Die vielen Gesichter von GESIS
Vita
Taimoor Khan is a postdoctoral researcher in the KTS department at GESIS. He is part of the Big Data Analytics team and contributes to the services related to infrastructure and analytics of big data. His research interests include data analytics, natural language processing and machine learning. He received his PhD in Computer Science from Bahria University Islamabad in 2018 with the thesis titled "Lifelong machine learning topic modeling for large-scale aspect extraction". During his PhD, he worked with continuous machine learning models for sequential task processing that maintain a common knowledge base to avoid relearning the repetitive patterns in different tasks and improve them.Service
Methods HubForschung
Natural language processingmachine learning
Veröffentlichungen
Zeitschriftenaufsatz
Wajid, Usman, Muhammad Hamza, M. Taimoor Khan, and Nouman Azam. 2024. "A Three-way Decision Approach for Dynamically Expandable Networks." International Journal of Approximate Reasoning 166 (March 2024): 109105. doi: https://doi.org/10.1016/j.ijar.2023.109105.
Khan, M. Taimoor, Nouman Azam, Shehzad Khalid, and Furqan Aziz. 2022. "Hierarchical lifelong topic modeling using rules extracted from network communities." PLoS one: Public Library of Science 3 (17): 1-22. doi: https://doi.org/10.1371/journal.pone.0264481.
Beitrag im Sammelwerk
Gangopadhyay, Susmita, M. Taimoor Khan, and Hajira Jabeen. 2024. "Linguistic_Hygenist at PAN 2024 TextDetox: HybridDetox - A Combination of Supervised and Unsupervised Methods for Effective Multilingual Text Detoxification." In Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024) Grenoble, France, 9-12 September, 2024, edited by Guglielmo Faggioli, Nicola Ferro, Petra Galuščáková, and Alba García Seco de Herrera, CEUR workshop proceedings 3740, 2576-2584. Aachen: RWTH. https://ceur-ws.org/Vol-3740/paper-236.pdf.
Saadi, Khouloud, and M. Taimoor Khan. 2022. "Effective Prevention of Semantic Drift in Continual Deep Learning." In Intelligent Data Engineering and Automated Learning – IDEAL 2022: 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, edited by Hujun Yin, David Camacho, and Peter Tino, Lecture Notes in Computer Science 13756, 456-464. Cham: Springer. doi: https://doi.org/10.1007/978-3-031-21753-1_44. https://link.springer.com/chapter/10.1007/978-3-031-21753-1_44.
Konferenzbeitrag
Khan, M. Taimoor, Arnim Bleier, Chung-hong Chan, Po-Chun Chang, Raniere Gaia Costa da Silva, Danilo Dessi, Stefan Dietze, Gabriella Lapesa, Brigitte Mathiak, David Schoch, Claudia Wagner, and Hajira Jabeen. 2024. "Methods Hub: A Platform for Sharing Computational Social Science Methods." 4th Workshop on Computational Linguistics for the Political and Social Sciences (CPSS), 2024-09-13.
Costa da Silva, Raniere Gaia, Arnim Bleier, Chung-hong Chan, Po-Chun Chang, Stefan Dietze, M. Taimoor Khan, Gabriella Lapesa, Brigitte Mathiak, David Schoch, and Claudia Wagner. 2024. "Methods Hub Reproducible Computation Methods for Social Science Research." BioNT Community Event & CarpentryConnect - Heidelberg 2024, 2024-11-12.
Khan, M. Taimoor, Danilo Dessi, Fakhri Momeni, and Hajira Jabeen. 2024. "Reproducibility of AI/ML methods in computational social science." META-REP 2024 – the Conference on Meta-Science and Replicability in the social, behavioral, and cognitive sciences, 2024-10-28.
Bleier, Arnim, Chung-hong Chan, Po-Chun Chang, Raniere Gaia Costa da Silva, Danilo Dessi, Stefan Dietze, Hajira Jabeen, M. Taimoor Khan, Gabriella Lapesa, David Schoch, and Claudia Wagner. 2024. "The Methods Hub." ESWC (Extended Semantic Web Conference) Greece, 2024, 2024-05-26.
Momeni, Fakhri, and M. Taimoor Khan. 2024. "Transformer-based Multitask Learning German Sexism Detector." KONVENS (Konferenz zur Verarbeitung natürlicher Sprache/Conference on Natural Language Processing), 2024-09-09.