Short Bio

I am an Assistant Professor in the Department of Computer Science at the University of Houston. Prior to this, I was a researcher at the Data Science Department of NEC Labs from 2018 to 2022 and the AWS AI Labs from 2022 to 2024. I received my Ph.D. degree from College of IST, The Pennsylvania State University in 2018, advised by Prof. Xiang Zhang. My research is centered around machine learning, data mining, and artificial intelligence, with a focus on time series analysis through cross-modal learning, multimodal integration, and LLM reasoning. My research has been extended to applications in healthcare (including personalized healthcare, press coverage: Science Japan, KeguanJP), biomedicine, cyber-physical systems, and AIOps (e.g., deployed in AWS cloud systems), and published in refereed conferences (e.g., ICLR, ICML, NeurIPS, ACL, AAAI, CVPR, KDD, WWW) and journals (e.g., IEEE TKDE, ACM TKDD), with more than 20 patents filed or granted.

Research Interests

• Machine learning: time series analysis with LVMs/LLMs/LMMs; agentic AI; generative models; anomaly/OOD analysis; graph learning
• Data science: AI for science (e.g., neuroscience, geoscience), AI for social good (e.g., healthcare, cyber-physical systems, AIOps)

News

[Prospective Students] I am looking for self-motivated Ph.D. students to join my group in Fall 2026. If you are interested, please drop me an email at jni7 [at] uh [dot] edu with your CV/resume, transcripts and any materials that you think are helpful.

Recent Talks

• [Tutorial] "Multi-Modal Time Series Analysis: Data, Methods, and Applications"
  
  • [01/2026] AAAI 2026. Singapore. [Web]
  • [08/2025] KDD 2025. Toronto, Canada. [Web] [Survey]
    Github


• "Cross-Modal Knowledge Transfer in Time Series via Large Vision Models"
  
  • [04/2026] UConn TSC Seminar. Virtual Session.
  • [01/2026] New Faculty Highlights, AAAI 2026. Singapore. [Talk] [Paper]


• "Cross-Modal Knowledge Transfer in Time Series via Multimodal Views"
  
  • [10/2025] UH DES Seminar. Houston, TX.
  • [10/2025] Rice AI Seminar. Houston, TX.
  • [08/2025] Keynote Talk, AI4TS workshop @ IJCAI 2025. Montreal, Canada.


• "Harnessing Vision Models for Time Series Analysis: A Survey"
  
  • [08/2025] IJCAI 2025. Montreal, Canada. [Survey]
    Github

Recent Publications

Full List | Google Scholar | DBLP

^♮ indicates equal contribution, ^★ indicates students / interns I have advised.

• Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting
  ChengAo Shen^★, Wenchao Yu, Ziming Zhao^★, Dongjin Song, Wei Cheng, Haifeng Chen, Jingchao Ni
  Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2025
  
  Github


• Harnessing Vision Models for Time Series Analysis: A Survey
  Jingchao Ni, Ziming Zhao^★, ChengAo Shen^★, Hanghang Tong, Dongjin Song, Wei Cheng, Dongsheng Luo, Haifeng Chen
  Proceedings of the International Joint Conferences on Artificial Intelligence (IJCAI), 2025
  
  Github


• Multi-modal Time Series Analysis: A Tutorial and Survey
  Yushan Jiang, Kanghui Ning, Zijie Pan, Xuyang Shen, Jingchao Ni, Wenchao Yu, Anderson Schneider, Haifeng Chen, Yuriy Nevmyvaka, Dongjin Song
  Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025
  
  Github
  [website]


• Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery
  ChengAo Shen^★, Zhengzhang Chen, Dongsheng Luo, Dongkuan Xu, Haifeng Chen, Jingchao Ni
  Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL Findings), 2025
  
  Github


• Interpreting Graph Neural Networks with In-Distributed Proxies
  Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mohan Mondal, Hua Wei, Dongsheng Luo
  Proceedings of the International Conference on Machine Learning (ICML), 2024
  Truestworthy Learning on Graphs Workshop at the Web Conference (TrustLOG @ WWW), 2024 [pdf]
  
  Github