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Shirin Seyedsalehi

PhD Student (Alumni)

Toronto Metropolitan University

Shirin Seyedsalehi is a former PhD student and alumna of the Human-Centered Machine Intelligence Lab at Toronto Metropolitan University. Her research focused on bias mitigation in information retrieval systems and neural ranking models.

Interests
  • Machine Learning
  • Information Retrieval
  • Bias Mitigation
  • Neural Networks

Latest

  • Self-Paced Fair Ranking with Loss as a Proxy for Bias
  • A contrastive neural disentanglement approach for query performance prediction
  • Bias-Aware Curriculum Sampling For Fair Ranking
  • Gender disentangled representation learning in neural rankers
  • De-biasing relevance judgements for fair ranking
  • Don't Raise Your Voice, Improve Your Argument: Learning to Retrieve Convincing Arguments
  • Neural disentanglement of query difficulty and semantics
  • A Light-Weight Strategy for Restraining Gender Biases in Neural Rankers
  • A Light-Weight Strategy for Restraining Gender Biases in Neural Rankers
  • A Neural Approach to Forming Coherent Teams in Collaboration Networks
  • A Neural Approach to Forming Coherent Teams in Collaboration Networks
  • Addressing gender-related performance disparities in neural rankers
  • Bias-aware Fair Neural Ranking for Addressing Stereotypical Gender Biases
  • Gender fairness in information retrieval systems
  • Matches made in heaven: Toolkit and large-scale datasets for supervised query reformulation
  • On the orthogonality of bias and utility in ad hoc retrieval

© 2026 Me. This work is licensed under CC BY NC ND 4.0

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