MathWorks at MIT IAP 2014

MathWorks is hosting six sessions during MIT's Independent Activities Period (IAP) 2014. Join us to learn how you can use MATLAB and Simulink for technical computing and application development in engineering, math, and science.

Tuesday, January 28

Explore, Visualize, and Analyze Your Data with MATLAB

10:00 a.m.–12:00 p.m.
Room 4-163

In this session, you will learn how to use MATLAB to gain insight into your engineering and scientific data. With the MATLAB language, interactive tools, and built-in math functions, you can explore and model your data, build customized analyses, and share your discoveries with others.

Through product demonstrations, you will see how to:

  • Access data from files and spreadsheets
  • Manage complex and messy data
  • Plot data and customize figures
  • Perform statistical analysis and fitting
  • Generate reports and build apps

This session is for students, faculty, and researchers who are new to MATLAB. Experienced MATLAB users may also benefit from the session, which features capabilities from recent releases of MATLAB.

About the Presenter
Vipresh Gangwal ( works in the Engineering Development Group at MathWorks. He has an M.S. in electrical engineering from University of Southern California (USC) and a B.E. in electrical engineering from University of Pune, India. His research at USC focused on probabilistic robotics involving computer vision for perception and planning for robots.

Introduction to MATLAB: Problem Solving and Programming

1:00–5:00 p.m.
Room 4-163

MATLAB is a high-level language that allows you to quickly perform computation and visualization through easy-to-use programming constructs. This hands-on lab presents the essentials you need to use MATLAB for your classes or research.

In this session, we import historical temperature data collected in the Northern Hemisphere from an external file, plot the data over time, then perform some analysis to view the data trend to determine if global warming is happening. You’ll learn how to write a MATLAB script and publish it to a format for sharing, such as HTML. You’ll also learn how to write your own MATLAB functions, use flow control, and create loops.

By the end of the session, you’ll have learned to create an application in MATLAB.

Key topics include:

  • Navigating the MATLAB desktop
  • Working with variables in MATLAB
  • Calling MATLAB functions
  • Importing and extracting data
  • Visualizing data
  • Conducting computational analysis
  • Fitting data to a curve
  • Automating analysis with scripts
  • Publishing MATLAB programs
  • Programming in MATLAB

Note: Attendees should bring a laptop to this hands-on lab.

About the Presenters
Laura Proctor ( develops and delivers training targeted to academic users and creates web-based content for online learning. She joined MathWorks in 2009 as an application support engineer and in 2010 transferred to the Customer Training Group. Laura has a B.S. in mathematics and a B.S. in mechanical and aerospace engineering with a minor in physics from the University of Missouri. She also has an M.S. in mechanical engineering and an M.S. in computation for design and optimization from MIT. Her graduate research included simulating and optimizing satellite trajectories, electronic circuit design and implementation, biomimetic design and prototyping, computational methods applied to nanostructural ion flow, and course material design with an emphasis on visual learning.

Eoin Moore ( delivers MATLAB training to academic and corporate audiences and also develops online self-paced MATLAB courses. He holds a B.S. in physics from the University of Massachusetts and an M.S. in physics from the University of California San Diego. His graduate research involved the analysis of plasmas, including turbulent flow and nonlinear dynamics.

Wednesday, January 29

Introduction to Simulink for Dynamic Systems Modeling and Simulation

9:00 a.m.–12:00 p.m.
Room 35-225

Simulink is an environment for multidomain simulation and Model-Based Design for dynamic and embedded systems. It provides an interactive graphical environment and a customizable set of block libraries that let you design, simulate, implement, and test a variety of time-varying systems in multiple domains, including communications, controls, and signal, video, and image processing.

Using specific, real-world examples, we show you how to model and simulate dynamic systems as part of a top-down design workflow. We start by modeling and simulating the differential equations governing the system dynamics using an approach based on first principles. We then show how to use additional domain-specific libraries for system design and architectural modeling to create more detailed models as physical networks of components. We present examples from a variety of domains, including electrical and mechanical, and for a variety of applications, including both control systems and digital signal processing.

Highlights include:

  • Creating a new model from scratch
  • Using libraries of predefined blocks
  • Creating your own reusable subsystems
  • Incorporating MATLAB code into Simulink models
  • Combining Simulink with physical modeling libraries

About the Presenters
Carlos Osorio ( is a principal applications engineer at MathWorks focusing on control system design and implementation. Carlos received a B.S. from the Pontificia Universidad Catolica del Peru and an M.S. from the University of California at Berkeley, both in mechanical engineering. He specializes in automatic control systems and vehicle dynamics. Before joining MathWorks in October 2007, he worked in the automotive industry in the Advanced Chassis Technology Department at Visteon Corporation, where he was involved in the development and implementation of prototype electronic active and semi-active suspensions and steer-by-wire and brake-by-wire systems for passenger vehicles.

