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ViewAttendees 3

Pre-Meeting Workshop

Room 317 B

PRE-MEETING WORKSHOP: Python and Machine Learning for Plant Pathologists

PRE-MEETING WORKSHOP: Python and Machine Learning for Plant Pathologists, Supported by BASF and Valent BioSciences

Saturday, August 2, 2025
8:00 AM - 12:00 PM HST
Location: Room 317 B

    Organizer(s)

  • NG

    Nikita Gambhir

    Plant Pathologist - Fungicide Discovery Biology
    FMC Corp.
    Newark, Delaware, United States

  • DH

    Daniel Winter Heck

    Sr Extension Associate
    Cornell University
    Riverhead, New York, United States

  • CN

    Camila Nicolli, PhD

    Assistant Professor - Extension Plant Pathologist
    University of Arkansas
    Stuttgart, Arkansas, United States

    • Speaker(s)

  • JM

    Josiah M.K Marquez, Ph.D.

    Plant Pathologist
    Hawaii Department of Agriculture and Biosecurity
    Aiea, Hawaii, United States

  • HC

    Huaijin Chen, Ph.D.

    Assistant Professor, Computer Science
    University of Hawaiʻi at Mānoa

  • XW

    Xing Wei, PhD

    Postdoctoral Researcher
    University of Hawaiʻi at Mānoa
    Honolulu, Hawaii, United States

The Introduction to Python for Plant Pathologists Workshop organized by CLARE and Epidemiology committee in 2022 gained much interest from the APS community with 70+ registered participants. However, it was conducted fully virtually without the hands-on collaborative environment that enriches interactive learning experiences. To improve the hands-on learning experience, this in-person workshop will focus on how Machine Learning can be used to analyze and interpret complex data sets, particularly in the context of plant disease detection and management. With a mix of theoretical and hands-on sessions, participants will learn how to utilize Python for data manipulation, visualization, and implementing machine learning algorithms. Given machine learning's increasing relevance in data science and its application in various fields, this workshop is applicable to a broad APS audience, ranging from those new to programming to experienced researchers seeking to integrate it into their work. The sessions will be structured to accommodate varying levels of expertise, ensuring that every attendee gains valuable insights regardless of their prior experience with Python. Participants will learn how to interpret data for informed decision-making and how to standardize methodologies for broader applicability across global plant health networks.

Target Audience: Students, Epidemiologists, Post-Docs, Bioinformaticians, Precision Agriculture Professionals, Plant Pathologists Interested in Data Analyses, and Data Scientists.

Supported by BASF and Valent BioSciences

Learning Objectives:

  • Understand the basics of Python and machine learning, including syntax, data types, and control structures.
  • Apply Python and machine learning in manipulating and visualizing large datasets relevant to plant pathology
  • Explore the use of Python in implementing basic machine learning algorithms for predictive analysis in plant disease management.