Computational Simulation and Analysis of Major Control Parameters of Time-Dependent PV/T Collectors. - Jimeng Shi; Cheng-Xian Lin (CoRR, 2021)

Time Series Forecasting (TSF) Using Various Deep Learning Models. - Jimeng Shi; Mahek Jain; Giri Narasimhan (CoRR, 2022)

Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting. - Jimeng Shi; Rukmangadh Myana; Vitalii Stebliankin; Azam Shirali; Giri Narasimhan (AALTD@ECML/PKDD, 2023)

Deep Learning Models for Water Stage Predictions in South Florida. - Jimeng Shi; Zeda Yin; Rukmangadh Myana; Khandker Ishtiaq; Anupama John; Jayantha Obeysekera; Arturo S. Leon; Giri Narasimhan (CoRR, 2023)

Graph Transformer Network for Flood Forecasting with Heterogeneous Covariates. - Jimeng Shi; Vitalii Stebliankin; Zhaonan Wang 001; Shaowen Wang 001; Giri Narasimhan (CoRR, 2023)

The Power of Explainability in Forecast-Informed Deep Learning Models for Flood Mitigation. - Jimeng Shi; Vitalii Stebliankin; Giri Narasimhan (CoRR, 2023)

Evaluating protein binding interfaces with transformer networks. - Vitalii Stebliankin; Azam Shirali; Prabin Baral; Jimeng Shi; Prem Chapagain; Kalai Mathee; Giri Narasimhan (Nat. Mac. Intell., 2023)

Boosting Time Series Prediction of Extreme Events by Reweighting and Fine-tuning. - Jimeng Shi; Azam Shirali; Giri Narasimhan (IEEE Big Data, 2024)

TimeX++: Learning Time-Series Explanations with Information Bottleneck. - Zichuan Liu; Tianchun Wang; Jimeng Shi; Xu Zheng 003; Zhuomin Chen; Lei Song 001; Wenqian Dong; Jayantha Obeysekera; Farhad Shirani 001; Dongsheng Luo (ICML, 2024)

CoDiCast: Conditional Diffusion Model for Weather Prediction with Uncertainty Quantification. - Jimeng Shi; Bowen Jin; Jiawei Han 001; Giri Narasimhan (CoRR, 2024)

ReFine: Boosting Time Series Prediction of Extreme Events by Reweighting and Fine-tuning. - Jimeng Shi; Azam Shirali; Giri Narasimhan (CoRR, 2024)

FIDLAR: Forecast-Informed Deep Learning Architecture for Flood Mitigation. - Jimeng Shi; Zeda Yin; Arturo S. Leon; Jayantha Obeysekera; Giri Narasimhan (AAAI, 2025)

Deep Learning and Foundation Models for Weather Prediction: A Survey. - Jimeng Shi; Azam Shirali; Bowen Jin; Sizhe Zhou; Wei Hu; Rahuul Rangaraj; Shaowen Wang 001; Jiawei Han 001; Zhaonan Wang 001; Upmanu Lall; Yanzhao Wu 001; Leonardo Bobadilla; et al. (CoRR, 2025)

How Effective are Large Time Series Models in Hydrology? A Study on Water Level Forecasting in Everglades. - Rahuul Rangaraj; Jimeng Shi; Azam Shirali; Rajendra Paudel; Yanzhao Wu 001; Giri Narasimhan (CoRR, 2025)

Hypercube-RAG: Hypercube-Based Retrieval-Augmented Generation for In-domain Scientific Question-Answering. - Jimeng Shi; Sizhe Zhou; Bowen Jin; Wei Hu; Shaowen Wang 001; Giri Narasimhan; Jiawei Han 001 (CoRR, 2025)

SF2Bench: Evaluating Data-Driven Models for Compound Flood Forecasting in South Florida. - Xu Zheng 003; Chaohao Lin; Sipeng Chen; Zhuomin Chen; Jimeng Shi; Wei Cheng 002; Jayantha Obeysekera; Jason Liu; Dongsheng Luo (CoRR, 2025)

Retrieval-Augmented Water Level Forecasting for Everglades. - Rahuul Rangaraj; Jimeng Shi; Rajendra Paudel; Giri Narasimhan; Yanzhao Wu 001 (CoRR, 2025)

A comprehensive survey of scoring functions for protein docking models. - Azam Shirali; Vitalii Stebliankin; Ukesh Karki; Jimeng Shi; Prem Chapagain; Giri Narasimhan (BMC Bioinform., 2025)