About
I am an autonomous driving algorithm engineer at NIO, primarily responsible for the research and development of
data loopback (DLB), AI algorithm engineering (AI Infra), and high-performance computing (HPC) etc.
In addition, I am a co-founder of Tsingpe Intelligence Inc., a start-up founded by alumni of Tsinghua University and Peking University.
Within this AI+CAX focused company, I serve as Director of Product and R&D, overseeing the engineering and practical deployment of AI algorithms.
Prior to this, I obtained my Bachelor’s degree in Electronic Engineering (EE) from Ocean University of China in 2020,
followed by a Master’s degree in Computer Science (CS) in 2023.
Research
My work centres on areas such as deep neural network compression, LLM knowledge distillation, high-performance computing and operators,
efficient inference, AI infra, and CUDA development.
I am also engaged in the design and optimisation of autonomous-driving-oriented algorithms, such as World Models.
Publications
- X Liu, LN Wang, W Liu, G Zhong "Incremental layers resection: a novel method to compress neural networks", IEEE Access 2019. [PDF]
- X Zhang, H Zeng, X Liu, Z Yu, H Zheng, B Zheng “In situ holothurian noncontact counting system: A general framework for holothurian counting”, IEEE Access 2020. [PDF]
- G Zhong, W Liu, H Yao, T Li, J Sun, X Liu “Merging similar neurons for deep networks compression”, Cognitive Computation 2020. [PDF]
- LN Wang, W Liu, X Liu, G Zhong, PP Roy, J Dong, K Huang “Compressing deep networks by neuron agglomerative clustering”, Sensors 2020. [PDF]
- X Liu, W Liu, LN Wang, G Zhong “Deep architecture compression with automatic clustering of similar neurons”, PRCV 2021. [PDF]
- Z Ding, X Liu, G Zhong, D Wang “Steelygan: semantic unsupervised symbolic music genre transfer”, PRCV 2022. [PDF]
- 刘翔，祝静，仲国强，顾永健 等 "量子原型聚类", 计算机科学 2023. [DOI]
Contact
Email: ailven.x.liu@gmail.com