Rick Rosson ( is a senior applications engineer specializing in signal processing and communications systems. He supports a wide variety of MATLAB and Simulink products, including Signal Processing Toolbox, DSP System Toolbox, and MATLAB Coder, in industries such as communications, electronics, semiconductors, aerospace, and automotive. His current professional interests include digital signal processing, digital communications, analog and mixed-signal system design, and embedded C code generation. Prior to joining MathWorks, Rick worked for 12 years in manufacturing management and process improvement, primarily in the automotive and electronics industries. Rick has an M.S. in electrical engineering from Boston University and an M.S. in management from the MIT Sloan School of Management.

MATLAB and Simulink with Raspberry Pi: A Hands-On Workshop on Hardware Support

1:00–4:00 p.m.
Room 35-225

Addressing the growing need in curriculum and research for low-cost, easy-to-use hardware and software environments, this session describes the built-in support in MATLAB and Simulink for prototyping, testing, and running Simulink models on Raspberry Pi.

Simulink includes the capability to program Arduino, Raspberry Pi, LEGO MINDSTORMS NXT, and other low-cost hardware platforms. This hands-on workshop introduces the hardware support capabilities in Simulink. Participants develop, simulate, and test custom algorithms and implement the code on an embedded system from within the Simulink environment. Lab modules include examples of video and image processing algorithms, from very simple video in/out handling to more sophisticated processing such as object recognition and edge detection. The workshop provides practical hands-on experience and gives attendees an understanding of the potential for use in the classroom, research, and student projects.

Participants will:

  • Design, simulate, and test custom algorithms in Simulink
  • Implement these algorithms on embedded hardware
  • Discover the ease of using Simulink to program


  • Necessary software and Raspberry Pi Kits will be made available to attendees for the duration of the workshop.
  • We have a limited class size for this workshop. Register now and we will contact you to confirm your seat.
  • Faculty, staff and graduate students will be given preference as attendees.

About the Presenter
Sumit Tandon ( joined MathWorks in 2007 and worked on Simulink and code generation products before transferring to application engineering in 2011. Previous work experience includes a year as a software developer in COBOL and mainframe technology. He has a B.E. in electrical engineering from Jadavpur University, India, and an M.S. in electrical engineering from University of Texas at Arlington. His master’s thesis focused on cancer research, and he developed a simulator for biopsy using concepts of computer graphics, computer vision, and haptics.

Thursday, January 30

Machine Learning with MATLAB

10:00 a.m.–12:00 p.m.
Room 4-231

Machine learning techniques are often used for data analysis and decision-making tasks such as forecasting, classification of risk, estimating probabilities of default, and data mining. However, implementing and comparing machine learning techniques to choose the best approach can be challenging. In this session, you will learn about several machine learning techniques available in MATLAB and how to quickly explore your data, evaluate machine learning algorithms, compare the results, and apply the best technique to your problem.

Highlights include unsupervised and supervised learning techniques such as:

  • K-means and other clustering tools
  • Neural networks
  • Decision trees and ensemble learning
  • Naïve Bayes classification
  • Linear, logistic, and nonlinear regression

About the Presenter
Abhishek Gupta ( joined Technical Support at MathWorks in 2007 and later moved to the Application Engineering Group. He primarily focuses on academia and the financial services industry. He has an M.S. in mechanical engineering from Texas A&M University. His research involved the development of mathematical models of heat exchangers using MATLAB and Simulink.

Accelerating MATLAB Algorithms and Applications

1:00–3:30 p.m.
Room 4-231

Analyze data, develop algorithms, and create models and applications – all more quickly. In this session we will present strategies and techniques to accelerate your MATLAB computations, and highlight ways that you can use MATLAB with HPC environments without needing to be an expert in parallel programming with CUDA or MPI.

The acceleration topics covered include:

  • Parallel computing on multicore processors and GPUs
  • Scaling computations to clusters and clouds
  • Generating and incorporating C-based functions that can be scaled with your code base

We will describe the underlying acceleration technology, and explain when it is most applicable.

About the Presenter
Adam Filion ( joined the MathWorks Engineering Development Group in 2010 and moved to Application Engineering in 2012. He holds a B.S. and M.S. in aerospace engineering from Virginia Tech. His research involved nonlinear controls of spacecraft and periodic orbits in the three-body problem.