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Learning Machines and Physical Systems

Concentration Information

This concentration considers the intersection between physical and artificial machines by combining mechanical design and modeling with artificial intelligence, machine learning, and computation. An essential component of this concentration is getting hands-on experience with physical products, sensors, and machines while using computation to inform those products’ design, functioning, and usage. 

Concentration Class Suggestions

Recommended REST subjects6.00
Note: You may only include one introductory/REST subject in your concentration.  The following classes are introductory: 6.0001/6.00, 6.042 (REST)/18.200, 6.004 (REST), and 6.008.
Recommended Core Subjects
2.004 Dynamics and Control II
2.007 Design and Manufacturing
Suggested Concentration Subjects
You are encouraged to select subjects across categories:
Physical systems
  • 2.12 Introduction to Robotics
  • 2.74 Bio-inspired Robotics
  • 2.008 Design and Manufacturing II
  • 2.72 Elements of Mechanical Design
  • 2.79[J] Biomaterials, Tissue Interactions
  • 2.813 Energy, Materials, and Manufacturing
  • 2.14 Analysis and Design of Feedback Control Systems
  • 2.184 Biomechanics and Neural Control of Movement
  • 2.151 Advanced System Dynamics and Control (GRAD)
  • 2.153 Adaptive Control and Connections to Machine Learning (GRAD)
  • 2.152[J] Nonlinear Control (GRAD)
Machine Learning, Artificial Intelligence and Computing
  • 2.791[J] Cellular Neurophysiology and Computing
  • 2.168 Learning Machines (GRAD)  *
  • 6.009 Fundamentals of Programming
  • 6.034 Artificial Intelligence
  • 6.036 Introduction to Machine Learning
  • 6.883 Advanced Topics in Artificial Intelligence
  • 2.122 Stochastic Systems (GRAD) *
  • 2.29 Numerical Fluid Mechanics (GRAD) *
  • 18.05 Intro to Probability & Statistics -OR- 6.041A  Intro to Probability I + 6.041B  Intro to Probability II
  • 18.06 Linear Algebra
  • 18.075 Methods for Scientists and Engineers

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Concentration Advisor

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Faez Ahmed

ABS career development assistant professor of mechanical engineering

Interest Areas

  1. Generative design
  2. Machine learning and optimization for engineering design
  3. Human-AI teams