I am currently a research intern at Northwestern University, under the supervision of Prof. Kaize Ding. I obtained my B.E. degree from Xidian University in 2021 and M.E. degree from Tsinghua University in 2024. My research interests are generally in data mining and machine learning, with a focus on reliable, efficient and automated AI systems. Meanwhile, I am passionate about developing data-centric algorithms to advance applications in social media, urban science and environmental science.

Current Research Interests

• Data-Centric AI: Time Series, Spatiotemporal Graph
• Trustworthy ML: Fraud, Anomaly and OOD Data
• Generative AI and Applications: Urban Science and Environmental Science

Contact Information

I am enthusiastic about the prospect of collaboration. Please feel free to reach out to me via email.
Email: kevin dot kxzhang at gmail dot com

News

• [05/2025] One paper accepted by ECML-PKDD, 2025.
• [05/2025] New survey paper: Large Language Models for Molecular Discovery is now on arXiv.
• [11/2024] One paper accepted by KDD, 2025.
• [10/2024] New survey paper: Deep Graph Learning under Distribution Shifts is now on arXiv.
• [10/2024] One paper accepted by WSDM, 2025.
• [10/2023] One paper accepted by WSDM, 2024.
• [08/2023] One paper accepted by CIKM, 2023.

Publications

• Cross-Domain Conditional Diffusion Models for Time Series Imputation
  Kexin Zhang, Baoyu Jing, K. Selcuk Candan, Dawei Zhou, Qingsong Wen, Han Liu, Kaize Ding^†
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2025.

• A Survey of Large Language Models for Text-Guided Molecular Discovery: from Molecule Generation to Optimization[pdf]
  Ziqing Wang^*, Kexin Zhang^*, Zihan Zhao, Yibo Wen, Abhishek Pandey, Han Liu, Kaize Ding^†
  

• Combinatorial Optimization Perspective based Framework for Multi-behavior Recommendation
  Chenhao Zhai, Chang Meng, Yu Yang, Kexin Zhang, Xuhao Zhao, Xiu Li^†
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025.

• A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation [pdf]
  Kexin Zhang, Shuhan Liu, Song Wang, Weili Shi, Chen Chen, Pan Li, Sheng Li, Jundong Li, Kaize Ding^†
  

• Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models
  Kexin Zhang, Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Kaize Ding, Xiuqiang He, Xue Liu
  ACM International Conference on Web Search and Data Mining (WSDM), 2025.

• An Incremental Learning Approach for Multi-Scenario Recommendation
  Kexin Zhang^*, Yichao Wang^*, Xiu Li^†, Ruiming Tang^†, Rui Zhang
  ACM International Conference on Web Search and Data Mining (WSDM), 2024.

• HCL4QC: Incorporating Hierarchical Category Structures Into Contrastive Learning for Ecommerce Query Classification
  Lvxing Zhu^*, Kexin Zhang^*, Hao Chen, Chao Wei, Weiru Zhang, Haihong Tang, Xiu Li^†
  ACM International Conference on Information and Knowledge Management (CIKM), 2023. (Oral Presentation)

Services

Conference Review:

• Reviewer - KDD 2025
• Sub reviewer - SDM 2025

Educations

• [09/2021]-[06/2024], Master, Institute of Data and Information, Shenzhen International Graduate School, Tsinghua University.
• [09/2017]-[06/2021], Bachelor, School of Electronic Engineering, Xidian University.