About
Jiahao JI is a Ph.D. candidate at the School of Computer Science and Engineering, Beihang University, China, supervised by Prof. Jingyuan Wang. He received his B.S from Beihang University in 2019.
Since February 2023, he is a visiting scholar at Nanyang Technological University, Singapore, supervised by Prof. Cheng Long. From March 2021 to January 2023, he participated in the joint doctoral training program of JD Intelligent Cities Research, supervised by Prof. Yu Zheng and Dr. Junbo Zhang.
Research Interests
His research interests include spatio-temporal data mining, interpretable machine learning and urban computing. In particular, he has passion in designing (1) interpretable and robust algorithms for mining spatio-temporal data and graph data and (2) models for learning from these data types for various applications such as transportation, hazardous chemicals, epidemic, etc.
Recent News
- [01/2024] Our paper for physics-informed neural network was accepted by ICLR 2024.
- [12/2023] Our paper Self-Supervised Deconfounding Against Spatio-Temporal Shifts: Theory and Modeling is now on arxiv.
- [09/2023] I was awarded with National PhD Scholarship. <!– * [11/2022] One paper is accepted by AAAI 2023.
- [11/2022] One paper is accepted by IEEE TKDE 2022. –>
Featured Publications [See more]
[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
[pdf][code][bib][media][web][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
[pdf][bib][web][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
[pdf][bib][web][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
[pdf][code][bib][media][web]
Professional Activities [See more]
Journal Reviewer: IEEE TKDE, IEEE T-ITS, ACM TIST, PMC, KNOSYS, TR_C
Conference Reviewer: KDD, CIKM, ICDM, AAAI, WSDM
Honors and Awards
- National Scholarship: 2023
- CETC The 14TH Research Institute Glarun Scholarship: 2022, 2020
- Scholarships for Postgraduate Studies (five times for the First Prize): 2023, 2022, 2021, 2020, 2019
- Huawei Scholarship: 2021
- CASC Scholarship: 2020
- Outstanding Freshman Scholarship: 2019
- National Scholarship for Encouragement: 2018, 2017, 2016
- MIIT Innovation and Entrepreneurship Scholarship: 2019
- ASC18 - ASC Student Supercomputer Challenge: the First Prize, 2018
- COMAP’s Mathematical Contest in Modeling: Meritorious Winner, 2018
- Merit Student of Beihang University: 2022, 2020, 2018, 2017