
Dr. Xingjie Wei
- Position: Associate Professor in Business Analytics & Machine Learning
- Areas of expertise: Business Analytics, Unstructured Data Mining, Social Computing, Human Trait, Multimodal Data, Financial Risk Analytics, Initial Coin Offering
- Email: X.Wei1@leeds.ac.uk
- Phone: +44(0)113 343 4489
- Location: 1.15 Charles Thackrah
- Website: Personal website | BuleSky | 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 intersection of data science and business management, focusing on understanding human behaviour through psychological experiments, big data analytics, and machine learning modelling. Xingjie’s work develops algorithms that identify human traits and characteristics from various forms of unstructured data—decoding identity and emotions from images, extracting personality patterns from text, and detecting behavioural signals from digital footprints. These approaches generate human-centred insights that drive better decisions and outcomes, ultimately guiding governments, public sector organisations, and businesses to transform their operations and make their services more cost-effective and user-friendly.
Xingjie is particularly interested in:
- Understanding and identifying human traits from unstructured data: faces, expressions, personalities, intelligence, confidence...
- Multimodal data mining techniques
- 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
Business Analytics, Unstructured Data Mining, Social Computing, Human Trait, Multimodal Data, Financial Risk Analytics, Initial Coin Offering
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-)
Research groups and institutes
- Centre for Decision Research