About Me

Introduction

My name is Jimeng Shi, a Ph.D. student in computer science under the supervision of Prof. Giri Narasimhan from Knight Foundation School of Computing and Information Sciences at Florida International University. My research focus is to address various real-world problems by developing robust and explainable machine learning tools. I have finished a project - flood prediction and mitigation using AI models. Recently, I have started working on generative AI models (e.g., diffusion models) for climate and weather forecasting. My work is being funded by NSF I-GUIDE.

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).

Selected Publications

• 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 (Under review).
  Part of work was presented at the I-GUIDE All-Hands Meeting, Chicago in 2022.
  [PDF] [Code]
  
  

Experience

• Florida International University - Research Assistant
• Working with Dr. Giri Narasimhan on the development and application of Machine Learning algorithms. (2021.08 - Now)
• Worked with Dr. 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)

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
• SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024, 2025.
• NeurIPS Workshop: Tackling Climate Change with Machine Learning, 2024.
• ICLR Workshop: Tackling Climate Change with Machine Learning, 2024.
• Machine Learning Research (MLR), 2023, 2024.
• International Conference on Information and Knowledge Management (CIKM), 2023.
• European Conference on Machine Learning (ECML), 2023, 2024.
• 6th International Conference on Computer Science and Application Engineering (CSAE), 2022.
• Journal of Intelligent & Fuzzy Systems 2021, 2022.
• ICPC Volunteer
• Helped to organize the International Collegiate Programming Contest (ICPC) Southeast USA Regional Contest at Florida International University. (2022, 2023, 2024)