Dr Xiang Li

Teaching Fellow in Digital Finance


Xiang is a Teaching Fellow within the Institute for Digital Technologies.

Xiang's primary research fields are financial technologies (FinTech), machine learning, banking, and systemic risk. Xiang is passionate about research and welcomes research collaborations in the relevant fields.

Xiang joined the Institute for Digital Technologies as a teaching fellow in February 2021, directly after her PhD in Finance at Loughborough University. Xiang teaches at the postgraduate level and supervises both MSc dissertations and collaborative projects. Xiang's current teaching modules include:

LLP130: Financial Technologies
LLP132: Foundations of AI and Data Analytics
LLP133: Advanced Programming and Visualisation
LLP104: Statistical Methods in Finance
LLP121: Principles of Data Science
LLP122: Advanced Big Data Analytics

Academic background

Xiang holds a PhD in Finance from Loughborough University, where she also worked as a four-year teaching assistant. Xiang also studied an MSc in Finance and Management at Cranfield University.

Prior to her appointment at Loughborough University London, Xiang worked at the University of Bristol as a research assistant on a Mergers & Acquisitions (M&A) research project.

Current research and collaborations

Xiang's current research focuses on FinTech and Machine Learning, e.g., financial networks for systemic risk and machine learning for asset pricing.

Xiang's research in Finance focuses on bank lending and its intersections across four research areas: insider trading, debt covenant violations, loan contracting and renegotiation, and financial derivatives (e.g., CDS, CLO).

Research expertise

  • Financial Technologies (FinTech) and Machine Learning
  • Systemic Risk in Financial Networks
  • Asset Pricing with Machine Learning
  • Banking: Loan Contracting, Covenant Violations, Loan Renegotiation
  • Financial Derivatives
  • Insider Trading
  • M&A

Interests and activities

Publications database