Behzad Samadi

Behzad Samadi

Director of Innovation and Engagement

Advanced Intelligent Systems

Biography

I can help you form and manage an agile technical team to make proof-of-concept prototypes. I have a strong background in numerical algorithms and convex optimization. I have made mathematical models of physical systems such as vehicle dynamics systems (steering, suspension and braking), automotive engines and robots. I have years of education and experience in Electrical, Mechanical, Automotive, Control Engineering and applied mathematics.

I was a Senior Research Engineer at Maplesoft for more than 6 years working on symbolic methods, acausal modeling, algorithm optimization and automatic code generation with Toyota, Japan and the Toyota Technical Center in Ann Arbor. I have also been an Assistant Professor for three years. I used to teach Mechatronics to undergraduate and Convex Optimization to graduate students.

Currently, I lead the software team for the development of connected autonomous vehicles and mobile robotics at AIS. I have also acted as the product owner of a connected autonomous electric tow tractor and a UV-C disinfection robot. In addition, I work with the Model Based Systems Engineering (MBSE) and product management teams. The main business model of AIS is Robot as a Service (RaaS). Therefore, cloud services are a large part of the development process. In my role as the lead of the software team, I need to make sure that the embedded software, autonomy software and the web services teams work smoothly together based on automated tests.

Interests
  • Machine Learning
  • Automatic Code Generation
  • Model Predictive Control
  • Reinforcement Learning
  • Convex Optimization
  • Fault Detection, Isolation and Accommodation
  • Estimation Theory
Education
  • PhD in Mechanical Engineering, 2008

    Concordia University

  • MSc in Electrical Engineering, 1999

    Amirkabir University of Technology

  • BSc in Electrical Engineering, 1996

    Sharif University of Technology

Projects

Computational Tools for Piecewise Affine Systems

PWATOOLS is a set of tools for the analysis and design of piecewise affine (PWA) systems.

Model based automatic code generation for nonlinear model predictive control

Symbolic computation methods are employed to generate optimized C code for nonlinear model predictive controllers.

Recent Publications

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(2015). Piecewise-affine approximations for a powertrain control verification benchmark. ARCH14-15. 1st and 2nd International Workshop on Applied Verification for Continuous and Hybrid Systems.

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(2014). A sum of squares approach to backstepping controller synthesis for piecewise affine and polynomial systems. International Journal of Robust and Nonlinear Control.

(2013). Active front-steering control of a sport utility vehicle using a robust linear quadratic regulator method, with emphasis on the roll dynamics. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering.

(2012). A convex formulation of controller synthesis for piecewise-affine slab systems based on invariant sets. 2012 IEEE 51st Annual Conference on Decision and Control (CDC).

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(2012). PWATOOLS: A MATLAB toolbox for piecewise-affine controller synthesis. American Control Conference (ACC).

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