Jiawen Zhang / 张佳雯

I am a Ph.D. student in Data Science and Analytics at The Hong Kong University of Science and Technology under the supervision of Prof. Jia Li and Prof. Xiaofang Zhou. Currently, my research interests include data mining and time series modeling. Prior to my doctoral studies, I received my M.Eng. degree in Computer Technology from the Chinese Academy of Sciences (CAS), with Professor Jiaqi Zhu as my advisor.

For research experience, I have been a research intern at the Machine Learning Group in Microsoft Research Asia, collaborating with Dr. Shun Zheng and Dr. Jiang Bian. Before that, I contributed as an NLP Algorithm Engineer Intern at the Multi-Media Understanding Group in Kwai Technology.

If you have any inquiries or are interested in potential collaborations, please do not hesitate to reach out to me. :D

Google Scholar: eUiwC9AAAAAJ

Publications

[1] J. Zhang, S. Zheng, X. Wen, X. Zhou, J. Bian and J. Li. (2024). ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer. In Proc. of NeurIPS 2024.

GitHub Project: https://github.com/microsoft/ProbTS/tree/elastst

[2] J. Zhang, X. Wen, Z. Zhang, S. Zheng, J. Li and J. Bian. (2024). ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons. In Proc. of NeurIPS 2024.

GitHub Project: https://github.com/microsoft/ProbTS

[3] X. Sun, J. Zhang, X. Wu, H. Cheng, Y. Xiong and J. Li. (2023). Graph prompt learning: A comprehensive survey and beyond. ArXiv.

[4] J. Zhang, S. Zheng, W. Cao, J. Bian and J. Li. (2023). Warpformer: A Multi-scale Approach for Irregularly Sampled Multivariate Time Series. In Proc. of KDD 2023.

GitHub Project: https://github.com/imJiawen/Warpformer

[5] Z. Gao, C. Jiang, J. Zhang, X. Jiang, L. Li, P. Zhao, H. Yang, Y. Huang and J. Li. (2023). Hierarchical Graph Learning for Protein-Protein Interaction. Nature Communications 2023.

[6] J. Zhang, J. Zhu, Y. Yang, W. Shi, C. Zhang and H. Wang. (2021). Knowledge-Enhanced Domain Adaptation in Few-Shot Relation Classification. In Proc. of KDD 2021.

GitHub Project: https://github.com/imJiawen/KEFDA

[7] J. Zhang, Y. Zhao, J. Zhu and J. Xiao. (2020). Distant Supervision for Polyphone Disambiguation in Mandarin Chinese. In Proc. of INTERSPEECH 2020.

[8] J. Zhang, M.L. Bourguet and G. Venture. (2018). The Effects of Video Instructors Body Languageon Students Distributionof Visual Attention: an Eye-tracking Study. In Proc. of British HCI 2018.

[9] Y Li, J. Zhu, C. Zhang, Y. Yang, J. Zhang and Y. Qiao. (2023). THGNN: An Embedding-based Model for Anomaly Detection in Dynamic Heterogeneous Social Networks. In Proc. of CIKM 2023.

[10] Y. Yang, H. Wang, J. Zhu, W. Shi, W. Guo and J. Zhang. (2021). Effective Seed-Guided Topic Labeling for Dataless Hierarchical Short Text Classification. In Proc. of ICWE 2021 (pp. 271-285).

Reaserch Experiences

08/2023 - 08/2024
Data Science Foundations Lab, HKUST, Hong Kong SAR
Visiting Student

12/2021 - 04/2023
Machine Learning Group, Microsoft Research Asia, Beijing
Research Intern

11/2019 - 11/2021
Multi-Media Understanding Group, Kwai Technology, Beijing
NLP Algorithm Engineer Intern

03/2018 - 05/2018
GVLab Robotics Laboratory, Tokyo University of Agriculture and Technology, Tokyo
Visiting Student

Key Technical Skills

Python > C > JAVA = MATLAB
Proficiency in spoken and written English (all the courses were deliveried in English in the undergraduate years)
Familiar with Linux system
Adobe Photoshop / Illustratory
Native Chinese speaker
Graphic design & Drawing
Table tennis