  organization = {Springer}
}

MGBSA-2

A Hybrid Occlusion Free Object Tracking Method Using Particle Filter and Modified Galaxy based Search Meta-Heuristic Algorithm

Faegheh Sardari, and Mohsen Ebrahimi Moghaddam

Applied Soft Computing, 2017

Bib HTML

@article{sardari2017hybrid,
  title = {A Hybrid Occlusion Free Object Tracking Method Using Particle Filter and Modified Galaxy based Search Meta-Heuristic Algorithm},
  author = {Sardari, Faegheh and Moghaddam, Mohsen Ebrahimi},
  journal = {Applied Soft Computing},
  volume = {50},
  pages = {280--299},
  year = {2017},
  publisher = {Elsevier}
}

MGBSA-1

An Object Tracking Method Using Modified Galaxy-based Search Algorithm

Faegheh Sardari, and Mohsen Ebrahimi Moghaddam

Swarm and Evolutionary Computation, 2016

Bib HTML

@article{sardari2016object,
  title = {An Object Tracking Method Using Modified Galaxy-based Search Algorithm},
  author = {Sardari, Faegheh and Moghaddam, Mohsen Ebrahimi},
  journal = {Swarm and Evolutionary Computation},
  volume = {30},
  pages = {27--38},
  year = {2016},
  publisher = {Elsevier}
}