Staff profile

Affiliation | Room number | Telephone |
---|---|---|
Postgraduate Student in the Department of Computer Science | Mathematical Sciences and Computer Science Building |
Biography
I joined Durham University as a PhD student in Nov 2019. My research interests are Knowledge Representation Learning (KRL) and its application in different domains. I mainly aim to investigate how to enhance the representation learning ability of models and I have applied them in various tasks including medical vision question answering, natural language processing, financial investment, social network and structural learning of molecules. I demonstrated two modules: Bias in AI and AI Search for undergraduates in the Spring term 2022.
I am also a member of the Alan Turing Institute Knowledge Graph Interest Group and currently working on a UKRI project as research assistant, in charge of developing chatbot. If you are interested in collaboration in any capacity, do not hesitate to get in touch.
Research interests
- Machine Learning for Healthcare
- Multimodal Machine Learning
- Natural Language Processing
- Knowledge Representation
- Graph Neural Networks
Related Links
Esteem Indicators
- 2022: Talk at the Alan Turing Institute: Knowledge Graphs Interest Group at the Alan Turing Institute 5th Meet-up
Publications
Conference Paper
- Sun, Zhongtian, Harit, Anoushka, Cristea, Alexandra I., Yu, Jialin, Shi, Lei & Al Moubayed, Noura (2022), Contrastive Learning with Heterogeneous Graph Attention Networks on Short Text Classification, 2022 International Joint Conference on Neural Networks (IJCNN). Padova, Italy, IEEE.
- Sun, Zhongtian, Harit, Anoushka, Cristea, Alexandra I., Yu, Jialin, Moubayed, Noura Al & Shi, Lei (2022), Is Unimodal Bias Always Bad for Visual Question Answering? A Medical Domain Study with Dynamic Attention, 2022 IEEE International Conference on Big Data (Big Data). 5352.
- Sun, Zhongtian, Harit, Anoushka, Yu, Jialin, Cristea, Alexandra & Al Moubayed, Noura (2021), A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data, 2021 International Joint Conference on Neural Networks (IJCNN). Shenzhen, China, IEEE.