Hongwei Jin, George Papadimitriou, Krishnan Raghavan, Pawel Zuk, Prasanna Balaprakash, Cong Wang, Anirban Mandal, and Ewa Deelman. Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning. SC24: International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, 2024. 

Hamza Safri, George Papadimitriou, Frederic Desprez, and Ewa Deelman. A Workflow Management System Approach To Federated Learning: Application to Industry 4.0. 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), Apr 2024

Anirban Mandal, Komal Thareja, and Paul Ruth. Network Testbed for Experimenting With Decentralized Federated Learning POSTER Paper in 20th IEEE International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT 2024), Abu Dhabi, UAE, April 2024.

Imtiaz Mahmud, George Papadimitriou, Cong Wang, Mariam Kiran, Anirban Mandal, and Ewa Deelman. Elephants Sharing the Highway – Studying TCP Fairness in Large Transfers Over High Throughput Links. 2023 IEEE/ACM Innovating the Network for Data-Intensive Science (INDIS).

Ewa Deelman. How is Artificial Intelligence Changing Science? IEEE 19th International Conference on e-Science (e-Science), Oct 2023

Imtiaz Mahmud, George Papadimitriou, Cong Wang, Mariam Kiran, Anirban Mandal, and Ewa Deelman Experimenting TCP Performance with Fabric. IEEE/ACM Innovating the Network for Data-Intensive Science (INDIS) Workshop at SC'23, Denver, CO, Nov 2023.

George Papadimitriou, Hongwei Jin, Cong Wang, Krishnan Raghavan, Anirban Mandal, Prasanna Balaprakash, and Ewa Deelman. Flow-Bench: A Dataset for Computational Workflow Anomaly Detection. arXiv preprint arXiv:2306.09930, June 2023.

Hongwei Jin, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Mariam Kiran, Ewa Deelman, and Prasanna Balaprakash. Graph Neural Networks for Detecting Anomalies in Scientific Workflows The International Journal of High Performance Computing Applications, 2023;0(0). doi:10.1177/10943420231172140, May 2023

Hongwei Jin, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Patrycja Krawczuk, Loïc Pottier, Mariam Kiran, and Ewa Deelman, Prasanna Balaprakash (2022). Workflow Anomaly Detection with Graph Neural Networks. 2022 IEEE/ACM Workshop on Workflows in Support of Large-Scale Science (WORKS), Nov 2022

Tu Mai Anh Do, Loïc Pottier, Orcun Yildiz, Karan Vahi, Patrycja Krawczuk, Tom Peterka, and Ewa Deelman Accelerating Scientific Workflows on HPC Platforms with In Situ Processing. 2022 IEEE/ACM 22nd International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 1–10. https://doi.org/10.1109/CCGrid54584.2022.00009

Loïc Pottier, Prasanna Balaprakash, George Papadimitriou, Mariam Kiran, Krishnan Raghavan, Cong Wang, Patrycja Krawczuk, Komal Thareja, Anirban Mandal and Ewa Deelman. Graph Neural Network for Anomalies Detection in Scientific Workflows Poster and Short Paper in 2022 Workshop on Modeling & Simulation of Systems and Applications (MODSIM '22), Seattle, WA, August 2022

Patrycja Krawczuk, George Papadimitriou, Ryan Tanaka, Tu Mai Anh Do, Srujana Subramany, Shubham Nagarkar, Aditi Jain, Kelsie Lam, Anirban Mandal, Loïc, Pottier, and Ewa Deelman.
A Performance Characterization of Scientific Machine Learning Workflows. 2021 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS).