Supervision Opportunities

Why consider supervision with me?

A doctoral degree is not simply a period of study; it is a period of professional development. The right supervisory environment should help you develop as a researcher, programmer, analyst, and academic writer. My aim is to provide supervision that is intellectually ambitious, practically grounded, and supportive throughout your research journey.

Areas I am interested in supervising

I am open to supervising projects in a range of related areas, especially where there is a clear computational component and a well-defined research problem. These include, but are not limited to:

• Natural language processing
• Authorship analysis and forensic linguistics
• Corpus linguistics and computational stylistics
• Large language models and AI-generated text analysis
• Educational applications of AI and NLP
• Text classification, pattern analysis, and language data mining
• Human-centred or explainable approaches to language technology

Example PhD topic areas

Applicants are welcome to propose their own topic. The examples below are intended only to illustrate the kinds of projects that would be a good fit.

• Cross-modal authorship attribution using written and spoken language data
• Detection and analysis of AI-generated text in high-stakes settings
• Large-scale modelling of authorial style and idiolect
• NLP tools for language learning, assessment, or feedback
• Explainable AI for text analysis and decision support
• Computational approaches to forensic interview or legal-language data
• Corpus-driven methods for identifying linguistic patterns in specialised domains

My supervision approach

Different students thrive under different supervisory styles. My own approach combines high expectations with sustained support.

• Regular meetings with clear goals and follow-up actions
• Emphasis on building a coherent and feasible research plan early on
• Support for both technical work and academic writing
• Encouragement to publish, present, and develop a visible research profile
• Constructive feedback that is direct, practical, and aimed at steady improvement
• Encouragement of independent thinking, originality, and ownership of the project

I particularly value students who are curious, self-motivated, and willing to engage seriously with both theory and implementation. I expect all students to show grit.

What you may gain from working with me

• Experience working on authorship teams at all stages of the publication journey from brainstorming to proofing the final camera-ready copy
• Hands-on experience designing and building computational tools, and releasing production-ready versions
• Deeper expertise in NLP, text analysis, and language-focused AI
• Guidance on presenting research, academic writing, reviewing, and dissemination
• A stronger research portfolio for academic or industry careers
• Experience working on real-world problems with both scientific and applied value

Who is likely to be a strong fit?

I am especially keen to hear from applicants who have a strong background in computer science and a genuine interest in language-related research.

• Strong programming ability, especially in Python or related languages
• Interest in NLP, machine learning, text analysis, or AI systems
• Willingness to work carefully with data, methods, and evaluation
• Ability to sustain a long-term research project
• Good written communication and academic seriousness

Prior experience in natural language processing is highly desirable, but strong applicants from other computational backgrounds may also be a good fit.

Student perspectives

"No matter on campus or remote, we can work closely to push forward our research. Your support from idea to publication gradually gives me a more open attitude towards new ideas, better practical skills in performing more independent work, as well as stronger confidence and willingness to publish and demonstrate my output, which broadens my future possibilities."

"What you taught me about the importance of 'grit' really stayed with me. It gave me the strength to keep going during difficult times and helped me complete my thesis."

"You let me try things my own way and were always considerate of my schedule. Meetings felt relaxed, so it was easy to talk things through."

"You've been incredibly supportive throughout my time here."

"Thank you so much for your lectures over the past two months. I really enjoyed them and learned a lot."

Frequently asked questions

Informal application process

I aim to keep the initial process straightforward and approachable. If you think your interests may align with mine, you are very welcome to make an informal enquiry.

Please send the following by email:

• A short statement of interest (around one or two paragraphs)
• Your CV
• An academic transcript, if available
• A brief outline of a possible topic or problem you would like to explore, written by you, not an LLM

In your email, briefly explain:

• your academic background,
• your programming or research experience,
• your area of interest, and
• whether you are seeking a funded opportunity, self-funded study, or exploratory discussion. Students selecting self-funded study will be prioritised in the application process.

Informal enquiries are welcome, and an initial message does not need to be polished or overly formal.