About Me
Currently, I am a third-year Ph.D. student with the School of Computing at the University of Leeds, UK. It is also a joint Ph.D. program with the Dept. of Computer Science and Engineering at Southern University of Science and Technology (SUSTech), China. I received the B.Eng. degree in Computer Science and Engineering from SUSTech in 2020.
My current research interests are in the field of image classification, automated machine learning, and in particular evolutionary neural architecture search.
Recent News
- 07/21: Our paper titled “RelativeNAS: Relative Neural Architecture Search via Slow-Fast Learning” is accepted to IEEE T-NNLS!
- 05/21: Our paper titled “Efficient Evolutionary Neural Architecture Search by Modular Inheritable Crossover” is accepted to Elsevier SWEVO!
Honours and Rewards
- 2019: BIC-TA Best Paper Award
Education
University of Leeds
Doctor of Philosophy
October 2021 - future
I am a Ph.D. student at the University of Leeds, under the supervision of Dr. Nabi Omidvar and co-supervision at SUSTech.
The vision of my research may contain three parts: how to analyze the neural network, how to design the neural network, and how to deploy the neural network.
Firstly, I will use Information Theory and Feature Visualization to interpret the behaviour of the neural network or find the boundary of it.
Secondly, the knowledge we discover can be used as a prior to design the neural network.
Thirdly, we will extend the designed neural network into a search space and use Neural Architecture Search to further improve its performance, or for deployment purposes when considering multiple objectives.
What is more, my long-term goal is to design a general neural network that can process multi-modal information, such as texts and images, at the same time.
SUSTech
B.Eng. in Computer Science and Technology
September 2016 - July 2020
During my degree at SUSTech, I learnt lots of basic skills for research. For example, collecting and tracing papers are very important to dive into specific research areas. I also learnt how to use Numpy and PyTorch to start my project and realised my idea.
Experience
After my graduation, I continued to do the academic research for neural architecture search as a Research Assitant at SUSTech. During this one year, I submitted my papers into journals and handled the responses. At the same time, I was the key member and responsible for developing neural architecture search algorithms under two research giants.
Publications
Journals
- Hao Tan, Ran Cheng, Shihua Huang, Cheng He, Changxiao Qiu, Fan Yang, Ping Luo. RelativeNAS: Relative Neural Architecture Search via Slow-Fast Learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021. [ paper / code / bibtex]
- Cheng He, Hao Tan, Shihua Huang, Ran Cheng. Efficient Evolutionary Neural Architecture Search by Modular Inheritable Crossover. Swarm and Evolutionary Computation (SWEVO), 2021. [ paper ]
Conferences
- Hao Tan, Cheng He, Dexuan Tang, Ran Cheng. Efficient Evolutionary Neural Architecture Search by Modular Inheritable Crossover. International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA), 2019. ( Best Paper Award )