Upcoming Seminar

MATLAB Academic Tour 2017

Machine Learning and rapid prototyping with low-cost hardware: Arduino and Raspberry Pi

ISCTE - Instituto Universitário de Lisboa
J.J. Laginha Auditorium
3 April 2017
09:30 - 13:00


We will explore basic Machine Learning methods with MATLAB. Using example-based learning, we will review typical workflows for supervised learning (classification and regression) and unsupervised learning techniques (clustering). We will show pattern recognition algorithms and build predictive models from data using the following methods:

  • Clustering: finding groups of data
  • Classification: building models that predict groups for new observations
  • Regression: building models that predict from continuous observations,/li>

We will cover several techniques such as K-means, decision trees, neural networks and lineal regression. We will also briefly discuss more advanced topics like Deep Learning.

Furthermore, we will present examples of project-based learning with MATLAB, Simulink and low-cost hardware (Arduino, Raspberry Pi, LEGO, smartphones...) to develop, simulate and test algorithms by experimenting with resources that are easily available to students.

We will provide attendee certifications.

Who Should Attend

This event is recommended for teachers, researchers and students who are interested in knowing more about MATLAB capabilities for Machine Learning and/or are looking into rapid prototyping using low-cost hardware platforms for different domains and applications, like teaching courses or doing research.

About the Presenters

Ascension Vizinho-Coutry joined MathWorks in 2005 as pre-sales engineer. Today she is a principal academic evangelist at MathWorks, addressing modern STEM teaching methods. Before joining MathWorks, Ascension was a senior application engineer at Cadence and also worked for Philips Consumer Communications in Le Mans (France) as a research engineer in wireless communications (UMTS). Ascension was a research assistant at the University of Sheffield (UK) in the computer science department from 1998 t0 2000.

Ascension obtained her Ph.D. in applied mathematics from the University of Sheffield and a French diploma in engineering and applied mathematics from the Institut National des Sciences Appliquées, Rouen.

Carlos Sanchis holds Master degrees in Industrial Engineering and Project Management. He has over 8 years of experience in technical roles and project management in the areas of: simulation, R&D and electronics in Iberdrola, Hewlett-Packard, Universidad Politécnica de Valencia and DevStat Statistical Consulting. As the academic technical specialist for Spain and Portugal at MathWorks, he collaborates with the main universities of the region in educational innovation projects, and curriculum development with MATLAB and Simulink.


Time Title
30 min MATLAB use @ Campus
60 min Machine Learning with MATLAB
30 min Break
60 min Project-based learning with MATLAB, Simulink and low-cost Hardware
15 min Q&A