教學(xué)和研究領(lǐng)域
教學(xué)課程:人工智能與經(jīng)管研究(碩博研究生),人工智能(本科,計劃開設(shè))
研究領(lǐng)域:從事機器學(xué)習(xí)算法及信息系統(tǒng)設(shè)計科學(xué)相關(guān)研究,具體關(guān)注個性化推薦系統(tǒng)、大語言模型、可信人工智能等領(lǐng)域
學(xué)術(shù)經(jīng)歷
2025年7月-至今 特聘副研究員,管理科學(xué)與工程系,武漢大學(xué)
2022年11月-2023年6月 訪問學(xué)者,金融服務(wù)分析研究院,美國特拉華大學(xué)
企業(yè)實踐經(jīng)歷
2025年7月-至今 顧問,大模型相關(guān)項目,美團
獲獎與榮譽
國際信息系統(tǒng)年會(ICIS)Best Student Paper Nominee,2024
編審經(jīng)歷
期刊:Information & Management,Scientific Data
會議:ICIS,PACIS,WITS,ICDM,PAKDD
主要論文及書籍
國際期刊論文
Shangkun Che, Hongyan Liu*, and Shen Liu (2024). Tagging Items with Emerging Tags: A Neural Topic Model based Few-Shot Learning Approach. ACM Transactions on Information Systems (TOIS).
Xiao Fang*, Shangkun Che*, Minjia Mao, Hongzhe Zhang, Ming Zhao, and Xiaohang Zhao (2024). Bias of AI-generated content: an examination of news produced by large language models. Scientific Reports. (ESI高被引論文)
Yi Bu, Binglu Wang, Win-Bin Huang*, Shangkun Che, Yong Huang (2018). Using the appearance of citations in full text on author co-citation analysis. Scientometrics.國內(nèi)期刊論文
韓雪雯,車尚錕,楊夢晴*,王能 (2024). 多模態(tài)數(shù)據(jù)驅(qū)動的AI智能體模式設(shè)計. 圖書情報工作
王瀟, 劉紅巖*, 車尚錕 (2021). 一種基于深度強化學(xué)習(xí)的直播推薦方法. 信息系統(tǒng)學(xué)報
王越千, 黃文彬, 步一*, 車尚錕 (2021). 學(xué)術(shù)論文子句語義類型自動標(biāo)注技術(shù)研究. 情報學(xué)報.
黃文彬, 車尚錕* (2019). 計算文本相似度的方法體系與應(yīng)用分析. 情報理論與實踐.
尚聞一*, 車尚錕 (2019). 群體極化還是協(xié)商調(diào)和?--維基百科Islamophobias詞條實證研究. 圖書館論壇.
會議論文
Shangkun Che, Minjia Mao, Hongyan Liu. New Community Cold-Start Recommendation: A Novel Large Language Model-based Method. International Conference on Information Systems. (ICIS, 2024)
Xuewen Han, Neng Wang, Shangkun Che, Hongyang Yang, Kunpeng Zhang, Sean Xin Xu. Enhancing Investment Analysis: Optimizing AI-Agent Collaboration in Financial Research. ACM International Conference on AI in Finance (ICAIF, 2024)
Shangkun Che, Hongyan Liu, Xiaojie Mao, Silin Du. Everything Has Its Price: The Fairness Cost of Fine-tuning Large Language Models for Recommendation. China Summer Workshop on AI in Business. (SWAIB, 2024)
Shen Liu, Shangkun Che, Hongyan Liu*. Enhancing Recommendation Interpretability with Tags: A Neural Variational Model. International Conference on Information Systems. (ICIS, 2022)
Shangkun Che, Hongyan Liu*, Xiaojie Mao. Measuring Counterfactual Fairness of Recommendation Systems: An Identifiable Causal Model. 31st Workshop on Information Technologies and Systems. (WITS, 2021)
Shangkun Che, Hongyan Liu*, Xiaojie Mao. Counterfactual Fairness for Recommendation System: Model, Identification and Measurement. The 5th INFORMS Workshop on Data Science. (Informs DS, 2021)
Yi Bu, Binglu Wang, Win-Bin Huang*, Shangkun Che. MFTACA:An Author Co-citation Analysis Method Combined with Metadata in Full Text. The International Conference on Scientometrics & Informatics. (ISSI, 2017)
專利
劉紅巖, 高歌, 車尚錕, 杜思霖, 景昊, 謝志輝, 吳顯仁, 徐偉招 (2024). 一種基于招聘需求相似度的職位推薦方法. 國家發(fā)明專利.
劉紅巖, 車尚錕, 王瀟 (2021). 模型訓(xùn)練方法、直播推薦方法、設(shè)備、程序產(chǎn)品. 國家發(fā)明專利.