Self-adaptive multi-population genetic algorithms for dynamic resource allocation in shared hosting platforms. - Azam Shirali; Javidan Kazemi Kordestani; Mohammad Reza Meybodi (Genet. Program. Evolvable Mach., 2018)

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)

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)

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

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)

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)