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Teaching in the Neural Engineering Laboratory

The Computational Neurobiology Group is engaged in collaborative explorations of the functioning of neurons and networks, using both invertebrate and vertebrate model systems.

Academic Elective Track – Computational Neuroscience

Undergraduate Courses

  • ECE/CS/BE/BioSci 4590 Computational Neuroscience
  • Computational Neuroscience is an emerging interdisciplinary field that links the diverse fields of biological sciences and quantitative sciences. ECE/BioSci 4580 is an interdisciplinary course that is team-taught by faculty from biology and engineering to introduce undergraduates to this exciting and growing field.
  • Flyer: ECE/CS/BE/BioSci  4590 Computational Neuroscience
  • Additional Information: NAE Grand Challenge in Engineering – Reverse Engineer the Brain; What is computational neuroscience? + Course requirements for an interdisciplinary minor in computational neuroscience + Coming soon – Undergraduate Certificates in Neural Engineering

Graduate Courses

Academic Elective Track – Control Systems

Undergraduate Courses

  • ECE/BE 4310 Feedback Control of Systems
  • See pdf document linked to ‘More Info.’ above for description of our undergraduate elective track in Control Systems

Graduate Courses

  • ECE 7380 Introduction to Digital Signal Processing
  • ECE 8320 Nonlinear Systems
  • MAE 7720 Modern Control
  • MAE 8740 Robust Control
  • MAE 8750 Nonlinear Control
  • MAE/ECE 8780 State Variable Methods in Automatic Control

Professional Development Courses

Annual Summer Neuroscience Workshop: Experiments and Models to Teach Undergraduate Neuroscience

(Impact: 68 biology and psychology faculty from 2- and 4-year colleges; Also see OUTREACH page)

ECE 8110/8120 Preparing Advanced Professionals I/II (1 credit hour each)

(Impact: 271 Engineering MS & PhD students)

    • This two-semester seminar course sequence (1 cr hr each; do not depend on each other, i.e., can be taken independently) covers several topics relevant to advanced graduate students, such as findings from cognitive science on ‘how people learn’, professional skills, personal skills, proposal writing, and the science of teaching and learning. Includes seminars by experts.
    • ECE 8110.   The topics in Part I include the following:
      • pedagogy – latest from cognitive science and learning theory, based on material from ‘How People Learn’ (The National Academy Press, 1999 – first book reading);
      • the importance of professional skills (2nd book reading – ‘The 7 Habits of Highly Effective People’ by Stephen Covey).
      • The book readings are interspersed with seminars by outside speakers on topics such as how to be an effective teacher, how does a university function, how do leading industries perform research; life in academic vs. industry, etc.
      • The requirements for the courses are attendance, reading assigned materials, participation in class discussions, and submission of materials developed for student presentations.
    • ECE 8120.  The topics in Part II include the following:
      • The second course in the two-semester sequence (both independent of each other) continues the format in Part I with a combination of group discussions using book readings and seminars by experts.
      • A major focus in Part II of the course is on ‘How to write an effective proposal’, spanning about 4 weeks.
      • As part of that segment, students review model proposals, model reviews, and the segment culminates with a ‘hands-on’ proposal writing session.
      • This is followed by a focus on the findings from psychology/cognitive science on ‘learning’ using the book ‘Make it Stick – the Science of Successful Learning” by Brown, Roediger III, and McDaniel.
      • The requirements for the courses are attendance, reading assigned materials, participation in class discussions, and submission of materials developed for student presentations.

Modeling Software Used in Courses


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