- Peking University, Data Science (computer vision), (Master degree), 2018-2021
- Wuhan University, Computer Science and Technology, (Bachelor degree), 2014-2018
- GPA: 3.83, Ranking: 1/38, CET-6: 571
Algorithm Engineer in AILab, ByteDance.Inc. (2021.7 - NAN)
- I am working on the application and research of large-scale language models(LLMs) in the commercial field, as well as the construction and evaluation of large-model systems. Which is primarily used for business scenarios such as advertising scripts, live broadcast copywriting, intelligent customer service or product titles generation, and more.
- Previously, I have worked on visual search system in video scenario, the system is widely applied in e-commerce products retrieval as well as advertisements recall and recommendation.
- Responsible for multi-modal research, as well as feature optimization and performance improvement of advertising systems.
Algorithm Engineer Intern in New Retail Intelligent Engine Business Group, Alibaba Group. (2020.6-2020.9)
- Mainly responsible for Object Matting, Advertising Image Generation, Video Understanding.
Winter Camp Intern in Google, China. (2020.1-2020.2)
- Completed an application that can transfer the human in a selfie into animation style and change the background at the same time. It mainly includes three modules: Human Matting, Face style translation and Background neural style transfer. It can synthesized the fine-grained animation human face into the style transferred background image to get a cartoonization photo.
- Completed a program which can achieve real-time character foreground matting and background style transfer in video stream on Intel-i5 CPU.
Research Intern in Medical AI Lab, Tencent. (2018.7-2019.7)
- Responsible for the research and development of the core module in the intelligent medical qualification examination system. The final model can score more than 390 points in the national medical qualification examination, which outperformed more than 70% of the human examinees.
- Researched the automatic generation of medical diagnostic reports for chest X-rays.
- Engeering Intern in Tencent Cloud. (2017.7-2017.9)
- Responsible for the Panshi system decoupling and reconstruction. Separated the system’s web access layer from its data access layer; completed the modification of related data interfaces.
- Developed and maintained the related functional plugins of the system.
- Exchange Student in Hong Kong Baptist University. (2017.5-2017.6)
- Researched on blockchain technology.
Yang Jin, Yongzhi Li, Zehuan Yuan, Yadong MU, “Embracing Consistency: A One-Stage Approach for Spatio-Temporal Video Grounding”, NeurIPS 2022[pdf]
Chenchen Liu, Yongzhi Li, Kangqi Ma, Duo Zhang, Peijun Bao, Yadong Mu,
“Learning 3-D Human Pose Estimation from Catadioptric Videos”, The 30th International Joint Conference on Artificial Intelligence (IJCAI) 2021.[pdf] [bibtex]
Yongzhi Li, Yadong Mu, Nan Zhuang, Xianglong Liu “Efficient Fine-Grained Visual-Text Search Using Adversarially-Learned Hash Codes”, IEEE International Conference on Multimedia and Expo (ICME) 2021. [pdf] [bibtex]
Yongzhi Li, Lu Chi, Guiyu Tian, Yadong Mu, Shen Ge, Zhi Qiao, Xian Wu, Wei Fan, “Spectrally-Enforced Global Receptive Field for Contextual Medical Image Segmentation and Classification”, IEEE International Conference on Multimedia and Expo (ICME) 2020. [pdf] [Bibtext]
Xinyu Weng†, Yongzhi Li†, Lu Chi, Yadong Mu, “High-Capacity Convolutional Video Steganography with Temporal Residual Modeling”, ACM International Conference on Multimedia Retrieval (ICMR) 2019. (Oral Presentation) [pdf] [Bibtext]
Most projects and introductions are shown in the project page
- Reviewer of CVPR 2023
- Reviewer of Neural Computing
- Familiar with Python, Java, Golang
- Proficient in using Pytorch, and familiar with TensorFlow.