Maryam Ramezani is an Assistant Professor in the Department of Computer Engineering at Sharif University of Technology, where she leads DAISY Lab. She completed her PhD in Computer Engineering at Sharif in 2023, after an MSc and a BSc in Information Technology Engineering at the same university.
Her work sits between machine learning and data systems. On one side, she studies how learned components change the way data systems are built: query and database optimization, natural language interfaces such as Text-to-SQL, and agent systems that operate over real data. On the other, she works on the machine learning those systems need — inference over partially observed networks, diffusion and cascade models, uncertainty-aware prediction, and the detection of manipulated content in social media.
Alongside her academic work she has worked in industry as a consultant on artificial intelligence and business intelligence projects, as the technical director and co-founder of an MLOps startup, and as a project manager on smart-card systems. That experience shapes how the lab works: problems are chosen because they appear in real deployments, and results are expected to survive contact with real data.
Supervision
She supervises PhD, MSc and undergraduate students at Sharif. If you would like to work with the lab, read the open positions first.
@misc{abolhasani2026teacher,
title = {{Teacher-Student Structure for Domain Adaptation in Ensemble Audio-Visual Video Deepfake Detection}},
author = {Elham Abolhasani and Maryam Ramezani and Hamid R. Rabiee},
year = {2026},
eprint = {2606.15117},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2606.15117}
}
@article{ramezani2025artificial,
title = {{Artificial Intelligence Applications in Health Insurances: A Scoping Review}},
author = {Maryam Ramezani and Ahad Bakhtiari and Mohammadreza Mobinizadeh and Rajabali Daroudi and Hamid R. Rabiee and Alireza Olyaeemanesh and Ali Akbar Fazaeli and Hakimeh Mostafavi and Saharnaz Sazgarnejad and Sanaz Bordbar and Amirhossein Takian},
journal = {Cost Effectiveness and Resource Allocation},
year = {2025},
doi = {10.1186/s12962-025-00640-w},
url = {https://resource-allocation.biomedcentral.com/articles/10.1186/s12962-025-00640-w}
}
@article{ramezani2025applications,
title = {{Applications of Artificial Intelligence and the Challenges in Health Technology Assessment: A Scoping Review and Framework with a Focus on Economic Dimensions}},
author = {Maryam Ramezani and Ahad Bakhtiari and Rajabali Daroudi and Mohammadreza Mobinizadeh and Ali Akbar Fazaeli and Alireza Olyaeemanesh and Hamid R. Rabiee and Hakimeh Mostafavi and Saharnaz Sazgarnejad and Sanaz Bordbar and Amirhossein Takian},
journal = {Health Economics Review},
year = {2025},
doi = {10.1186/s13561-025-00645-4},
url = {https://healtheconomicsreview.biomedcentral.com/articles/10.1186/s13561-025-00645-4}
}
@misc{cheraghi2025epistemic,
title = {{Epistemic Uncertainty-aware Recommendation Systems via Bayesian Deep Ensemble Learning}},
author = {Radin Cheraghi and Amir Mohammad Mahfoozi and Sepehr Zolfaghari and Mohammadshayan Shabani and Maryam Ramezani and Hamid R. Rabiee},
year = {2025},
eprint = {2504.10753},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2504.10753}
}
@misc{ramezani2024detecting,
title = {{Detecting Popular Social Events through Limited Observation with Deep Survival Analysis}},
author = {Maryam Ramezani and Hossein Goli and AmirMohammad Izadi and Hamid R. Rabiee},
year = {2024},
eprint = {2410.01320},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2410.01320}
}
@article{ramezani2023joint,
title = {{Joint Inference of Diffusion and Structure in Partially Observed Social Networks Using Coupled Matrix Factorization}},
author = {Maryam Ramezani and Aryan Ahadinia and Amirmohammad Ziaei Bideh and Hamid R. Rabiee},
journal = {ACM Transactions on Knowledge Discovery from Data},
year = {2023},
eprint = {2010.01400},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2010.01400}
}
@article{ghorbanpour2023similarity,
title = {{FNR: A Similarity and Transformer-Based Approach to Detect Multi-Modal Fake News in Social Media}},
author = {Faeze Ghorbanpour and Maryam Ramezani and Mohammad Amin Fazli and Hamid R. Rabiee},
journal = {Social Network Analysis and Mining},
year = {2023},
doi = {10.1007/s13278-023-01065-0},
eprint = {2112.01131},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2112.01131}
}
@inproceedings{ramezani2019news,
title = {{News Labeling as Early as Possible: Real or Fake?}},
author = {Maryam Ramezani and Mina Rafiei and Soroush Omranpour and Hamid R. Rabiee},
booktitle = {IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining},
year = {2019},
eprint = {1906.03423},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/1906.03423}
}
ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2018
BibTeX
@article{ramezani2018community,
title = {{Community Detection Using Diffusion Information}},
author = {Maryam Ramezani and Ali Khodadadi and Hamid R. Rabiee},
journal = {ACM Transactions on Knowledge Discovery from Data},
year = {2018}
}
Maryam Tahani, Ali Mohammad Afshin Hemmatyar, Hamid R. Rabiee, Maryam Ramezani
ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2016
BibTeX
@article{tahani2016inferring,
title = {{Inferring Dynamic Diffusion Networks in Online Media}},
author = {Maryam Tahani and Ali Mohammad Afshin Hemmatyar and Hamid R. Rabiee and Maryam Ramezani},
journal = {ACM Transactions on Knowledge Discovery from Data},
year = {2016}
}
