I am a postdoctoral researcher at Speech Interaction Technology Group research group at Aalto University in Espoo, Finland. Since March 2025, I have also been a postdoctoral researcher in the TurkuNLP Group at the University of Turku, Turku, Finland.

My main research interest is AI for Social Good, with focus on Multilingual Natural Language Processing.

I received my doctoral degree in ICT at Web Science and Social Computing research group of Universitat Pompeu Fabra, Barcelona where I was advised by Prof. Carlos Castillo. My doctoral thesis focuses on developing a multilingual approach to extract, summarize, and prioritize crisis-related information from social media, enabling emergency managers and responders to efficiently monitor events, validate data, and address critical help-seeking requests.

I received my Master’s Degree (with honors) in Computational linguistics from the National Research University Higher School of Economics under the supervision of Prof. Nikolay Karpov with a dissertation titled “Deep Semantics in Expert Finding Systems.” We proposed an LSI-based topic similarity search model for authors of academic publications.

Before starting my Ph.D., I worked in Havas, Ailove and Convergent.

Publications

• Fedor Vitiugin, Hemant Purohit (2024). Serviceability Model for Ranking Multilingual Social Media Requests. Proceedings of ICWSM. [code]
• Fedor Vitiugin, Henna Paakki (2024). Ensemble-based Multilingual Euphemism Detection: a Behavior-Guided Approach. In Proceedings of the 4th Workshop on Figurative Language Processing (FigLang 2024) (pp. 73-78). [code]
• Fedor Vitiugin, Sunok Lee, Henna Paakki, Anastasiia Chizhikova, and Nitin Sawhney (2024). Unraveling Code-Mixing Patterns in Migration Discourse: Automated Detection and Analysis of Online Conversations on Reddit. Proceedings of the 5th International Workshop on Data for the Wellbeing of Most Vulnerable at AAAI ICWSM 2024.
• Datta, Preetha, Fedor Vitiugin, Anastasiia Chizhikova, Nitin Sawhney (2024). Construction of Hyper-Relational Knowledge Graphs Using Pre-Trained Large Language Models. Proceedings of the 4th Workshop on Graphs and more Complex structures for Learning and Reasoning at AAAI 2024.
• Hamada M. Zahera, Fedor Vitiugin, Mohamed Ahmed Sherif, Carlos Castillo, Axel-Cyrille Ngonga Ngomo (2023). Using Pre-Trained Language Models for Abstractive DBPEDIA Summarization: A Comparative Study. Knowledge Graphs: Semantics, Machine Learning, and Languages, pp. 19-37. IOS Press.
• Fedor Vitiugin, Carlos Castillo (2022). Cross-Lingual Query-Based Summarization of Crisis-Related Social Media: An Abstractive Approach Using Transformers. Proceedings of the 33rd ACM Conference on Hypertext and Social Media, Barcelona, Spain. [code]
• Lan Li, Aisha Aldosery, Fedor Vitiugin, Naomi Nathan, David Novillo-Ortiz, Carlos Castillo, Patty Kostkova (2021). The Response of Governments and Public Health Agencies to COVID-19 Pandemics on Social Media: A Multi-Country Analysis of Twitter Discourse. Frontiers in Public Health, 1410. [code]
• Fedor Vitiugin, Giorgio Barnabo (2021). Emotion Detection for Spanish by Combining LASER Embeddings, Topic Information, and Offense Features. IberLEF. Málaga, Spain. [code]
• Fedor Vitiugin, Yasas Senarath, Hemant Purohit (2021). Efficient Detection of Multilingual Hate Speech by Using Interactive Attention Network with Minimal Human Feedback. Proceedings of the 13th ACM Web Science Conference, Virtual Event, United Kingdom. [code]
• Fedor Vitiugin, Carlos Castillo (2019). Comparison of Social Media in English and Russian During Emergencies and Mass Convergence Events. ISCRAM. Valencia, Spain (WiPe).
• Nikolay Karpov, Julia Baranova, Fedor Vitiugin (2014). Single-sentence readability prediction in Russian. In International Conference on Analysis of Images, Social Networks and Texts (pp. 91-100). Springer, Cham.