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publications
Matches Made in Heaven: Toolkit and Large-Scale Datasets for Supervised Query Reformulation
Published in 30th ACM International Conference on Information & Knowledge Management (CIKM 2021, Core Rank: A), 2021
A large-scale dataset and toolkit for supervised query reformulation in search systems.
Recommended citation: Arabzadeh, N., Bigdeli, A., Seyedsalehi, S., Zihayat, M., & Bagheri, E. (2021). Matches Made in Heaven: Toolkit and Large-Scale Datasets for Supervised Query Reformulation. CIKM 2021.
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On the Orthogonality of Bias and Utility in Ad hoc Retrieval
Published in The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021, Core Rank: A*), 2021
An empirical study on the relationship between bias and utility dimensions in ad hoc retrieval.
Recommended citation: Bigdeli, A., Arabzadeh, N., Seyedsalehi, S., Zihayat, M., & Bagheri, E. (2021). On the Orthogonality of Bias and Utility in Ad hoc Retrieval. SIGIR 2021.
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A Light-weight Strategy for Restraining Gender Biases in Neural Rankers
Published in 44th European Conference on Information Retrieval (ECIR 2022, Core Rank: A), 2022
A computationally efficient bias mitigation approach for neural ranking models.
Recommended citation: Bigdeli, A., Arabzadeh, N., Seyedsalehi, S., Zihayat, M., & Bagheri, E. (2022). A Light-weight Strategy for Restraining Gender Biases in Neural Rankers. ECIR 2022.
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Bias-aware Fair Neural Ranking for Addressing Stereotypical Gender Biases
Published in 25th International Conference on Extending Database Technology (EDBT 2022, Core Rank: A), 2022
A fairness-aware neural ranking framework to mitigate gender stereotypes in retrieval systems.
Recommended citation: Seyedsalehi, S., Bigdeli, A., Arabzadeh, N., Mitra, B., Zihayat, M., & Bagheri, E. (2022). Bias-aware Fair Neural Ranking for Addressing Stereotypical Gender Biases. EDBT 2022.
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A Neural Approach to Forming Coherent Teams in Collaboration Networks
Published in 25th International Conference on Extending Database Technology (EDBT 2022, Core Rank: A), 2022
A neural model that identifies cohesive collaboration teams in large-scale networks.
Recommended citation: Seyedsalehi, S., Hamidi Rad, R., Kargar, M., Zihayat, M., & Bagheri, E. (2022). A Neural Approach to Forming Coherent Teams in Collaboration Networks. EDBT 2022.
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Generative Adversarial Networks for Propagation Channel Modeling
Published in AUT Journal of Modeling and Simulation, 2022
GAN-based modeling of wireless propagation channels for improved simulation fidelity.
Recommended citation: Seyedsalehi, S., Pourahmadi, V., Sheikhzadeh, H., & Gharari, A. H. (2022). Generative Adversarial Networks for Propagation Channel Modeling. AUT Journal of Modeling and Simulation.
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Addressing Gender-related Performance Disparities in Neural Rankers
Published in The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022, Core Rank: A*), 2022
An empirical study addressing gender-based disparities in neural retrieval models.
Recommended citation: Seyedsalehi, S., Bigdeli, A., Arabzadeh, N., Zihayat, M., & Bagheri, E. (2022). Addressing Gender-related Performance Disparities in Neural Rankers. SIGIR 2022.
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De-Biasing Relevance Judgements for Fair Ranking
Published in 45th European Conference on Information Retrieval (ECIR 2023, Core Rank: A), 2023
A data-centric framework to correct annotator bias in relevance judgements for fair IR evaluation.
Recommended citation: Bigdeli, A., Arabzadeh, N., Seyedsalehi, S., Mitra, B., Zihayat, M., & Bagheri, E. (2023). De-Biasing Relevance Judgements for Fair Ranking. ECIR 2023.
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Neural Disentanglement of Query Difficulty and Semantics
Published in 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023, Core Rank: A), 2023
A model that isolates query difficulty from semantic intent for better ranking behavior analysis.
Recommended citation: Salamat, S., Arabzadeh, N., Seyedsalehi, S., Bigdeli, A., Zihayat, M., & Bagheri, E. (2023). Neural Disentanglement of Query Difficulty and Semantics. CIKM 2023.
