Lecturer in Probability & Statistics

Lingyi Yang

  • I studied for a DPhil at Oxford in Industrially Focused Mathematical Modelling on the topic of optimising arrival management in air traffic control.
  • Currently, I am a post-doctoral researcher at the Mathematical Institute working doing research on the intersection of applied rough paths and neural networks, in particular looking at anomaly detection on time series, and differential equation-inspired neural networks.
  • Since 2018, I have been involved with undergrad teaching in Oxford, first at the Mathematical Institute, then later in colleges. The tutorial system at Oxford is great for engaging with students and tailoring classes to individuals.
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Teaching

At Trinity, I teach the first and second year modules for probability and statistics. I have also tutored follow-on third year courses as well as modules for the MSc in Mathematical and Computational Finance at the department.

Research

My research interests include anomaly detection, embedding, reinforcement learning & control, and applications of signatures in machine learning. I have been involved in a range of projects involving sequential data problems using path signatures (from rough analysis) and neural controlled differential equations. These include early detection of sepsis, deterioration in patients with COVID-19, as well as economic nowcasting.

Subjects
Mathematics
Lingyi Yang
lingyi.yang@maths.ox.ac.uk

As mathematicians we can take our toolbox and create new insight in many applications. Mathematics is both beautiful and relevant in today’s world.

Oxford Mathematical Institute Profile