Dame Kathleen Ollerenshaw Fellow (Assistant Professor/Lecturer) at the Computer Science Department of the University of Manchester in the United Kingdom. My fellowship project is on "AI for healthcare applications - Interpretable machine learning to uncover biological mechanisms". The main diseases to be studied include cancer, fetal growth limitation and heart diseases. My research interests are machine learning, deep learning, Bayesian learning, interpretable learning and bioinformatics. 

There are always positions available for talented and self-motivated Postdocs, PhDs, and visiting PhDs (check Here for more details). You are welcome to contact me if you are interested. 

Three available PhD positions are funded by the EPSRC Doctoral Training Partnership (DTP),  A*STAR PhD Programme and UKRI AI CDT in Decision Making for Complex Systems respectively. 

We are going to organize a workshop on “Computational & Experimental Spatial Omics” on Mon, 4 Mar 2024 at UoM. Welcome to join by then! The details can be found here.

2021.12 - 2023.04:

I was a postdoc research associate at Prof.Magnus Rattray's group - Division of Informatics, Imaging and Data Sciences at the Faculty of Biology, Medicine and Health of the University of Manchester. My research project was to develop machine learning algorithms to reveal biological mechanisms behind single-cell transcriptomics data. 

2018.09 - 2022.05:

Before the postdoc, I received my PhD degree at the Department of Cognitive Robotics of the Delft University of Technology in the Netherlands, supervised by Prof.Martijn Wisse and Dr.Wei Pan. My PhD work was developing Bayesian deep learning algorithms for neural network compression, neural architecture search, interpretable deep learning and system identification. Please check my PhD thesis "Bayesian deep learning for system identification".

2011.08 - 2017.07:

I received my Bachelor's and Master's degrees at the Department of Control Science and Engineering of Harbin Institute of Technology in China, supervised by Prof.Shen Yin.