MATLAB Users Group

The MATLAB Users Group provides opportunities for campus MATLAB users to learn more about using MATLAB, help each other, and learn more about research and teaching being done at Princeton using MATLAB. To be added to the group's mailing list or to volunteer to help with planning and putting on future events, send e-mail to [email protected]
 

Past events

Thursday, March 8, 4:30 pm - 6:00 pm
120 Lewis Science Library, Washington Road & Ivy Lane

From medical diagnosis, speech and handwriting recognition to automated trading and movie recommendations, machine learning techniques are being used to make critical business and life decisions every moment of the day. In this session, we explore the fundamentals of machine learning using MATLAB. Working  with a range of classification models, we will perform model assessment and comparisons.

Dr. Elvira Osuna-Highley is a Senior Customer Success Engineer at MathWorks, where she supports faculty in their teaching and research with MATLAB. Prior to joining MathWorks, she was a Lecturer in the Computational Biology department at Carnegie Mellon University. Dr. Osuna-Highley holds a doctorate in Biomedical Engineering from Carnegie Mellon University.


Wednesday, March 29, 4:30 – 6:00 pm
Vis Lab, 347 Lewis Science Library, Washington Road & Ivy Lane

Melanie Weber, Applied and Computational Mathematics
 

Neural Networks are among the hottest topics in machine learning and their applications in a wide range of fields have contributed to major scientific advances.  MATLAB’s Neural Networks Toolbox offers a rich selection of methods that allow for implementing a variety of network architectures and concepts. While we will review the functionality of the toolbox, we also want to understand basic concepts underlying the implementation of neural networks.

For this session, we will implement one of the early neural network models – the Hopfield network [Hopfield; 1984] – from scratch. Until today, the model is widely used for memory modeling in Neurosciences. We will take associative memory modeling as an example for our implementation and discuss applications in biomedical research [Weber, Maia, Kutz; 2016].


Wednesday, February 1, 4:30 – 6:00 pm, 138 Lewis Science Library
Yibin Zhang, Mechanical and Aerospace Engineering


Many differential equations cannot be solved in closed form – that is, a clean, analytical solution is often lacking in real-world settings. A number of numerical methods for solving these equations currently exist depending on the problem to be tackled. The aim of this workshop is to learn to apply suitable numerical approximations to different systems of ordinary differential equations (ODEs) in MATLAB, beyond the popular ODE45, which is used in many classroom settings.

A brief introduction to the mathematics will be given, although the focus will be on the practical application of numerical methods to solve common academic problems rather than an exploration of the theoretical background. The user does not need previous knowledge of the ODE solver suite in order to participate. There will be a 20-minute talk followed by a help/discussion session. Please bring a laptop with MATLAB (2005 or later) installed if you would like to follow along. 
 
Yibin is a 4th year doctoral candidate in the Mechanical and Aerospace Engineering department at Princeton University.


Wednesday, September 28, 2016, 4:30 - 7:30 pm  

120 Lewis Science Library, Washington Road & Ivy Lane Join us for a special Kick-Off Event titled "Princeton Speaks MATLAB" on September 28th at 4:30 pm. The newly-formed group hopes to ignite participation and build a support community among MATLAB users.

This event is open to undergraduate and graduate students, postdocs and researchers at Princeton and its affiliates. There will be presentations from faculty and researchers, a poster session, open discussions and a keynote talk from MathWorks.