@inproceedings{hasanov2026modules, abbr = {WISE-ST}, title = {Primary-Preserving Complementary Module Retrieval Across Formal Mathematics Libraries}, author = {Hasanov, Elgun and Bashirov, Fatulla and El Kadhi, Nahla}, booktitle = {WISE 2026, Student Track}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, year = {2026}, note = {Accepted for proceedings · Formal mathematics / semantic retrieval}, abstract = {Summary: Retrieval between MathComp/Rocq and mathlib/Lean is not always a one-to-one matching problem. This work studies complementary module retrieval while preserving the primary result, accounting for content distributed across different library boundaries.}, website = {https://conferences.sigappfr.org/wise2026/program-2/}, preview = {formal-libraries.svg}, selected = {true}, bibtex_show = {true} } @inproceedings{hasanov2026asymmetric, abbr = {CBMS}, title = {Asymmetric Cross-Cohort Generalization in Alzheimer's Disease Classification: A Bidirectional External Validation Study}, author = {Hasanov, Elgun and El Kadhi, Ayman and Safarli, Gulzar and El Kadhi, Nahla}, booktitle = {IEEE International Symposium on Computer-Based Medical Systems}, year = {2026}, abstract = {A bidirectional external-validation study of Alzheimer's disease classifiers across independent clinical cohorts.}, note = {Accepted full paper · Biomedical AI / external validation}, website = {https://www.linkedin.com/posts/elgunhas_geai4nd-ieee-cbms2026-activity-7457014694802026497-hVLD}, preview = {cross-cohort.svg}, selected = {true}, bibtex_show = {true} } @inproceedings{hasanov2026leakagesafe, abbr = {KES}, title = {Leakage-Safe Machine Learning for Alzheimer's Disease Classification with External Validation on ADNI and OASIS}, author = {Hasanov, Elgun and El Kadhi, Ayman and Safarli, Gulzar and El Kadhi, Nahla}, booktitle = {KES International Conference}, year = {2026}, abstract = {A leakage-safe machine-learning evaluation across ADNI and OASIS with external validation.}, note = {Accepted for oral presentation and proceedings · Paper 337}, website = {https://www.linkedin.com/posts/elgunhas_30th-kes2026-biomedicalai-activity-7462041820777299968-Beye}, preview = {cross-cohort.svg}, bibtex_show = {true} } @inproceedings{hasanov2026attentiondep, abbr = {WISE}, title = {AttentionDep: Knowledge-Infused Attention for Interpretable Depression Severity Assessment from Social Media}, author = {Ibrahimov, Yusif and Anwar, Tarique and Yuan, Tommy and Mutallimov, Turan and Hasanov, Elgun}, booktitle = {WISE 2026, Main Research Track}, year = {2026}, address = {Venice, Italy}, abstract = {A knowledge-infused attention approach for interpretable depression-severity assessment from social-media text.}, note = {Accepted for presentation · Mental-health NLP / interpretable attention}, website = {https://conferences.sigappfr.org/wise2026/program-2/}, code = {https://github.com/ioseff-i/AttentionDep}, preview = {attentiondep.svg}, selected = {true}, bibtex_show = {true} } @inproceedings{hasanov2026trustllms, abbr = {AIDT}, title = {Can We Trust LLMs for Mental Health-Based Decisions? A Causality Aware Reliability Analysis}, author = {Ibrahimov, Yusif and Mutallimov, Turan and Mirzabayov, Seymour and Hasanov, Elgun}, booktitle = {Artificial Intelligence for Digital Transformations (AIDT)}, series = {Communications in Computer and Information Science}, volume = {3023}, pages = {251--263}, publisher = {Springer}, year = {2026}, address = {UFAZ}, doi = {10.1007/978-3-032-31319-5_17}, html = {https://link.springer.com/chapter/10.1007/978-3-032-31319-5_17}, pdf = {https://link.springer.com/content/pdf/10.1007/978-3-032-31319-5_17.pdf}, note = {Published · Open access · LLM reliability / causal analysis}, abstract = {Summary: An analysis of Qwen2.5-7B's attention in mental-health classification examines whether predictive signals align with domain reasoning. The work identifies a limitation in attention-based causal discovery and studies a correction using contrastive TF-IDF and directed pointwise mutual information.}, preview = {causal-analysis.svg}, dimensions = {true}, selected = {true}, bibtex_show = {true} } @inproceedings{hasanov2025ensemble, abbr = {DASA}, title = {Decision Support through Feature-Aware Ensemble Clustering: A Multi-Algorithm Fusion Framework for Complex Data Analysis}, author = {Hasanov, Elgun and El Kadhi, Nahla El Zant}, booktitle = {International Conference on Decision Aid Sciences and Applications (DASA)}, year = {2025}, pages = {980--986}, doi = {10.1109/DASA68193.2025.11498998}, note = {Published · Ensemble clustering / decision support}, dimensions = {true}, bibtex_show = {true} } @inproceedings{hasanov2025fastsurfer, abbr = {DASA}, title = {Rapid Automated Alzheimer's Disease Classification Using FastSurfer Segmentation and Explainable Machine Learning}, author = {Safarli, Gulzar and El Kadhi, Ayman and Hasanov, Elgun and El Zant El Kadhi, Nahla}, booktitle = {International Conference on Decision Aid Sciences and Applications (DASA)}, year = {2025}, pages = {1527--1535}, doi = {10.1109/DASA68193.2025.11499040}, note = {Published · Medical imaging / explainable ML}, dimensions = {true}, bibtex_show = {true} } @article{ibrahimov2025attentiondep, abbr = {arXiv}, title = {AttentionDep: Domain-Aware Attention for Explainable Depression Severity Assessment}, author = {Ibrahimov, Yusif and Anwar, Tarique and Yuan, Tommy and Mutallimov, Turan and Hasanov, Elgun}, journal = {arXiv preprint arXiv:2510.00706}, year = {2025}, arxiv = {2510.00706}, doi = {10.48550/arXiv.2510.00706}, html = {https://arxiv.org/abs/2510.00706}, pdf = {https://arxiv.org/pdf/2510.00706}, abstract = {A domain-aware attention model that combines contextual text representations with mental-health knowledge for interpretable, ordinal depression-severity assessment.}, altmetric = {true}, dimensions = {true}, note = {Preprint · Earlier version of the WISE 2026 AttentionDep paper}, code = {https://github.com/ioseff-i/AttentionDep}, preview = {attentiondep.svg}, bibtex_show = {true} }