MATLAB Webinar: Empowering Discovery with Open Code and Open Access AI for Berkeley Lab

Overview

Please join us for a practical webinar designed for researchers at Berkeley Lab interested in making their computational work more transparent, reproducible, and impactful. Learn how the MATLAB platform supports open code practices and the development of open access AI models enabling you to share your work, collaborate across teams, and accelerate discovery. 

• Date:    Wednesday, June 4
• Time:    1:00 PM – 2:30 PM PDT
• Location:   Join Zoom Meeting (link will be sent after registration)

>>REGISTER HERE

Highlights

• Learn how to document, organize, and share reproducible research code  
• See how MATLAB integrates with open-source tools for collaborative research 
• Discover practical examples of open access workflows in scientific computing 

About the Presenters

María Elena Gavilán is a Principal Technical Program Manager at MathWorks, supporting researchers and educators in engineering and science. Given her technical expertise with several engineering tools and languages like C++, Python and MATLAB, Maria supports projects that seek to increase the use of MATLAB alongside Open Source in academic and research projects worldwide, particularly in applications involving AI and physical modeling.  María has extensive industry experience in numerical simulation projects (CFD and FEA) in the automotive and aerospace industries. María holds a BSc in Physics from the National University of Colombia, a MSc in Aeronautics and Astronautics from Purdue University, and an MBA from the University of Illinois at Urbana-Champaign. 

Temo Vekua is the Physics manager at MathWorks with extensive experience in modeling quantum many-body systems.  Before joining MathWorks, Temo worked at the University of Indiana, Bloomington, studying the effects of dualities in low-dimensional systems.  

Reza Fazel-Rezai is a Senior Science and Education Application Engineer at MathWorks.  He holds a Ph.D. in Biomedical Engineering with over 20 years of industry expertise as a senior research scientist and research team manager, and academic experience as the founding Director and tenured Professor of Biomedical Engineering. With over 190 scientific publications, six edited books, and extensive research interests in biomedical signal and image processing, he has become an expert in pattern recognition methods, particularly in machine learning and deep learning approaches. He is passionate about utilizing and sharing his skills and knowledge to assist others in achieving their goals and objectives and helping them succeed.

Please contact Tom McHugh, tmchugh@mathworks.com with any questions.