Xin Zhang

Xin Zhang

Assistant Professor

Computer Science

San Diego State University

Biography

Xin Zhang is an Assistant Professor in the Computer Science Department at San Diego State University. She received her Ph.D. degree in Data Sciences from Worcester Polytechnic Institute in 2023. Her main research focuses are on artificial intelligence (AI) and spatial-temporal data mining with applications in smart cities and urban intelligence. Particularly, she is interested in: (1) human behavior analysis, decision making and embodied AI using deep learning approaches, and (2) spatial-temporal data mining with novel AI techniques for urban computing and smart cities. Her works appear in NeurIPS, KDD, ICDM, etc.

Download my CV.

Openings: I am looking for self-motivated PhD students to work on deep learning projects. I’m particularly interested in candidates with background in CS/AI/Data Mining/Machine Learning/Stat/Math and strong programming skills. Please send me a short email with your CV and transcript.

Interests
  • Artificial Intelligence
  • Spatial-temporal Data Mining
  • Applications in Smart Cities and Urban Intelligence
Education

  • Ph.D. in Data Sciences, 2023

    Worcester Polytechnic Institute

  • M.S. in Data Sciences, 2019

    Worcester Polytechnic Institute

  • B.S. in Applied Mathematics, 2017

    University of Illinois at Urbana-Champaign

Recent News

  • [Paper] 08/2025: One paper was accepted by SIGSPATIAL 2025, another accepted by ICDM 2025.
  • [Talk] 07/2025: Invited talk at SDSU AI Bootcamp.
  • [Grant] 06/2025: Our Google-CAHSI IRP project has been selected for award, with me as PI. Thanks to Google-CAHSI!
  • [Grant] 06/2025: My NSF CRII proposal has been selected for award. Thanks to NSF!
  • [Paper] 06/2025: One paper was accepted by KDD 2025, another accepted by ICCV 2025.
  • [TPC] 03/2025: Served as Technical Program Committee for KDD 2025, NeurIPS 2025.
  • [Paper] 09/2024: One paper was accepted by ICDM 2024.
  • [TPC] 06/2024: Served as Technical Program Committee for ICLR, AISTATS 2025.
  • [Paper] 06/2024: One paper was accepted by KDD 2024.
  • [TPC] 01/2024: Served as Technical Program Committee for IEEE MASS 2024.
  • [Paper] 12/2023: One paper was accepted by SDM 2024.
  • [Talk] 12/2023: Invited talk at Ocean University of China.
  • [Talk] 10/2023: Invited talk at CSRC Colloquium at SDSU.
  • [Paper] 09/2023: Three papers were accepted by ICDM 2023.
  • [TPC] 09/2023: Served as Program Committee for SDM 2024 & ICLR 2024.
  • [Paper] 05/2023: One paper was accepted by KDD 2023.
  • [Award] 04/2023: Awarded the SDM 2023 Doctoral Forum travel award.
  • [TPC] 03/2023: Served as Technical Program Committee for NeurIPS 2023.
  • [TPC] 01/2023: Served as Technical Program Committee for KDD 2023.
  • [Paper] 12/2022: One paper was accepted by SDM 2023.
  • [TPC] 12/2022: Serve as Technical Program Committee for ICML 2023.
  • [Paper] 10/2022: One paper was accepted by WACV 2023.
  • [TPC] 03/2022: Served as Technical Program Committee for NeurIPS 2022.
  • ……

Publications

Quickly discover relevant content by filtering publications.
Yuhang Liu, Yingxue Zhang, Xin Zhang, Yu Yang, Yanhua Li, Jun Luo (2025). MARCEL: Multifaceted Spatial-Temporal Contrastive Learning for Generic Spatial-Temporal Representations. 2025 IEEE International Conference on Data Mining (ICDM), 12-15 November 2025..

Cite

Mingzhi Hu, Xin Zhang, Yanhua Li, Jun Luo (2025). KG-STFT: Knowledge Graph-Guided Human-Generated Spatial-Temporal Cross-task Fine-Tuning. 33rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2025).

Cite

Wan Jiang, He Wang, Xin Zhang, Dan Guo, Zhaoxin Fan, Yunfeng Diao, Richang Hong, (2025). Moderating the generalization of score-based generative model. 2025 Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV).

PDF Cite

Yuhang Liu, Yingxue Zhang, Xin Zhang, Ling Tian, Yanhua Li, Jun Luo (2025). UrbanMind: Urban Dynamics Prediction with Multifaceted Spatial-Temporal Large Language Models. 2025 Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD).

PDF Cite

Yuhang Liu, Yingxue Zhang, Xin Zhang, Yu Yang, Yiqun Xie, Sahar Ghanipoor Machiani, Yanhua Li, Jun Luo (2024). Align Along Time and Space: A Graph Latent Diffusion Model for Traffic Dynamics Prediction. 2024 IEEE International Conference on Data Mining (ICDM), 9-12 December 2024, Abu Dhabi, UAE. (Acceptance rate = 19.5%).

Cite

See all publications

Students

Current Graduate Students

  • Bijal Bharadva
  • Surinder Singh Chhabra
  • Manuel Kelly
  • Robert Ashe

Current Undergraduate Students

  • Chris Anderson
  • Liam Seidel

Past Graduate Students

  • Jonathan Martinez
  • Ibisia Jack (MS Student) – Now a PhD Candidate at SDSU

Teaching

  • CS549 Machine Learning.
  • CS696 Reinforcement Learning.

Contact