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Jungha Woo

Jungha Woo is a Software Engineer in the Research Computing at the Purdue University. His Ph.D. work included analyzing investors’ behavioral biases in the U.S. stock markets and implementing profitable strategies utilizing irrational behaviors. His experience and interests lie in AI/ML models, model coupling, the statistical analysis of scientific data, and software development. Jungha develops scientific software to help high-performance computational communities run models and predict the execution time of jobs.

Jungha has mentored four graduate, and undergraduate in research projects.


  • Ph.D., Electrical and Computer Engineering, Purdue University, West Lafayette, IN
  • M.S., Computer Science, Purdue University, West Lafayette, IN
  • B.S., Computer Science, Yonsei University, South Korea

Selected Projects

  • AnalytiXIN, a strategic program facilitated by the Central Indiana Corporate Partnership (CICP). (PI/co-PI(s): Teresa Meyer, Dongyan Xu, and Ananth Grama. ). Project Title: AnalytixIN: Advanced Manufacturing. 01/2022-11/2024. $1.6 million, Role: Software Engineer 
    • My contribution to this project: Researched, designed, and implemented artificial intelligence and machine-learning models (recurrent neural network) for advanced predictive maintenance at a motor manufacturing company in Indiana. Using hundreds of real-time sensor data, I constructed machine learning models that predict the number of car defects in an hour for the manufacturer’s paint shop.
      When a sudden hike in the defect ratio is predicted, it alerts the staff, enabling preventive actions to resolve the possible root cause of the defects
  • INFEWS/T2 NSF Award Number: 1855937 (PI/co-PI(s): Richard Lammers, Christopher Kucharik, Thomas Hertel, Wilfred Wollheim, David Johnson ). Project Title: INFEWS/T2: Identifying Sustainability Solutions through Global-Local-Global Analysis of a Coupled Water-Agriculture-Bioenergy System. NSF. 07/24/2019-07/31/2022. Role: Software Engineer
    • My contribution to this project: Researched, designed, and developed an automated pipeline that connects multiple computational models to work together for studying long-run sustainability issues in the global food-water-environment nexus. Given future sustainability scenarios, an economic model computes the future agricultural prices and their effects on the water balances on the land. Researchers study the changes in agricultural prices and water balance by varying factors such as tax, nitrate leaching, food demands, disposable income, etc. This work resulted in a generally applicable model coupling framework called C3F that can also be used for other research projects. With the C3F framework, complex simulation codes are packaged in a self-contained virtual container that others can run easily. This simplifies how collaborators share and connect their simulation models to study more complex environmental problems. The execution of coupled models is accelerated by running on Purdue’s Anvil supercomputer, which is part of the national research cyberinfrastructure ecosystem, Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS).
  • GeoEDF: NSF Award Number: 1835822 (PI/co-PI: Xiaohui Carol Song, Venkatesh Merwade, Jack Smith, Uris Lantz Baldos, Jian Jin. ). Project Title: Framework: Data: HDR: Extensible Geospatial Data Framework towards FAIR (Findable, Accessible, Interoperable, Reusable) Science. NSF. 10/1/2018-09/30/2024. Role: Software Engineer.
    • My contribution to this project: Designed and developed several data connectors and processors that make data acquisition, wrangling, and processing easier for researchers. I developed a data connector that downloads earth observation data from NASA and USGS, and a processor that calculates the agricultural prices using downloaded satellite datasets. This work enabled scientists to focus on their search questions by automating their data acquisition and computations. These data connectors and processors can be connected to form workflows. They are open source and can be accessible publicly.
  • IsoMAP: NSF Award Number: 1565128 (PI/co-PI(s): Gabriel Bowen, Hannah Vander Zanden, Lan Zhao). Project Title: Collaborative Research: ABI Development: ORIGIN: Origin Inference from Geospatial Isotope Networks. NSF. 07/20/2016-01/31/2022. Role: Software Engineer.
    • My contribution to this project: design, and implemented Isoscapes Modeling Analysis and Prediction (IsoMAP) portal, the science gateway delivering a dynamic, online workspace for spatial analysis, modeling, and prediction of stable isotope ratio variation in the natural environment (isoscapes). I developed a suite of web-based GIS (Geographic Information System) and software tools, letting users easily explore, design, and implement statistical and process-based models for isotope distributions. More than 2,300 registered users have used the IsoMAP science gateway for over ten years. Ninety-three papers cited IsoMAP science gateways. IsoMAP has been operational for over ten years and runs about 1,000 experiments annually.
  • PI/co-PI: John-Paul Navarro, Shava Smallen). Project Title: SDIACT-
    234 Enhance Resource Prediction Service showing where jobs would run first.XSEDE (Extreme Science and Engineering Discovery Environment, NSF-funded). 10/1/2015-09/21/2016.
    enhance-resource-prediction-service-showing-where-jobs-would-run-first. Role: Software Engineer.
    • My contribution to this project: Researched the legacy implementation of the Karnak service that predicts how long computational jobs would wait in queues on the supercomputers of the national research cyberinfrastructure before they begin to execute. This system recommends to researchers the best-fit systems on which they may want to run jobs for the fastest execution, like a GPS navigator in a car showing the best routes to the destination. I improved this prediction system by applying the decision tree ensembles technique, resulting in more stable and accurate predictions.

