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Justin M. Wozniak

Computer Scientist 4

Wozniak researches and develops workflow systems for high performance computing.

Biography

Justin Wozniak joined Argonne as a postdoc in 2008 and has been a member of the Data Science and Learning Division since its founding in 2018.  He has had a joint appointment at the University of Chicago since 2009, and is currently a Scientist-at-Large.

Wozniak designs and implements workflow systems for scientific applications and deep learning workloads, combining techniques from high-performance computing and distributed computing.  He has extensive experience integrating advanced computing techniques in collaboration with the experimental and simulation sciences.

Research Interests

  • High-level programming models for concurrency at large scale
  • Distributed computing, fault tolerance, and recovery
  • Workflow systems for simulation, experiment, and learning
  • Simulation of computer systems
  • Integrating computing with databases, provenance, and analysis

Education

  • Ph.D., Computer Science and Engineering, University of Notre Dame, 2008.
  • MMath, University of Waterloo, ON, 2003.
  • B.S., Mathematics and Computer Science, University of Illinois at Urbana Champaign, 2000,
    minors in Chemistry and Latin.

Awards

Activities

  • Co-Chair, XLOOP: Workshop on Large-scale Experiment-in-the-Loop Computing @ SC
  • Co-Organizer, ERROR: Workshop on E-science ReseaRch leading tO negative Results @ eScience
  • Co-Organizer, WoWoHa: DOE Workflow Workshop and Hackathon

Key Publications

  • A population data-driven workflow for COVID-19 modeling and learning
    Jonathan Ozik, Justin M. Wozniak, Nicholson Collier, Charles M. Macal, and Mickaël Binois, International Journal of High Performance Computing Applications, 2021.
  • High-bypass learning: Automated detection of tumor cells that significantly impact drug response
    Justin M. Wozniak, Hyunseung Yoo, Jamaludin Mohd-Yusof, Bogdan Nicolae, Nicholson Collier, Jonathan Ozik, Thomas Brettin, and Rick Stevens
    Proc. Machine Learning in HPC Environments @ SC 2020.
  • MPI jobs within MPI jobs: A practical way of enabling task-level fault-tolerance in HPC workflows
    Justin M. Wozniak, Matthieu Dorier, Robert Ross, Tong Shu, Tahsin Kurc, Li Tang, Norbert Podhorszki, and Matthew Wolf.
    Future Generation Computing Systems 101, 2019.
  • CANDLE/Supervisor: A workflow framework for machine learning applied to cancer research
    Justin M. Wozniak, Rajeev Jain, Prasanna Balaprakash, Jonathan Ozik, Nicholson Collier, John Bauer, Fangfang Xia, Thomas Brettin, Rick Stevens, Jamaludin Mohd-Yusof, Cristina Garcia Cardona, Brian Van Essen, and Matthew Baughman. BMC Bioinformatics, 2018.
  • Turbine: A distributed-memory dataflow engine for high performance many-task applications
    Justin M. Wozniak, Timothy G. Armstrong, Ketan Maheshwari, Ewing L. Lusk, Daniel S. Katz, Michael Wilde, and Ian T. Foster.  Fundamenta Informaticae 28(3), 2013.

A more complete list is maintained here: https://web.cels.anl.gov/~woz/papers.html