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Natural Language Processing for Business Intelligence

For over a decade, the Intelligent Data Analysis Research Group has been working in an extensive area of artificial intelligence and data science. Recent projects include medical imaging, bioimaging, biometrics, natural language processing, semantic video analysis, pattern recognition and computer graphics. We have received numerous research awards from international conferences, research institutions and professional organisations.

We invite talented and hard-working candidates to join us for their PhD study.

Business operations involve a large amount of data from their internal communications, presentations, reports, accounting and marketing, and external information from governments, industry sectors, customers, suppliers, competitors etc. These data are often available in unstructured or semi-structured formats, and therefore make data analytics a challenging task.

This project is aimed to develop novel methods using modern natural language processing (NLP) technologies to support decision making for both business operations and strategic planning. You will focus one or more of the following tasks in the project: sentiment analysis, chatbots for customer service or business data analytics, tagging and text classification, text extraction and document summarisation, personalised marketing, customer profiling and market intelligence.

How to apply

If you are interested in applying for the above PhD topic please follow the steps below:

  1. Contact the supervisor by email or phone to discuss your interest and find out if you would be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
  2. Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
  3. Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.

Good luck!

This is a self funded topic

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.

Meet the Supervisor(s)

Yongmin Li - Please visit my personal website where you may find more details of my work. Dr. Yongmin Li received his PhD from Queen Mary, University of London, MEng and BEng from Tsinghua University, China. Before joining Brunel University, he worked as a research scientist in the British Telecom Laboratories. Dr. Li is a Senior Member of the IEEE, and Senior Fellow of the Higher Education Academy. He was ranked in the world's top 2% scientists by the Standardized Citation Indicators (Elsevier) every year over the past four years ( 202020212022, and 2023). His research interest covers the areas of data science, machine learning, artificial intelligence, image processing, computer vision, video analysis, medical imaging, bio-imaging, biomedical engineering, healthcare technologies, automatic control and nonlinear filtering. Together with his colleagues, their work has won the following awards:
  • 1st Place, RETOUCH Challenge (Online), MICCAI 2023 (with Ndipenoch, Miron and Wang).
  • 2nd Place, FeTA Challenge, MICCAI 2022 (with McConnell, Ndipenoch and Miron).
  • Most Influential Paper over the Decade Award, MVA, 2019 (with Ruta, Porikli, et al).
  • Best Student Paper Award, Bioimaging, 2018 (with Dodo, Eltayef and Liu).
  • VC Prize, Brunel University, 2015 (with Kaba and Liu).
  • Best Paper Award, HIS, 2012 (with Salazar-Gonzalez and Kaba).
  • Best Poster Prize, BMVC, 2007 (with Ruta and Liu).
  • Best Scientific Paper Award, BMVC, 2001 (with Gong and Liddell).
  • Best Paper Prize, RATFG, 2001 (with Gong and Liddell).
Prospective PhD Students: We invite talented and hard-working students to join us for their PhD study. From time to time, we may have studentships available, which include an annual bursary (about £18,000 this year) plus payment of tuition fees for three years. Currently we have several projects on-going, for example, Deep Learning for Medical Imaging, Natural Language Processing for Business Intelligence, Natural Language Processing for Tax Assessment, and Image/Video Content Generation for Personalised Remarketing. But any other topics within the area of artificial intelligence and data science would also be welcome.  Contact me for details if interested. Master of Science in Artificial Intelligence 2023/24: Built on our strong international research profile (consistently ranked in the top 100 in the world, 1st in UK for H-index and Highly Cited Papers for 3 years in a row from 2018-2020, and 3rd in UK for overall performance in "the NTU Performance Ranking of Scientific Papers for World Universities", Subject: Computer Science, 2020),  we offer the MSc Artificial Intelligence course with great flexibility (1 year full-time, 2 year part-time or 3 year staged study). If you are interested, apply here. 15 Scholarships available for applicants from under-represented groups, £10,000 of each. Research & Development Collaboration: Developing downstream applications of large AI models is a focused area of my group in the upcoming years. Contact me if you have a collaboration project. We can assist in securing funding from sources like UKRI, EU, or Innovate UK, potentially cutting your costs in the project significantly (e.g. by 1/3 or more), plus the university's input.

Related Research Group(s)

Intelligent Data Analysis

Intelligent Data Analysis - Concerned with effective analysis of data involving artificial intelligence, dynamic systems, image and signal processing, optimisation, pattern recognition, statistics and visualisation.