Publications

• S. Hashemifar and S. Sahebi, “Personalized student knowledge modeling for future learning resource prediction,” in The 26th International Conference on Artificial Intelligence in Education (AIED), 2025.

• S. Zhao and S. Sahebi, “Neighborhood-Aware Negative Sampling for Student Knowledge and Behavior Modeling,” in The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025, pp. 13374–13382. paper code slides

• S. Sahebi, M. Yao, S. Zhao, and R. Feyzi Behnagh “MoMENt: Marked Point Processes with Memory-Enhanced Neural Networks for User Activity Modeling”, ACM Transactions on Knowledge Discovery from Data (TKDD), 2024. paper code

• S. Zhao and S. Sahebi, “Multi-Task Modeling of Student Knowledge and Behavior,” in the 33rd ACM International Conference on Information and Knowledge (CIKM), 2024, pp.3363-3373. paper code slides

• S. Zhao and S. Sahebi, “Discerning Canonical User Representation for Cross-Domain Recommendation,” in the 18th ACM Conference on Recommender Systems (RecSys), 2024, pp.318-328. paper code slides

• S. Zhao and S. Sahebi, “Exploring Simultaneous Knowledge and Behavior Tracing,” in the 17th International Conference on Educational Data Mining (EDM), 2024, pp. 927-932. paper code

• C. Wang, S. Sahebi, “Continuous personalized knowledge tracing: Modeling long-term learning in online environments,” 2023, pp. 2616-2625. paper code slides

• S. Zhao and S. Sahebi, “Graph-enhanced multi-activity knowledge tracing,” in Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, 2023, pp. 529–546. paper code slides

• S. Zhao, S. Sahebi, and R. Feyzi-Behnagh, “Curb your procrastination: A study of academic procrastination behaviors,” in The 31st Conference on User Modeling, Adaptation and Personalization (UMAP), 2023. paper code slides

• S. Zhao, C. Wang, and S. Sahebi, “Transition-aware multi-activity knowledge tracing,” in The 2022 IEEE International Conference on Big Data, 2022. paper code slides video

• C. Wang, S. Sahebi, and P. Brusilovsky “Proximity-based educational recommendations: A multi-objective framework”, The 2nd Workshop on Multi-Objective Recommender Systems (MORS’22), 2022. paper

• M. Yao, S. Zhao, S. Sahebi, and R. Feyzi Behnagh “Stimuli-Sensitive Hawkes Processes for Personalized Student Procrastination Modeling”, The Thirtieth Web Conference (The Web-21), 2021. paper code slides video

• C. Wang, S. Sahebi, S. Zhao, P. Brusilovsky, and L. Moraes “Knowledge tracing for complex problem solving: Granular rank-based tensor factorization”, The 29th Conference on User Modeling, Adaptation and Personalization (UMAP-21), 2021. paper code

• M. Yao, S. Zhao, S. Sahebi, and R. Feyzi Behnagh “Relaxed clustered hawkes process for procrastination modeling in moocs”, Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021. paper code slides

• C. Wang, S. Zhao, and S. Sahebi “Learning from non-assessed resources: Deep multi-type knowledge tracing”, The 14th International Conference on Educational Data Mining (EDM-21), 2021. paper code

• M. Yao, S. Sahebi, R. Feyzi Behnagh, S. Bursali, and S. Zhao “Temporal processes associating with procrastination dynamics”, The 22nd International Conference on Artificial Intelligence in Education (AIED-21), 2021. paper

• C. Wang, S. Sahebi, and H. Torkamaan “STRETCH: Stress and Behavior Modeling with Tensor Decomposition of Heterogeneous Data”, The 2021 IEEE/WIC/ACM International Joint Conference On Web Intelligence And Intelligent Agent Technology (WI-IAT), 2021. paper code

• C. Wang, S. Sahebi, and P. Brusilovsky “MOCHI: an Offline Evaluation Framework for Educational Recommendations”, The Workshop on Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES’21), 2021. paper code

• T.N. Doan, and S. Sahebi, “Transcrosscf: Transition-based cross-domain collaborative filtering”, 19th IEEE International Conference on Machine Learning and Applications (ICMLA), 2020 paper code

• M. Mirzaei, S. Sahebi, and P. Brusilovsky, “SB-DNMF: A structure based discriminative non-negativematrix factorization model for detecting inefficient learning behaviors”, The 2020 IEEE/WIC/ACMInternational Joint Conference On Web Intelligence And Intelligent Agent Technology. WI-IAT, 2020. paper code video

