Ewa Deelman

About

Ewa Deelman is a Research Professor of Computer Science and a Principal Scientist at USC Information Sciences Institute. Her main area of research is distributed computing, focusing on supporting complex scientific applications across various computational environments such as campus clusters, grids, and clouds. She has designed new algorithms for job scheduling, resource provisioning, and data storage optimization within scientific workflows. Since 2000, she has conducted research in scientific workflows and led the development of the Pegasus software, which maps complex application workflows onto distributed resources and is utilized by a broad community of researchers in fields including astronomy, bioinformatics, earthquake science, gravitational-wave physics, and limnology. Deelman is also the Principal Investigator for the CI CoE pilot, providing leadership and support to cyberinfrastructure practitioners at NSF Major Facilities and throughout the research ecosystem. Her interests extend to distributed data management, high-level application monitoring, and resource provisioning in grids and clouds. She has co-edited a book on scientific workflows and authored numerous journal articles and conference publications. Additionally, she established the Workshop on Workflows in Support of Large-Scale Science (WORKS), an annual workshop in the field of scientific workflows.

Research topics

• Computer Science
• Artificial Intelligence
• Computer Security
• Data science
• Risk analysis (engineering)
• Engineering
• World Wide Web
• Database
• Management science

Selected publications

• Artificial Intelligence for Modeling Complex Systems: Taming the Complexity of Expert Models to Improve Decision Making

  ACM Transactions on Interactive Intelligent Systems · 2021 · 80 citations

  Major societal and environmental challenges involve complex systems that have diverse multi-scale interacting processes. Consider, for example, how droughts and water reserves affect crop production and how agriculture and industrial needs affect water quality and availability. Preventive measures, such as delaying planting dates and adopting new agricultural practices in response to changing weather patterns, can reduce the damage caused by natural processes. Understanding how these natural and…

  PublisherOA PDFDOI

• The Workflow Trace Archive: Open-Access Data From Public and Private Computing Infrastructures

  IEEE Transactions on Parallel and Distributed Systems · 2020 · 33 citations

  Realistic, relevant, and reproducible experiments often need input traces collected from real-world environments. In this work, we focus on traces of workflows-common in datacenters, clouds, and HPC infrastructures. We show that the state-of-the-art in using workflow-traces raises important issues: (1) the use of realistic traces is infrequent and (2) the use of realistic, open-access traces even more so. Alleviating these issues, we introduce the Workflow Trace Archive (WTA), an open-access arc…

  DOI

• High-performance computing at a crossroads

  Science · 2025-02-20 · 14 citations

  article1st authorCorresponding

  Long-term plans and comprehensive vision are needed.

  PublisherDOI

• A terminology for scientific workflow systems

  Future Generation Computer Systems · 2025-06-24 · 12 citations

  articleOpen access
  PublisherOA PDFDOI

• Large Language Models for Anomaly Detection in Computational Workflows: From Supervised Fine-Tuning to In-Context Learning

  2024-11-17 · 12 citations

  articleSenior author

  Anomaly detection in computational workflows is critical for ensuring system reliability and security. However, traditional rule-based methods struggle to detect novel anomalies. This paper leverages large language models (LLMs) for workflow anomaly detection by exploiting their ability to learn complex data patterns. Two approaches are investigated: (1) supervised fine-tuning (SFT), where pretrained LLMs are fine-tuned on labeled data for sentence classification to identify anomalies, and (2) i…

  PublisherDOI

Recent grants

• STCI: Middleware for Monitoring and Troubleshooting of Large-Scale Applications on National Cyberinfrastructure

  NSF · $1.9M · 2009–2013

• Collaborative Research: EAGER: VisDict - Visual Dictionaries for Enhancing the Communication between Domain Scientists and Scientific Workflow Providers

  NSF · $100k · 2021–2023

• SI2-SSI: Pegasus: Automating Compute and Data Intensive Science

  NSF · $2.5M · 2017–2023

Frequent coauthors

• Karan Vahi

  University of Southern California

  137 shared

• Rafael Ferreira da Silva

  Oak Ridge National Laboratory

  114 shared

• Gideon Juve

  94 shared

• Gaurang Mehta

  Institute and Faculty of Actuaries

  92 shared

• Mats Rynge

  University of Chicago

  78 shared

• Anirban Mandal

  University of North Carolina at Chapel Hill

  77 shared

• Carl Kesselman

  University of Southern California

  73 shared

• G. Bruce Berriman

  72 shared

Awards & honors

• 2006 e-Science Best Paper
• 2001 15th Workshop on Parallel and Distributed Simulation Be…
• 1987 Wells College Special Distinction in the field of Mathe…
• AAAS fellow
• IEEE fellow

Similar researchers at University of Southern California

• Ramesh Govindanh-101
• Jonathan Gratchh-82
• Muhao Chenh-74