Xin Zhang, Ph.D.

Pronouns: Xin

Assistant Professor of Computer Science

College of Sciences
Department of Computer Science

San Diego

Phone
Office Hours

Tues 12:30pm – 1:30pm
Thur 12:30pm – 1:30pm

Location
GMCS 538
5500 Campanile Dr
San Diego, CA 92182
Mail Code
1020
Fax
619-594-6746
Accounts

Areas of Expertise

Spatial-Temporal Data Science, Deep Learning, Imitation Learning, Meta-learning

Bio

Dr. Zhang’s 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.

Details

Education
  1. Ph.D. in Data Sciences
    Worcester Polytechnic Institute
  2. M.S. in Data Sciences
    Worcester Polytechnic Institute
  3. B.S. in Applied Mathematics
    University of Illinois Urbana-Champaign
Publications
  1. Guojun Wu, Xin Zhang, Ziming Zhang, Yanhua Li, Xun Zhou, Christopher Brinton, and Zhenming Liu, Learning Lightweight Neural Networks via Channel-Split Recurrent Convolution. Winter Conference on Applications of Computer Vision 2023, Waikoloa, Hawaii, Jan 3 – Jan 7, 2023.
  2. Xin Zhang, Yanhua Li, Xun Zhou, Oren Mangoubi, Ziming Zhang, Vincent Filardi, and Jun Luo, DAC-ML: Domain Adaptable Continuous Meta-Learning for Urban Dynamics Prediction. IEEE International Conference on Data Mining, Auckland, New Zealand, Nov. 7-10, 2021.
  3. Xin Zhang, Weixiao Huang*, Yanhua Li, Renjie Liao, and Ziming Zhang, Imitation Learning From Inconcurrent Multi-Agent Interactions. The 60th IEEE Conference on Decision and Control (CDC 2021), Austin, TX on December 13-15, 2021.
  4. Xin Zhang, Menghai Pan*, Yanhua Li, Xun Zhou, and Jun Luo, Learning Decision Making Strategies of Non-experts: A NEXT-GAIL Model for Taxi Drivers. The 29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Beijing, China, Nov. 2 – Nov. 5, 2021.
  5. Xin Zhang, Yanhua Li, Ziming Zhang, and Zhi-Li Zhang, f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning. 34th Conference on Neural Information Processing Systems (NeurIPS), Virtual Conference, Dec. 6 – 12, 2020.
  6. Xin Zhang, Yanhua Li, Xun Zhou, Ziming Zhang, and Jun Luo, Traj-GAIL: Trajectory Generative Adversarial Imitation Learning for Long-term Decision Analysis. IEEE International Conference on Data Mining (ICDM), Sorrento, Italy, Nov. 17-20, 2020.
  7. Xin Zhang, Yanhua Li, Xun Zhou, and Jun Luo, cGAIL: Conditional Generative Adversarial Imitation Learning—An Application in Taxi Drivers’Strategy Learning. IEEE Transactions on Big Data, Accepted for publication, 2020.
  8. Xin Zhang, Yanhua Li, Xun Zhou, and Jun Luo, Unveiling Taxi Drivers’Strategies via cGAIL – Conditional Generative Adversarial Imitation Learning. IEEE International Conference on Data Mining, Beijing, China, Nov. 8-11, 2019.
Grants
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Presentations
  1. Winter Conference on Applications of Computer Vision (WACV) Waikoloa, HI, Jan. 2023
    Conference Presenter
  2. IEEE International Conference on Data Mining (ICDM) Virtual event, Nov. 2021
    Conference Presenter
  3. IEEE International Conference on Decision and Control (CDC) Virtual event, Dec. 2021
    Conference Presenter
  4. International Conference on Advances in Geographic Information Systems Beijing, Nov. 2021
    Conference Presenter
  5. Conference on Neural Information Processing Systems (NeurIPS) Virtual event, Dec. 2020
    Poster Presenter
  6. IEEE International Conference on Data Mining (ICDM) Virtual event, Nov. 2020
    Conference Presenter
Service
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Clinical Trials
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Awards & Honors
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Patents & Copyrights
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Media
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Fun Facts
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