Dr. Xingjie Wei
- Position: Associate Professor in Business Analytics & Machine Learning
- Areas of expertise: Social computing, business analytics, social data mining
- Email: X.Wei1@leeds.ac.uk
- Phone: +44(0)113 343 4489
- Location: 1.15 Charles Thackrah
- Website: Personal website | Twitter | LinkedIn | Googlescholar | Researchgate | ORCID
Profile
Dr. Xingjie Wei is Associate Professor in Business Analytics and Machine Learning in the Centre for Decision Research (CDR) at Leeds University Business School. Xingjie’s research interests lie in the interaction between data science, and business and management to understand human behaviour through psychological experiments, big data analytics, and machine learning modelling. Her research develops quantitative models to describe and predict behavioural and psychological traits (e.g., personality) of humans from unstructured data (e.g., text, image), which can be applied to improve management practice in many fields such as marketing and finance. She is interested in applying cross-disciplinary techniques to discover hidden patterns within data and generate insights to guide governments, public sector organisations, and businesses to transform the way they work to make their services more cost-effective and easier to use.
Xingjie is particularly interested in:
- human traits understanding and identification: faces, expressions, personalities, intelligence, confidence…
- unstructured multi-media data mining: texts, images, EEGs…
- employing those computational techniques to improve business and management practices
Supervision
Xingjie is accepting PhD students and is interested in supervising topics related to the above areas using big data and machine learning techniques. Students are also welcome to propose their own topics and discuss them with Xingjie. Xingjie also welcomes visiting PhD students. Please send her an email with your CV and research statement for further discussion.
Grant
- 2025-2027, Academic advisor, Knowledge transfer partnerships(KTP) with SR Mailing, on the project of 'LLM-enhanced decision support system for the sustainable packaging', £338,916, Innovate UK.
- 05/2024-05/2026, Academic advisor, Knowledge transfer partnerships(KTP) with Katchr to develop, deploy and embed a bespoke business dashboard driven by complex AI and machine learning algorithms to enable tailored and customer-centric financial service provisions to the legal sector, £324,129, Innovate UK.
- 09/2023-09/2027, Primary supervisor, Collaborative Award, White Rose DTP, "Measuring life quality from digital footprints for informed policy decision making" to recruit a 4-year fully funded PhD student (international rates, equivalent to £150,166), ESRC
- 02/2022-06/2023, PI, "LINK: Climate change, social inequality & psychosocial wellbeing with emerging digital data - a multidisciplinary network between UK and South Korea", £45,758, ESRC
- 01/2022-08/2023, PI, "Predicting inequality from digital textual data", £21,467, LUBS Challenge Fund
- 02/2019-11/2020, PI, "Visual analytics on CEO profile images in initial coin offerings (ICO)", £2K, University of Leeds
- 02/2017-11/2017, PI, "Image pre-processing for automatic face recognition in forensics applications", £37.5K, Metropolitan Police Service
Responsibilities
- Departmental Director of Postgraduate Research (2025-)
- Head of Year for Bsc Business Analytics Programme (2018-2021)
- Facilitator for CDR Seminar Series (2021-2023)
Research interests
Social computing, business analytics, social data mining
Qualifications
- Ph.D. Computer Science, University of Warwick, UK
- Fellow of the Higher Education Academy (FHEA)
Professional memberships
- IEEE
- British Academy of Management
- Operational Research Society
Student education
Teaching:
LUBS1086 Exploring Your Potential (2018-19)
LUBS2940 Business Analytics 2 (2018-21)
LUBS3200 Business Analytics 3: Analytics Project (2018-19)
LUBS5990M Machine Learning in Practice (2019-presnet)
Research groups and institutes
- Centre for Decision Research