🧑‍🔬 Radu Tudor Ionescu

🏛️ Affiliations

🎓University of BucharestBucharest · Romania2006–2026 · 214 papersEducation 2006–2009 · Bachelors, Faculty of Mathematics and Computer ScienceEducation 2009–2011 · Masters, Faculty of Mathematics and Computer ScienceEducation 2011–2013 · PhD, Faculty of Mathematics and Computer ScienceEmployment since 2016 · Associate Professor, Faculty of Mathematics and Computer ScienceEmployment since 2019 · Professorcurrent🔬Inception Institute of Artificial IntelligenceAbu Dhabi · United Arab Emirates2018–2019 · 4 papers🎓Université de MontréalMontreal · Canada2013 · 2 papers🎓Universitatea Națională de Știință și Tehnologie Politehnica BucureștiBucharest · Romania2004–2007 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Learning to Identify Arabic and German Dialects using Multiple Kernels (2017 · 64 citations)
   The paper describes the UnibucKernel entry to two closed dialect-identification shared tasks at the DSL 2017 Challenge (VarDial).
2. UnibucKernel: An Approach for Arabic Dialect Identification Based on Multiple String Kernels (2016 · 53 citations)
   The paper addresses Arabic Dialect Identification (ADI) in the closed track of the DSL 2016 Challenge. Systems had to assign each text to one of five classes: Modern Standard Arabic (MSA) or one of four dialects. The data are ASR transcripts of Broadcast News speech, so they may contain recognition errors. The…
3. UnibucKernel Reloaded: First Place in Arabic Dialect Identification for the Second Year in a Row (2018 · 39 citations)
   The paper describes UnibucKernel, the system that won the closed Arabic Dialect Identification (ADI) task at VarDial 2018.
4. Improving the results of string kernels in sentiment analysis and Arabic dialect identification by adapting them to your test set (2018 · 22 citations)
   The paper asks whether string kernels, which already lead several text classification benchmarks, can gain further accuracy by using the unlabeled test set during training.

All works

12 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. Object-Centric Auto-Encoders and Dummy Anomalies for Abnormal Event Detection in Video ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetRadu Tudor Ionescu et al.2019 · 430 citations
2. Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetNicolae-Cătălin Ristea et al.2022 · 292 citations
3. UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetAndra Acsintoae et al.2022 · 189 citations
4. Automated essay scoring with string kernels and word embeddings ↗Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · no summary yetMădălina Cozma, Andrei Butnaru, Radu Tudor Ionescu2018 · 161 citations
5. Learning to Identify Arabic and German Dialects using Multiple KernelsWorkshop on NLP for Similar Languages, Varieties and Dialects (VarDial)Radu Tudor Ionescu, Andrei Butnaru2017 · 64 citations
6. UnibucKernel: An Approach for Arabic Dialect Identification Based on Multiple String KernelsInternational Conference on Computational Linguistics (COLING)Radu Tudor Ionescu, Marius Popescu2016 · 53 citations
7. UnibucKernel Reloaded: First Place in Arabic Dialect Identification for the Second Year in a RowWorkshop on NLP for Similar Languages, Varieties and Dialects (VarDial)Andrei Butnaru, Radu Tudor Ionescu2018 · 39 citations
8. Improving the results of string kernels in sentiment analysis and Arabic dialect identification by adapting them to your test setConference on Empirical Methods in Natural Language Processing (EMNLP)Radu Tudor Ionescu, Andrei M. Butnaru2018 · 22 citations
9. FreSaDa: A French Satire Data Set for Cross-Domain Satire Detection ↗arXiv:2104.04828 · no summary yetRadu Tudor Ionescu, Adrian Gabriel Chifu2021 · 13 citations
10. FreCDo: A Large Corpus for French Cross-Domain Dialect Identification ↗arXiv:2212.07707 · no summary yetMihaela Gaman et al.2022 · 9 citations
11. UnibucKernel: Geolocating Swiss German Jodels Using Ensemble Learning ↗Proceedings of the Eighth Workshop on NLP for Similar Languages, Varieties and Dialects · no summary yetMihaela Găman, Sebastian Cojocariu, Radu Tudor Ionescu2021 · 3 citations
12. Combining Deep Learning and String Kernels for the Localization of Swiss German Tweets ↗Proceedings of the 7th Workshop on NLP for Similar Languages, Varieties and Dialects · no summary yetMihaela Gaman, Radu Tudor Ionescu2020 · 3 citations

🤝 Co-authors here

2 co-authors with a page, the most papers together first.

• Andrei Butnaru ×3
• Marius Popescu

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial) ×4: VarDial 2018, VarDial 2017
• IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings ×3
• International Conference on Computational Linguistics (COLING): COLING 2016
• Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2018
• Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

🔗 Cited by

Papers of our library cite their works 137 times (of the 149,439 papers whose bibliographies we read); 23 citing papers with a page here →.

Updated 1 November 2026

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