CV
Education
- Ph.D., Computer Science, Lancaster University, Lancaster, UK, 2020 -
- M.Sc., Data Science and Machine Learning, University College of London (UCL), London, UK, 2018 - 2019
- Merit
- Thesis title: Distinguish the transgenic mice and select the most important genes related to Alzheimer’s Disease.
- B.Eng., Electrical and Electronic Engineering, University of Manchester, Manchester, UK, 2016 - 2018
- First Class
- Thesis title: Unobtrusive foot printing with “light under your carpet”.
- B.Eng., Electrical and Electronic Engineering, North China Electrical Power University (NCEPU), Beijing, China, 2014 - 2016
- The Second Prize Scholarship
- GPA: 3.52/4.0
Work experience
- Opera Software (Beijing,China), Oct.- Dec.2019
- Department: Recommend System of Opera News
- Role: Algorithm Engineer
- Duties included: Build the Transfer model which is based on attention algorithm for the news recommend system.
Programs
- Determine whether mice carry human genes and predict mouse gene expression, Jun.-Sep. 2019
- Use PCA technology to reduce the dimensionality of data and select the most important feature information
- Use python to build SVM model to classify mouse gene expression and determine whether mice are injected with human genes. Predicting the performance of 12- month-old mice by 3-month-old mouse gene expression.
- Generate ancient poems using the Transformer model, Mar.- Jun. 2019
- Use PyTorch to build a Transformer model to generate Chinese poems.
- Unobtrusive foot printing with ’light under your carpet’ Identify gait with artificial intelligence network, Oct.2017- May. 2016
- Use MATLAB to build a Neural Network model,record the pressure value of the person passing the sensor carpet, and then divide the length of each step, and then use the ANN model to classify the speed of each step.
Skills
