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Integrating Machine Learning in Aerospace and Mechanical applications

  • 1.  Integrating Machine Learning in Aerospace and Mechanical applications

    Posted 09 Aug, 2025 08:43

    Integrating Machine Learning in Aerospace and Mechanical applications

    Date & Time: August 14th, 2025, 5:00-6:00 pm EST

    Registration: https://aiaa.zoom.us/webinar/register/WN_3Jr6NWwUS3669h5TLFRn_A

    The AIAA New England Section is organizing an expert webinar session. Come and listen to

     Dr. Justin Hodges talk about interesting applications of Machine Learning surrogates in aerospace and mechanical applications. 

    In this talk, Dr. Justin Hodges covers relevant use cases, considerations, and fundamentals for industry-relevant machine learning (ML) surrogates working alongside simulation work (e.g. CFD). After setting the stage for 'Geometric Deep Learning', a modern class of ML surrogates relevant to our simulation data and endeavors, we cover a variety of important functionality for modern ML surrogates to be useful in industrial applications (other than simply being accurate). From covering a variety of fundamental academic steps in ML surrogate pipelines to discussing emerging topics with precise detail (GenAI for engineering), we look forward to an active discussion on relevant burning questions expert engineers have in mind when considering integrating ML surrogates into their projects. Here's a link to his book - https://geni.us/JaXp

     

    Speaker bio:

    Dr. Justin Hodges is the AI/ML technical specialist at Siemens Digital Industries Software. Justin did his bachelors, masters, and PhD at the University of Central Florida in Mechanical Engineering (with gas turbine heat transfer and aerodynamics focus).  Justin knew his career vector would be folding AI into engineering disciplines after his first professional experience with AI in 2017.  This career defining moment was a research internship in Princeton whereby he patented a novel Artificial intelligence-based COPD assessment approach, which combined airflow simulations through the lungs, traditional imaging methods, and patent data into an AI framework. Since joining industry in 2018, Justin has self-published a hands-on book which helps mechanical/aerospace engineers adopt AI/ML technologies into their current work.

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    Shreyas Hegde
    Pratt & Whitney
    Middletown CT
    (919)519-6719
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