Selected Publications

  • J. Woo, L. Zhao, D. S. Grogan, I. Haqiqi, R. Lammers, and C. X. Song. C3f: Collaborative container-based model coupling framework. In Practice and Experience in Advanced Research Computing, PEARC ’22, New York, NY, USA, 2022. Association for Computing Machinery.
  •  C. X. Song, J. Woo, L. Zhao, D. S. Grogan, I. Haqiqi, and R. B. Lammers. Accelerating Multi-scale Cross-domain Model Linking Using Advanced Cyberinfrastructure. In AGU Fall Meeting Abstracts, volume 2022, pages GC52I–0248, Dec. 2022.
  • J. Woo, L. Zhao, and G. J. Bowen. Streamlining geospatial data processing for isotopic landscape modeling. Concurrency and Computation: Practice and Experience, page e6324, 2021.3336
  • C. Song, R. Kalyanam, L. Zhao, J. Jin, L. Biehl, U. Baldos, R. Campbell, C. Ellis,J. Smith, N. Brewer, et al. Geoedf-an extensible geospatial data framework for fair science. In AGU Fall Meeting Abstracts, volume 2019, pages IN53B–0737, 2019.
  • J. Woo, U. L. C. Baldos, L. Zhao, C. Song, and J. Shin. Simple-G US web application. 2018.
  • J. Woo. Economic and statistical significance of disposition effect and momentum in the US stock market. PhD thesis, Purdue University, 2015.
  • Z. Zhao, J. Woo, and D. Braun. Google web toolkit for ogce gadget based architecture. InProceedings of the 2011 ACM workshop on Gateway computing environments, pages 37–42, 2011.
  • H. Zhang, J. Woo, L. Zhao, D. Braun, C. X. Song, and M. Lakshminarayanan. Domain-specific web services for scientific application developers. In 2010 GatewayComputing Environments Workshop (GCE), pages 1–7. IEEE, 2010.
  • J. Woo, J. Padma, J.-W. Lee, D. Braun, and C. X. Song. Puffin: a fast and efficient web service-based condor job manager. In Proceedings of the 5th Grid ComputingEnvironments Workshop, pages 1–6, 2009.
  • F. Paci, N. Shang, S. Kerr, K. Steuer Jr, J. Woo, and E. Bertino. Privacy-preserving management of transactions’ receipts for mobile environments. In Proceedings of the 8th Symposium on Identity and Trust on the Internet, pages 73–84, 2009.
  • F. Paci, E. Bertino, S. Kerr, A. C. Squicciarini, and J. Woo. An overview of veryidx-a privacy-preserving digital identity management system for mobile devices.J. Softw.,4(7):696–706, 2009.
  • J. Woo, A. Bhargav-Spantzel, A. C. Squicciarini, and E. Bertino. Verification of receipts from m-commerce transactions on nfc cellular phones. In 2008 10th IEEEConference on E-Commerce Technology and the Fifth IEEE Conference on EnterpriseComputing, E-Commerce and E-Services, pages 36–43. IEEE, 2008.
  • F. Paci, E. Bertino, S. Kerr, A. Lint, A. Squicciarini, and J. Woo. Veryidx-a digital identity management system for pervasive computing environments. In IFIPInternational Workshop on Software Technologies for Embedded and UbiquitousSystems, pages 268–279. Springer, 2008.
  • J. Woo and E. Bertino. Receipt management-transaction history based trust establishment. 2007.
  • J. Woo.TRANSACTION HISTORY BASED TRUST ESTABLISHMENT. PhD thesis, Purdue University West Lafayette, 2007.
  • U. Topkara, C. X. Song, J. Woo, and S. P. Park. Connected in a small world: Rapid integration of heterogenous biology resources. In International Workshop on GridComputing Environments, 2007.
  • A. Bhargav-Spantzel, J. Woo, and E. Bertino. Receipt management-transaction history based trust establishment. InProceedings of the 2007 ACM workshop on Digital identity management, pages 82–91, 2007.
  • J. Woo, A. Bhagav-Spantzell, A. C. Squicciarinii, and E. Bertino. Verification of receipts from m-commerce transactions on nfc cellular phones.
  • A. Bhargav-Spantzel, J. Woo, A. C. Squicciarini, and E. Bertino. History based identity verification and management.