About Me

Introduction

My name is Jimeng Shi, a fourth-year Ph.D. student in Computer Science at Florida International University, fortunately advised by Prof. Giri Narasimhan. My research focus locates at developing robust and explainable AI tools to address real-world problems in Environmental Science, Climate Science and Earth Science. Recently, I am working on Large Language Models (LLMs) and Multi-modal learning. My work is being funded by NSF I-GUIDE.

Research Interests

• AI for Science
• Environmental Science: flood prediction (FloodGTN) and mitigation (FIDLAr), air quality prediction (AIR), physics-informed neural networks (PINNs)
• Climate Science: diffusion model for weather prediction (CoDiCast), RAG for precipitation nowcast (coming soon)
• Biology: vision transformer for protein binding (PIsToN), evaluating protein docking models (Survey)
• Large Models
• Large Language Models: LLMs+RAG (coming soon)
• Time Series Foundation Models: (Evaluation)
• Explainable AI
• Time Series: explanations with information bottleneck (TimeX++), explanations using LIME (ReFine, FIDLAr), explainations using GradCAM (ParaRCNN)

Selected Publications

• FIDLAR: Forecast-Informed Deep Learning Approaches for Flood Mitigation
  Jimeng Shi, Zeda Yin, Arturo Leon, Jayantha Obeysekera, Giri Narasimhan
  The 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025) (Oral)
  [PDF] [Code] [Media]
  
  
• CoDiCast: Conditional Diffusion Model for Weather Prediction with Uncertainty Quantification
  Jimeng Shi, Bowen Jin, Jiawei Han, Sundararaman Gopalakrishnan, Giri Narasimhan
  The 34th International Joint Conference on Artificial Intelligence (IJCAI 2025)
  [PDF] [Code]
  
  
• ReFine: Boosting Time Series Prediction Under Extreme Events by Reweighting and Fine-tuning
  Jimeng Shi, Azam Shirali, Giri Narasimhan.
  2024 IEEE International Conference on Big Data (IEEE BigData 2024) (Oral)
  [PDF] [Code]
  
  
• The Power of Explainability in Forecast-Informed Deep Learning Models for Flood Mitigation
  Jimeng Shi, Vitalii Stebliankin, Giri Narasimhan
  NeurIPS 2023 workshop on Climate Change AI (Poster)
  [PDF] [Code]
  
  
• Graph Transformer Network for Flood Forecasting with Heterogeneous Covariates
  Jimeng Shi, Vitalii Stebliankin, Zhaonan Wang, Shaowen Wang, Giri Narasimhan
  NSF I-GUIDE Forum in New York, 2023 (Oral)
  [PDF] [Code]
  
  
• Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting
  Jimeng Shi, Rukmangadh Myana, Vitalii Stebliankin, Azam Shirali, Giri Narasimhan
  ECML-PKDD 2023 workshop on Advanced Analytics and Learning on Temporal Data (Oral)
  [PDF] [Code]
  
  
• Deep Learning Models for Water Level Prediction in South Florida
  Jimeng Shi^*, Zeda Yin^*, Rukmangadh Myana, Arturo Leon, Jayantha Obeysekera, Giri Narasimhan
  Journal of water resources planning and management (To appear)
  [PDF] [Code]
  

Education

• Ph.D. Computer Science - Florida International University (2021 - 2025).
• M.S. Computer Science - Florida International University (2019 - 2021).
• B.S. Vehicle Engineering - Tianjin University of Science & Technology (2014 - 2018).

Experience

• Florida International University - Research Assistant
• During Ph.D., Working with Prof. Giri Narasimhan on the development and application of Machine Learning algorithms. (2021.08 - Now)
• During Master's Degree, I had been workeing with Prof. Cheng-Xian Lin on numeric analysis and simulation on solar enginerring using Matlab. (2019.01 - 2020.06)
• Columbia University - Research Fellow
• Worked at NSF LEAP on generative AI for climate emulation while mentoring two REU students. (2024.05 - 2024.08)
• Lid Vizion - Machine Learning Engineer (Internship)
• Worked at Lid Vizion Company at Miami, Florida, USA. I was in charge of applying Yolo-v4 model to detect objects (paper or cardboard) on the river. (2020.09 - 2020.12)

Professional Services

• Committee Member
• International Conference on Deep Learning Technologies (ICDLT) (2023, 2024)
• World Academy of Science, Engineering and Technology (WASET) (2022, 2023, 2024)
• Paper Reviewer
• International Conference on Learning Representations (ICLR), 2025
• International Joint Conference on Artificial Intelligence (IJCAI), 2025
• SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024
• NeurIPS Workshop: Tackling Climate Change with Machine Learning, 2024
• ICLR Workshop: Tackling Climate Change with Machine Learning, 2024, 2025
• International Conference on Information and Knowledge Management (CIKM), 2023
• European Conference on Artificial Intelligence (ECAI), 2025
• European Conference on Machine Learning (ECML), 2023, 2024, 2025
• 6th International Conference on Computer Science and Application Engineering (CSAE) 2022
• IEEE Transactions on Big Data, 2025
• Journal of Intelligent & Fuzzy Systems, 2021, 2022
• Volunteer
• Helped to organize the International Collegiate Programming Contest (ICPC) Southeast USA Regional Contest at Florida International University. (2022, 2023, 2024)
• Helped to organize the High School Programming Contest at Florida International University. (2025)