Professor Constantin Orasan
Academic and research departmentsSchool of Literature and Languages, Centre for Translation Studies.
I am Professor of Language and Translation Technologies at the Centre of Translation Studies, University of Surrey. Before starting this role, I was Reader in Computational Linguistics at the University of Wolverhampton, UK, and the deputy head of the Research Group in Computational Linguistics at the same university. I have received my BSc in computer science at Babeș-Bolyai University, Cluj-Napoca, Romania and was awarded my PhD from the University of Wolverhampton.
I have over 20 years experience of working in the fields of (applied) Natural Language Processing (NLP), Artificial Intelligence and Machine Learning for language processing. My research interests are largely focused on facilitating information access and include translation technology, sentiment analysis, question answering, text summarisation, anaphora and coreference resolution, building, annotation and exploitation of corpora.
I recently coordinated the EXPERT project, an extremely successful Initial Training Network (ITN) funded under the People Programme of the Seventh Framework Programme (FP7) of the European Community which trained the next generation of world-class researchers in the field of data-driven translation technology. In addition to coordinating this project between nine partners across both academia and industry, I was actively involved in the training of the Early Stage Researchers (ESRs) appointed in the project and, in collaboration with these ESRs, I carried out research on translation memories and quality estimation for machine translation. I continue researching these topics.
I was also the deputy coordinator of the FIRST project, a project which developed language technologies for making texts more accessible to people with autism. In addition to managing a consortium of nine partners from academia, industry and heath care organisations, I also carried out research on text simplification and contributed to the development of a powerful editor which can be used by carers of people with autism to make texts more accessible for these people.
In the past In the past, I was the Local Course Coordinator of the Erasmus Mundus programme on Technology for Translation and Interpretation and the Erasmus Mundus International Masters in Natural Language Processing and Human Language Technology, and the scientist in charge for the University of Wolverhampton in two European projects QALL-ME and MESSAGE. I also worked as a research fellow on the CAST project.
I love programming and in my spare time I contribute to some open source projects and have my own GitHub repository.
Areas of specialism
Postgraduate research supervision
Second supervisor of Alistair Plum’s PhD thesis on Wikipedia-based Approaches to Multi-Lingual Information Extraction (expected submission date autumn 2022)
Second supervisor of Hadeel Saadany's PhD thesis entitled A Study of the Transfer of Sentiment by Neural Machine Translation Systems (expected submission date autumn 2022)
First supervisor of Eleanor Taylor-Stilgoe's PhD Thesis on Towards Better Healthcare Communications: Assessing Quality in Medical Translation (expected submission date autumn 2024)
First supervisor of Gökhan Firat's PhD thesis on Collaborative and Cooperative Translation on Digital Platforms (expected submission date winter 2024)
Second supervisor of Maria Andreea Deleanu's PhD thesis entitled (Narrative) E2U Audio Cues for neurodiverse end-users (expected submission date autumn 2024)
First supervisor of Shenbin Qian's PhD thesis on Sentiment Preservation in Neural Machine Translation (expected submission date early 2025)
Completed postgraduate research projects I have supervised
- Second supervisor of Tharindu Ranasinghe’ PhD thesis on Deep learning based semantic textual similarity for applications in translation technology, University of Wolverhampton, UK, 2021 (pdf)
- Second supervisor of Reshmi Gopalakrishna Pillai’s PhD thesis on Expressions of psychological stress on Twitter: detection and characterisation, University of Wolverhampton, UK, 2021 (pdf)
- First supervisor of Richard Evans' PhD thesis entitled Sentence simplification for text processing, University of Wolverhampton, UK, 2020
- First supervisor of Hanna Bechara' PhD thesis entitled A Semantic Textual Similarity Enhanced Quality Estimation Method and its Applications to Natural Language Processing Task, University of Wolverhampton, UK, 2020
- First supervisor of Rohit Gupta's PhD thesis on Use of language technology to improve matching and retrieval in translation memories, University of Wolverhampton, UK, 2016
- Second supervisor of Sanja Stajner's PhD thesis on New Data-Driven Approaches to Text Simplification, University of Wolverhampton, 2015 (pdf)
- Second supervisor of Natalia Konstantinova's PhD thesis on Knowledge acquisition from user reviews for Interactive Question Answering, University of Wolverhampton, UK, 2013 (pdf)
- First supervisor of Iustin Dornescu's PhD thesis on Encyclopedic question answering, University of Wolverhampton, UK, 2012 (pdf)
- Second supervisor of Georgiana Marsic's PhD thesis on Temporal Processing of News: Annotation of Temporal Expressions, Verbal Events and Temporal Relations, University of Wolverhampton, UK, 2011 (pdf)
Second supervisor of Laura Hasler's PhD thesis entitled From extracts to abstracts: Human summary production operations for computer-aided summarisation, University of Wolverhampton, UK, 2007 (pdf)
MODULES TAUGHT THIS ACADEMIC YEAR
- TRAM500: Introduction to computational thinking for translators (module leader)
- The purpose of this module is to enable students to acquire basic and intermediate concepts of computer science and programming, and to learn how to apply them to problems related to translation-related tasks such as glossary creation, error analysis, automatic substitution. The programming language used in the class is Python.
- TRAM502: Smart technologies for translators (module leader)
- The module explores the main theoretical and practical aspects of smart technologies for translation, with emphasis on how to use methods from Natural Language Processing and Corpus Linguistics to help translators. The purpose of this module is to enable students to understand the challenges faced when using computers to process text automatically or when they need to process speech as an input.
- TRAM449: Interpreting and technologies
- This module introduces students to the principles and practical implications of using technologies in the interpreting profession. In this module, I contributed with lectures on machine translation and speech to speech translation.
- TRAM495: Principles and challenges of translation and interpreting
- This module provides students with a systematic framework for understanding the key concepts in Translation and Interpreting Studies and how they relate and apply to everyday professional practice. In this module, I contributed with lectures on human-computer interaction for translators and interpreters and quality in translation.