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Don’t Raise Your Voice, Improve Your Argument: Learning to Retrieve Convincing Arguments
Published in 45th European Conference on Information Retrieval (ECIR 2023, Core Rank: A), 2023
A learning-to-rank framework for persuasive argument retrieval from debate corpora.
Recommended citation: Salamat, S., Arabzadeh, N., Bigdeli, A., Seyedsalehi, S., Zihayat, M., & Bagheri, E. (2023). Don't Raise Your Voice, Improve Your Argument: Learning to Retrieve Convincing Arguments. ECIR 2023.
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A Contrastive Neural Disentanglement Approach for Query Performance Prediction
Published in Machine Learning Journal (Impact Factor: 4.3), 2024
Contrastive disentanglement of query attributes for robust performance prediction in retrieval.
Recommended citation: Salamat, S., Arabzadeh, N., Seyedsalehi, S., Bigdeli, A., Zihayat, M., & Bagheri, E. (2024). A Contrastive Neural Disentanglement Approach for Query Performance Prediction. Machine Learning Journal.
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Gender Disentangled Representation Learning in Neural Rankers
Published in Machine Learning Journal (Impact Factor: 4.3), 2024
A disentanglement-based neural ranking model that separates semantic relevance from gender information.
Recommended citation: Seyedsalehi, S., Salamat, S., Arabzadeh, N., Ebrahimi, S., Zihayat, M., & Bagheri, E. (2024). Gender Disentangled Representation Learning in Neural Rankers. Machine Learning Journal.
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Understanding and Mitigating Gender Bias in Information Retrieval Systems
Published in Foundations and Trends® in Information Retrieval (Impact Factor: 10.4), 2024
A systematic exploration of gender bias sources in IR pipelines and mitigation strategies across benchmarks.
Recommended citation: Seyedsalehi, S., Bigdeli, A., Arabzadeh, N., AlMousawi, B., Marshall, Z., Zihayat, M., & Bagheri, E. (2024). Understanding and Mitigating Gender Bias in Information Retrieval Systems. Foundations and Trends® in Information Retrieval.
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Bias-aware Curriculum Sampling for Fair Ranking
Published in The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025, Core Rank: A*), 2025
A curriculum strategy that progressively reduces ranking bias in neural retrieval systems.
Recommended citation: Seyedsalehi, S., Le, H. S., Zihayat, M., & Bagheri, E. (2025). Bias-aware Curriculum Sampling for Fair Ranking. SIGIR 2025.
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Query Performance Prediction Using Neural Query Space Proximity
Published in ACM Transactions on Intelligent Systems and Technology (Impact Factor: 6.6), 2025
A neural proximity-based model for predicting query performance using latent query representations.
Recommended citation: Bigdeli, A., Ebrahimi, S., Arabzadeh, N., Salamat, S., Seyedsalehi, S., Khodabakhsh, M., Zarinkalam, F., & Bagheri, E. (2025). Query Performance Prediction Using Neural Query Space Proximity. ACM Transactions on Intelligent Systems and Technology.
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A Regularization Framework for Bias Mitigation in Dense Neural Rankers
Published in Machine Learning Journal (Impact Factor: 4.3), 2025
A framework that mitigates representational bias in dense neural ranking models while preserving utility.
Recommended citation: Seyedsalehi, S., Zihayat, M., & Bagheri, E. (2025). A Regularization Framework for Bias Mitigation in Dense Neural Rankers. Machine Learning Journal.
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Reinforcement Learning for Effective Few-Shot Ranking
Published in The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025, Core Rank: A*), 2025
Reinforcement learning techniques that enhance few-shot ranking tasks with minimal supervision.
Recommended citation: Soleimani, S., Ebrahimi, S., Seyedsalehi, S., Zarinkalam, F., & Bagheri, E. (2025). Reinforcement Learning for Effective Few-Shot Ranking. SIGIR 2025.
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Self-Paced Fair Ranking with Loss as a Proxy for Bias
Published in WSDM 2025 (Core Rank: A), 2025
A self-paced learning framework that adaptively minimizes bias in neural ranking through loss-based sampling.
