The publications below are listed in chronological order. You can also find my articles on my Google Scholar profile.

In the year of 2024

  1. [ICLR’24] AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction (Acceptance Ratio=31%, CORE Rank A*)
    K. Hettige, J. Ji, S. Xiang, C. Long, G. Cong, J. Wang
    International Conference on Learning Representations

In the year of 2023

  1. [Interspeech’23] Enhancing New Intent Discovery via Robust Neighbor-based Contrastive Learning (CCF C, Core Rank A)
    Z. Wu, X. Yu, M. Chen, L. Wu, J. Ji, and Z. Li
    INTERSPEECH Conference

  2. [Weekly’23] High-Resolution Data on Human Behavior for Effective COVID-19 Policy-Making — Wuhan City, Hubei Province, China, January 1–February 29, 2020 (SCI)
    J. Wang, H. Shi, J. Ji, X. Lin, H. Tian
    China CDC Weekly

  3. [AAAI’23] Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction (Acceptance Ratio=19.6%, CCF A)
    J. Ji, J. Wang, C. Huang, J. Wu, B. Xu, Z. Wu, J. Zhang and Y. Zheng
    AAAI Conference on Artificial Intelligence

In the year of 2022

  1. [TKDE’22] Traffic Flow Prediction Based on Spatiotemporal Potential Energy Fields (IF=9.235, CCF A)
    J. Wang, J. Ji, Z. Jiang, L. Sun
    IEEE Transactions on Knowledge and Data Engineering

  2. [ECML/PKDD’22] DialCSP: A Two-stage Attention-based Model for Customer Satisfaction Prediction in E-commerce Customer Service (Acceptance Ratio=26.0%, CCF B)
    Z. Wu, L. Wu, S. Song, J. Ji, B. Zou, Z. Li, and X. He
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases

  3. [KDD’22] Precision CityShield Against Hazardous Chemicals Threats via Location Mining and Self-Supervised Learning (Acceptance Ratio=25.9%, CCF A)
    J. Ji, J. Wang, J. Wu, B. Han, J. Zhang, and Y. Zheng
    ACM International Conference on Knowledge Discovery and Data Mining

  4. [AAAI’22] STDEN: Towards Physics-Guided Neural Networks for Traffic Flow Prediction (Acceptance Ratio=15.0%, CCF A)
    J. Ji, J. Wang, Z. Jiang, J. Jiang, and H. Zhang
    AAAI Conference on Artificial Intelligence

Before the year of 2022

  1. [ICDM’20] Interpretable Spatiotemporal Deep Learning Model for Traffic Flow Prediction Based on Potential Energy Fields (Acceptance Ratio=9.9%, CCF B)
    J. Ji, J. Wang, Z. Jiang, J. Ma, and H. Zhang
    IEEE International Conference on Data Mining