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

  • [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.
Palawat Busaranuvong, Xin Zhang, Yanhua Li, Xun Zhou, Jun Luo (2023). CAC: Enabling Customer-Centered Passenger-Seeking for Self-Driving Ride Service with Conservative Actor-Critic. 2023 IEEE International Conference on Data Mining (ICDM).

Cite

Xin Zhang, Yanhua Li, Ziming Zhang, Christopher Brinton, Zhenming Liu, Zhi-Li Zhang (2023). Distributional Cloning for Stabilized Imitation Learning via ADMM. 2023 IEEE International Conference on Data Mining (ICDM).

Cite

Mingzhi Hu, Zhuoyun Zhong, Xin Zhang, Yanhua Li, Yiqun Xie, Xiaowei Jia, Xun Zhou, Jun Luo (2023). Self-supervised Pre-training for Robust and Generic Spatial-Temporal Representations. 2023 IEEE International Conference on Data Mining (ICDM).

Cite

Mingzhi Hu, Xin Zhang, Yanhua Li, Yiqun Xie, Xiaowei Jia, Xun Zhou, Jun Luo (2023). Only Attending What Matter within Trajectories -- Memory-Efficient Trajectory Attention. SIAM International Conference on Data Mining (SDM24).

Cite

Xin Zhang, Yanhua Li, Ziming Zhang, Zhi-Li Zhang (2023). Domain Disentangled Meta-Learning. Proceedings of the 2023 SIAM International Conference on Data Mining (SDM).

PDF Cite

Guojun Wu, Xin Zhang, Ziming Zhang, Yanhua Li, Xun Zhou, Christopher Brinton, Zhenming Liu (2023). Learning Lightweight Neural Networks via Channel-Split Recurrent Convolution. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision.

PDF Cite

Mingzhi Hu, Xin Zhang, Yanhua Li, Xun Zhou, Jun Luo (2023). ST-iFGSM: Enhancing Robustness of Human Mobility Signature Identification Model via Spatial-Temporal Iterative FGSM. the 29th SIGKDD conference on Knowledge Discovery and Data Mining (KDD 2023).

PDF Cite

Xin Zhang, Yanhua Li, Xun Zhou, Oren Mangoubi, Ziming Zhang, Vincent Filardi, Jun Luo (2021). DAC-ML: domain adaptable continuous meta-learning for urban dynamics prediction. 2021 IEEE International Conference on Data Mining (ICDM).

PDF Cite

Xin Zhang, Weixiao Huang, Yanhua Li, Renjie Liao, Ziming Zhang (2021). Imitation Learning From Inconcurrent Multi-Agent Interactions. 2021 60th IEEE Conference on Decision and Control (CDC).

PDF Cite

Xin Zhang, Menghai Pan, Yanhua Li, Xun Zhou, Jun Luo (2021). Learning Decision Making Strategies of Non-experts: A NEXT-GAIL Model for Taxi Drivers. Proceedings of the 29th International Conference on Advances in Geographic Information Systems.

PDF Cite

Xin Zhang, Yanhua Li, Xun Zhou, Jun Luo (2020). cGAIL: Conditional Generative Adversarial Imitation Learning—an Application in Taxi Drivers’ Strategy Learning. IEEE transactions on big data.

PDF Cite

Xin Zhang, Yanhua Li, Ziming Zhang, Zhi-Li Zhang (2020). f-GAIL: Learning f-divergence for generative adversarial imitation learning. Advances in neural information processing systems.

PDF Cite

Xin Zhang, Yanhua Li, Xun Zhou, Ziming Zhang, Jun Luo (2020). TrajGAIL: Trajectory generative adversarial imitation learning for long-term decision analysis. 2020 IEEE International Conference on Data Mining (ICDM).

PDF Cite

Xin Zhang, Yanhua Li, Xun Zhou, Jun Luo (2019). Unveiling taxi drivers' strategies via cGAIL: Conditional generative adversarial imitation learning. 2019 IEEE International Conference on Data Mining (ICDM).

PDF Cite

Teaching

  • CS549 Machine Learning.
  • CS696 Reinforcement Learning.

Contact