Recommended citation: Seyedsalehi, S., Le, H. S., Zihayat, M., & Bagheri, E. (2025). Self-Paced Fair Ranking with Loss as a Proxy for Bias. WSDM 2025 (Core Rank: A).
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research
Gender Disentangled Representation Learning in Neural Rankers
Published:
A disentanglement-based approach to reduce gender leakage in neural ranking models while preserving effectiveness.
talks
Stereotypical Gender Biases in Information Retrieval Systems
Published:
A research talk highlighting how stereotypical gender associations emerge in ranking models and discussing data-driven approaches for mitigation.
Gender Biases in Neural Rankers
Published:
An invited research talk focusing on quantifying and mitigating gender-related performance disparities in modern neural rankers.
Understanding and Mitigating Gender Bias in Information Retrieval Systems
Published:
This invited talk discussed sources of gender bias in information retrieval systems and introduced recent methods for mitigation and evaluation.
Understanding and Mitigating Gender Bias in Information Retrieval Systems
Published:
A presentation exploring bias sources in neural retrieval models and practical debiasing strategies within large-scale IR pipelines.
Gender Disentangled Representation Learning in Neural Rankers
Published:
This seminar introduced a disentanglement-based framework for reducing gender bias in neural ranking systems and discussed empirical findings on real-world search datasets.
Gender Disentangled Representation Learning in Neural Rankers
Published:
Paper presentation at ACML2024.
teaching
Statistics and Probability
Teaching Assistant, Department of Electrical Engineering, Amirkabir University of Technology, 2017
Conducted tutorial sessions and designed weekly quizzes for undergraduate students in Statistics and Probability (2017–2019).
COE758: Digital Systems Engineering
Teaching Assistant, Department of Electrical and Computer Engineering, Toronto Metropolitan University, 2021
Led tutorials and labs in digital design, logic circuits, and hardware simulation, providing guidance on assignments and course projects.
EES512: Electric Circuits
Teaching Assistant, Department of Electrical and Computer Engineering, Toronto Metropolitan University, 2022
Conducted tutorials and labs for multiple sections of Electric Circuits, focusing on circuit analysis, problem solving, and measurement techniques (2022–2024).
ELE888: Intelligent Systems
Teaching Assistant, Department of Electrical and Computer Engineering, Toronto Metropolitan University, 2022
Facilitated tutorials and problem-solving sessions on machine learning and intelligent systems concepts, supporting course delivery and grading.
Tutorial: Gender Fairness in Information Retrieval Systems
Tutorial, 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022), 2022
Co-presented a tutorial on fairness in neural retrieval systems, focusing on identifying, measuring, and mitigating gender bias.
COE848: Fundamentals of Data Engineering
Teaching Assistant, Department of Electrical and Computer Engineering, Toronto Metropolitan University, 2023
Delivered tutorials and hands-on exercises on data modeling, ETL workflows, and SQL, assisting students with assignments and grading.
ITM500: Data and Information Management
Teaching Assistant, Ted Rogers School of Management, Toronto Metropolitan University, 2023
Supported two sections of ITM500, teaching SQL, database design, and information retrieval concepts. Provided problem-solving support and graded assignments.
Tutorial: Understanding and Mitigating Gender Bias in Information Retrieval Systems
Tutorial, 45th European Conference on Information Retrieval (ECIR 2023), 2023
Co-led a tutorial on gender bias in information retrieval systems, covering bias sources, evaluation metrics, and mitigation strategies.
ITM200: Fundamentals of Programming
Instructor, Ted Rogers School of Management, Toronto Metropolitan University, 2025
Instructor for ITM200, introducing programming fundamentals, control structures, functions, and data types using Python. Responsible for lectures, assignments, and assessment.
ITM618: Business Intelligence and Analytics
Instructor, Ted Rogers School of Management, Toronto Metropolitan University, 2025
Instructor for ITM618, a senior undergraduate course focusing on business intelligence, data warehousing, and analytics-driven decision making. Responsibilities include designing course content, lecturing, and assessment.
ITM740: Artificial Intelligence in Business
Guest Lecturer, Ted Rogers School of Management, Toronto Metropolitan University, 2025
Guest lecture on applications of artificial intelligence in business contexts, focusing on fairness and bias in decision-support systems.