Jingtong Gao

Jingtong Gao

About Me

I'm currently a fourth-year PhD student of Data Science at the City University of Hong Kong (CityU) under the advisory of Prof. Xiangyu Zhao. Prior to CityU, I completed my MSc under the advisory of Prof. Danwei Wang at Nanyang Technological University (NTU) in 2022 and my BEng under the advisory of Prof. Shaopeng Dong at Beihang University (BUAA) in 2021.

My research interests include Recommender Systems (RecSys) · Advertising · Large Language Models (LLMs) · Reinforcement Learning (RL) · Deep Learning. I have published several papers at the top international AI conferences with 800+ citations.

Open to Opportunities

Expected PhD graduation: October 2026. Actively seeking opportunities in Recommender Systems, Ads tech and other LLM-related positions worldwide. Feel free to reach out via email.

News

Honors and Awards

2025

  • Outstanding Academic Performance Award (OAPA-CityU 2025)
  • WWW'25 Student Travel Award

2024

2023

  • IJCAI'23 Travel Award
  • Research Tuition Scholarship (RTS-CityU 2023)
  • Outstanding Academic Performance Award (OAPA-CityU 2023)

Professional Experience

  • 2024.08 – PresentResearch Intern at Kuaishou
  • 2022 – 2024.06Research Intern at Huawei
  • ServicePC member of CIKM, IJCAI

Publications

Tutorials

[4]

Joint Modeling in Deep Recommender Systems

Pengyue Jia, Jingtong Gao, Yuhao Wang, Xiaopeng Li, Qidong Liu, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang

WWW'25, Proceedings of the ACM Web Conference 2025

CITE

[3]

Joint Modeling in Recommendations: Foundations and Frontiers

Xiangyu Zhao, Yichao Wang, Bo Chen, Pengyue Jia, Yuhao Wang, Jingtong Gao, Huifeng Guo, Ruiming Tang

IJCAI'23, Proceedings of the 32st International Joint Conference on Artificial Intelligence

[2]

Trustworthy Recommender Systems: Foundations and Frontiers

Wenqi Fan, Xiangyu Zhao, Lin Wang, Xiao Chen, Jingtong Gao, Qidong Liu, Shijie Wang

IJCAI'23, Proceedings of the 32nd International Joint Conference on Artificial Intelligence

KDD'23, Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

CITE

Conference and Journal Papers

C15

Generative Auto-Bidding in Large-Scale Auctions via Diffusion Completer-Aligner

Yewen Li, Jingtong Gao, Peng Jiang, Ruyi An, Xiangyu Zhao, Bo An, Fei Pan, Qingpeng Cai, Peng Jiang, Kun Gai

KDD'26 ADS Track, Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Deployed online · Kuaishou
C14

Hierarchical Residual Policy Optimization for Generative Recommendations

Kaifeng Guo, Yiming Yang, Jingtong Gao, Guolei Zeng, Fukang Yang, Yukang Liang, Peng Jiang, Qingpeng Cai, Xiangyu Zhao

KDD'26, Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Deployed online · Kuaishou
C13

Detecting Miscitation on the Scholarly Web through LLM-Augmented Text-Rich Graph Learning

Huidong Wu, Haojia Xiang, Jingtong Gao, Xiangyu Zhao, Dengsheng Wu and Jianping Li

WWW'26, Proceedings of the ACM Web Conference 2026

C12

BlossomRec: Block-level Fused Sparse Attention Mechanism for Sequential Recommendations

Mengyang Ma, Xiaopeng Li, Wanyu Wang, Zhaocheng Du, Jingtong Gao, Pengyue Jia, Yuyang Ye, Yiqi Wang, Yunpeng Weng, Weihong Luo, Xiao Han and Xiangyu Zhao

WWW'26, Proceedings of the ACM Web Conference 2026

C10

Generative Auto-Bidding with Value-Guided Explorations

Jingtong Gao, Yewen Li, Shuai Mao, Peng Jiang, Nan Jiang, Yejing Wang, Qingpeng Cai, Fei Pan, Peng Jiang, Kun Gai, Bo An, Xiangyu Zhao

SIGIR'25, Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval

Deployed online · Kuaishou

CITE