MATLAB with Python for AI

Overview

Do you work in a cross functional team that uses and collaborates in both MATLAB and Python?  Perhaps you have a TensorFlow or PyTorch model from a published research group and want to import that into MATLAB? These two presentations will cover specific tools for AI development and deployment collaboration, with the first webinar discussing the interoperability between MATLAB/Simulink and Python in both directions with a focus on AI. 

The second will focus specifically on Deep Learning and show how you can take full advantage of the MATLAB ecosystem and integrate it with resources developed by the open-source community with TensorFlow and PyTorch. This workflow enables the integration of AI models created within Python into Simulink-enabled model-based design workflows. For example, using verification and validation with model-based tests allows you to certify a golden reference model from which you can generate code for a wide variety of platforms.

About the Presenters

Dr Emmanuel Blanchard is a senior application engineer at MathWorks who first joined the company as a training engineer in 2014. He focuses on data analytics. Prior to joining MathWorks, he was a Lecturer in Mechatronic Engineering at the University of Wollongong. He holds a PhD in Mechanical Engineering from Virginia Tech. He also worked as a Systems / Controls Engineer at Cummins Engine Company and as a research assistant in several research institutions in California and Virginia. 

Dr Peter Brady is a Senior Application Engineer with MathWorks striving to accelerate our customer’s engineering and scientific computing workflows across maths, statistics, finance and machine learning. Prior to joining MathWorks, Peter worked in computational fluid and thermodynamics as well as high performance computing for a number of defence and civil contractors as well as a few universities. He has worked in fields as diverse as cavitation, wave/turbulence interactions, rainfall and runoff, nano-fluidics, HVAC and natural convection including scale out cloud simulation techniques. Peter holds a doctorate in free surface computational fluid dynamics and a Bachelor of Civil Engineering both from the University of Technology Sydney and is a Chartered Practicing Engineer in Australia.