I am an applied linguist, discourse researcher and university educator based in Valencia, Spain. I am completing a PhD in applied linguistics at the Polytechnic University of Valencia (UPV). My dissertation has been approved for defence, scheduled for late October 2026.
My research centres on conflict in digital discourse, particularly its more hostile forms: aggression, incivility, gendered delegitimisation and multimodal hostility. I am interested not only in what people say, but also in how linguistic choices, images, interactional patterns and platform conditions make particular forms of judgement and exclusion possible.
I came to applied linguistics through more than twenty years of language teaching, assessment and course development. During that time, I worked with learners at different levels and in different educational contexts, including examination preparation, academic communication and university teaching.
Teaching made me increasingly interested in the gap between what speakers intend, what language communicates and how meaning is interpreted by others. It also drew my attention to evaluation: how people express approval and disapproval, assign responsibility, construct authority and turn disagreement into personal judgement.
What began as an interest in verbal interaction expanded into the study of gender, multimodality, visual hostility and the wider conditions under which aggressive discourse circulates online.
My work examines how conflict is organised through discourse rather than treating hostility as a collection of isolated offensive words.
I study recurring patterns of evaluation, impoliteness and delegitimisation in social-media discourse, particularly in communication directed at women in public and political life. This includes the ways in which public figures are represented as incompetent, dishonest, abnormal, illegitimate or out of place.
My research also considers multimodal communication. Images, memes and visual framing do not simply illustrate verbal messages; they can intensify judgement, introduce meanings that are not stated directly and construct forms of symbolic punishment or exclusion.
Critical Discourse Analysis and Feminist Critical Discourse Analysis provide an important part of this perspective. They allow me to connect individual linguistic and visual choices with broader questions of power, ideology, gender and social legitimacy.
My research is primarily corpus-based. I work with purpose-built collections of social-media posts, replies, comments and multimodal material, using both qualitative discourse analysis and quantitative methods.
Depending on the project, my work may involve:
I am particularly interested in methodological transparency. Categories used in discourse research often involve interpretation, and interpretation should not be disguised as mechanical certainty. For this reason, I pay close attention to annotation guidelines, disagreement between coders, reliability measures and the evidence required to justify analytical claims.
Artificial intelligence has become a second major strand of my work.
One part concerns the use and methodological validation of AI in linguistic research. Large language models can assist with corpus design, classification and exploratory analysis, but their outputs cannot be treated as automatically valid. I am interested in how human expertise and AI-assisted procedures can be combined, how model performance should be evaluated and where automated analysis introduces bias, inconsistency or false confidence.
A second part concerns algorithmic and AI-mediated social-media discourse. Generative content, recommender systems, automated moderation and synthetic participation increasingly affect what is produced, what becomes visible and which forms of discourse are amplified or suppressed.
I also study generative AI in language education and university teaching. Students will use these systems regardless of whether institutions attempt to prohibit them. The more useful question is therefore how teaching, feedback and assessment should be redesigned so that AI supports learning without replacing critical judgement, responsibility or independent intellectual work.
My teaching is based on clear task design, transparent expectations and feedback that students can act on.
I favour communicative and task-based learning, but I do not treat communication as an alternative to accuracy, structure or explicit instruction. Students work more effectively when complex tasks are broken into manageable stages, criteria are made visible in advance and feedback identifies a concrete next step.
My experience as a Cambridge speaking examiner has also influenced how I approach assessment. It has reinforced the importance of distinguishing evidence-based evaluation from general impressions and of making performance criteria understandable to students before they are assessed.
A fuller account of my teaching approach is available on the Teaching page. Teaching experience and statement →