• S. Zhao, C. Wang, and S. Sahebi, “Modeling Knowledge Acquisition from Multiple Learning Resource Types”, 13th International Conference on Educational Data Mining (EDM), 2020. paper code video

• M. Yao, S. Sahebi, and R. Feyzi Behnagh “Analyzing Student Procrastination in MOOCs: A Multivariate Hawkes Approach”, 13th International Conference on Educational Data Mining (EDM), 2020. paper code video

M. Mirzaei, S. Sahebi, , and P. Brusilovsky, “Detecting Trait versus Performance Student Behavioral Pattern Using Discriminative Non-Negative Matrix Factorization”, The Thirty-Third International FLAIRS Conference, 2020.

T.N. Doan, and S. Sahebi, “Review-Based Cross-Domain Collaborative Filtering: A Neural Framework”, Third Workshop on Recommendation in Complex Scenarios (ComplexRec), 2019.

T.N. Doan, and S. Sahebi, “Rank-Based Tensor Factorization for Student Performance Prediction”, 12th International Conference on Educational Data Mining (EDM), 2019.

M. Mirzaei, S. Sahebi, , and P. Brusilovsky, “Annotated Examples and Parameterized Exercises: Analyzing Student’s Sequential Patterns”, The 20th International Conference on Artificial Intelligence in Education (AIED), 2019.

S. Sahebi, , and P. Brusilovsky, “Student Performance Prediction by Discovering Inter-Activity Relations”, 11th International Conference on Educational Data Mining (EDM), 2018.

S. Sahebi, , P. Brusilovsky, and V. Bobrikov, “Cross-domain recommendation for large-scale data”, The 1st Workshop on Intelligent Recommender Systems by Knowledge Transfer & Learning (RecSysKTL), 2017.

S. Sahebi, Y. Lin, and P. Brusilovsky, “Tensor Factorization for Student Modeling and Performance Prediction in Unstructured Domain”, The 9th International Conference on Educational Data Mining, 2016.

S. Sahebi and P. Brusilovsky, “It Takes Two to Tango: an Exploration of Domain Pairs for Cross-Domain Collaborative Filtering”, 9th ACM Conference on Recommender Systems (RecSys), 2015. p. 131-138.

S. Sahebi and T. Walker, “Content-Based Cross-Domain Recommendations Using Segmented Models”, Workshop on New Trends in Content-based Recommender Systems (CBRecsys), 2014. p. 57-63.

J. Guerra, S. Sahebi, P. Brusilovsky, and Y. Lin, “The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises”, International Conference on Educational Data Mining, 2014. p. 153-160.

S. Sahebi, Y. Huang, and P. Brusilovsky, “Parameterized Exercises in Java Programming: using Knowledge Structure for Performance Prediction”, The second Workshop on AI-supported Education for Computer Science (AIEDCS), 2014.

S. Sahebi, Y. Huang, and P. Brusilovsky, “Predicting Student Performance in Solving Parameterized Exercises”, International Conference on Intelligent Tutoring Systems, 2014. p. 496-503.

S. Sahebi and P. Brusilovsky, “Cross-Domain Recommendation in a Cold-Start Context: The impact of User Profile Size on the Quality of Recommendation”, User Modeling and Adaptive Hypermedia, Springer Berlin Heidelberg, 2013. p. 289-295.

D. Parra and S. Sahebi, “Advanced Techniques in Web Intelligence - 2,” Advanced Techniques in Web Intelligence-2: Web User Browsing Behaviour and Preference Analysis, J. D. Vasquez et al. (Eds.), Ed. Berlin Heidelberg: Springer-Verlag, 2013, p. 149-175.

C. Lopez, R. Farzan, S. Sahebi, and P. Brusilovsky, “What Influences the Decision to Participate in Audience-bounded Online Communities?”, iConference, 2013.

S. Sahebi and W. W. Cohen, “Community-Based Recommendations: a Solution to the Cold Start Problem,” in Workshop on Recommender Systems and the Social Web (RSWEB), 2011.

P. Brusilovsky, D. Parra, S. Sahebi, and C. Wongchokprasitti, “Collaborative Information Finding in Smaller Communities: The Case of Research Talks,” in Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), IEEE, 2010.

S. Sahebi, C. Wongchokprasitti, and P. Brusilovsky, “Recommending Research Colloquia: A Study of Several Sources for User Profiling,” in International Workshop on Information Heterogeneity and Fusion in Recommender Systems (HetRec), 2010.