Meriem BELOUCIF مريم بلوصيف
Postdoctoral ResearcherInformatics Department
beloucif (at) informatik (dot) uni-hamburg (dot) de
I am a postdoctoral researcher at Hamburg University, working on Comparative Question Answering at the LT group under the supervision of Prof. Chris Biemann. Before that, I spent one year at the University of Copenhagen under the supervision of Professor Anders Søgaard. Before joining the CoAStaL group in Copenhagen, I obtained a Doctor of Philosophy (PhD) degree at the Department of Computer Science and Engineering in Hong Kong University of Science and Technology (HKUST) under the supervision of Professor Dekai Wu. I did a Master degree in Software Engineering and a Bachelor degree in Academic Computer Science at the Department of Computer Science, University of Science and Technology Houari Boumedienne, Algiers, Algeria.
My current research focus now is on neural machine translation with a particle focus on using reinforcement learning for NMT. However, I am passionate about NLP in general and thus collaborating on multiple projects like semantic role labelling and fact checking. Please feel free to check my curriculum vitae and my Google Scholar.
Question Answering, Neural Machine Translation, Co-reference NMT, Semantic parsing, Statistical Machine Translation, Word Alignment, Semantic Role Labeling, SMT for Low Resource Languages, Fact checking, Quality Estimation, Natural Language Processing, Machine Learning.
Study and implementation of a face authentification and recognition system based on the fusion of Principal Components Analysis (PCA) and Linear Discriminant Analysis (LDA) scores.
- Design and implementation of an information system for hardware monitoring for NAFTAL Algeria.
Grants and Awards
- Meriem BELOUCIF, Ana Valeria Gonzalez, Marcel Bollmann and Soegaard Anders. Naive regularizers for low-resource neural machine translation. Recent Advances in Natural Language Processing 2019. Borovets, Bulgaria.
- Meriem BELOUCIF and Dekai WU. SRL for low resource languages isn't needed for semantic SMT. 21st Annual Conference of the European Association for Machine Translation (EAMT 2018). Alicante: May 2018.
- Meriem BELOUCIF and Dekai WU. Injecting a Semantic Objective Function into Early Stage Learning of Spoken Language Translation. Sixth IEEE Workshop on Spoken Language Technology (SLT 2016). San Diego: Dec 2016.
- Meriem BELOUCIF, Markus SAERS and Dekai WU. Improving word alignment for low resource languages using English monolingual SRL. Sixth Workshop on Hybrid Approaches to Translation (HyTra-6). Osaka, Japan: Dec 2016.
- Meriem BELOUCIF and Dekai WU. Injecting a Semantic Objective Function into Early Stage Learning of Spoken Language Translation. Oriental COCOSDA 2016, 19th International Conference of the Oriental Chapter of the International Committee for the Co-ordination and Standardization of Speech Databases and Assessment Techniques (O-COCOSDA 2016). Bali, Indonesia: Oct 2016.
- Meriem BELOUCIF and Dekai WU. Driving inversion transduction grammar induction with semantic evaluation. 5th Joint Conference on Lexical and Computational Semantics (*SEM 2016), at ACL 2016, 55-63. Berlin: Aug 2016.
- Meriem BELOUCIF and Dekai WU. A semantically confidence-weighted ITG induction algorithm. 3rd International Workshop on Semantic Machine Learning (SML 2016), at IJCAI 2016. New York: Jul 2016.
- Meriem BELOUCIF, Markus SAERS, and Dekai WU. Improving Semantic SMT via Soft Semantic Role Label Constraints on ITG Alignments . Machine Translation Summit XV, Miami, Florida: Oct 2015.
- Meriem BELOUCIF, Chi-kiu LO, and Dekai WU. Improving MEANT Based Semantically Tuned SMT. 11th International Workshop on Spoken Language Translation (IWSLT 2014), 34-41. Lake Tahoe, California: Dec 2014.
- Dekai WU, Chi-kiu LO, Meriem BELOUCIF and Markus SAERS. Better Semantic Frame Based MT Evaluation via Inversion Transduction Grammars. Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation (at EMNLP 2014), 22-33. Doha: Oct 2014.
- Chi-kiu LO, Meriem BELOUCIF, Markus SAERS, and Dekai WU. XMEANT: Better semantic MT evaluation without reference translations. 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014), 765-771. Baltimore, Maryland: Jun 2014.
- Chi-kiu LO,Meriem BELOUCIF, and Dekai WU. "Improving machine translation into Chinese by tuning against Chinese MEANT". 10th International Workshop on Spoken Language Translation (IWSLT 2013). Heidelberg, Germany: Dec 2013.
- Dekai WU, Karteek ADDANKI, Markus SAERS, and Meriem BELOUCIF. Learning to Freestyle: Hip Hop Challenge-Response Induction via Transduction Rule Segmentation. 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), 102-112. Seattle: Oct 2013.