Zhaoji Wang (王兆基)

Hi! I'm Zhaoji Wang, a PhD candidate in Information Science at the Department of Information Management, Peking University, and also affiliated with the Research Center for Digital Humanities, Peking University (PKUDH) under the supervision of Prof. Jun Wang since 2024. I am a member of the "Peking University-ByteDance Digital Humanities Open Lab" within the Institute for Artificial Intelligence, Peking University. My research focuses on Digital Humanities, Ancient Chinese Information Processing, and Computational Linguistics. I have participated in several significant research projects, including those funded by the National Natural Science Foundation, National Social Science Foundation, and Beijing Social Science Foundation.

I am responsible for the research and development of multiple digital humanities infrastructure projects, such as the "Wu Yu Dian" Intelligent Annotation Platform at Peking University and the "Tongjiazi Online Resource Library" at Beijing Normal University. Additionally, I am responsible for the development of the "Jing Ji Zhi Zhang" Chinese Historical Bibliography Analysis System at Peking University. I was honored with the Best Paper Award at CCL 2023.

Previously, I worked under the tutelage of Assoc. Prof. Renfen Hu as a Master's student in Linguistics and Applied Linguistics at Beijing Normal University, where I earned my Master of Arts degree, focusing on Chinese Information Processing, Computational Linguistics, and Digital Humanities.

Before that, I worked with Prof. Min Zhu at Sichuan University's Visual Computing Laboratory (SCUVIS), delving into Data Visualization. In 2021, I graduated from Sichuan University with dual degrees in Chinese Language & Literature (B.A.) and Computer Science & Technology (B.E.), studying at the esteemed Wu Yuzhang Honors College. This multidisciplinary education has equipped me with unique insights, bridging the worlds of technology and literature.

Since March 2023, I have been serving as Co-Founder and Lead Engineer at Jinghong Software, a leading AI startup in China. Our company specializes in developing innovative AI-driven applications and customized solutions for both B2C and B2B markets. We've successfully launched popular WeChat and Douyin Mini Programs centered around AI conversational capabilities, such as "Wenzhi AI" and "Chat Treasure". Our expertise extends to providing tailored AI solutions for government and enterprise clients, including dialogue platforms, knowledge-enhanced Q&A systems, and data annotation systems. At Jinghong Software, I lead the entire technology stack, from frontend and backend development to large language model engineering. I've spearheaded the development of our proprietary data annotation platform, advanced large model training framework, and multiple successful end-user applications. Among our diverse projects, we've developed FastPassAI, a website that leverages large language models to help students efficiently prepare for various English exams. Our company's unique "trinity" technical ecosystem encompasses data generation and processing, large model training and optimization, and end-application implementation, enabling us to deliver comprehensive AI solutions across various domains.

Feel free to reach out to me at zhaojiwang[at]stu.pku.edu.cn.

Visit my LinkedIn profile: Zhaoji Wang | Linkedln

Visit my blog: One Zhaoji | The place where Zhaoji Wang writes

Visit my Github profile: frederick-wang (Irisjiel)

Visit my lab personal homepage: Zhaoji Wang | Research Center for Digital Humanities of Peking University

Publications

1

Zhaoji Wang, Shirui Zhang, Renfen Hu, et al. 2024. 古汉语通假字资源库的构建及应用研究 (Ancient Chinese Language Resource on Tongjiazi: Construction and Application) [J]. 中文信息学报 (Journal of Chinese Information Processing), 38(03):152-162.

CCL 2023 Best Paper Core Journal CCF T1 Journal PDF Website Github

2

Wenqi Li, Zhaoji Wang, Hanxu Yu, Qianting Lai, Jun Wang. 2024. Book cluster: a new approach to explore the evolution of knowledge organization in ancient China [J]. Digital Scholarship in the Humanities, fqae055.

SSCI Journal PDF

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