Shlizerman's Research Group on
Data-driven Dynamical Systems
Data driven Dynamical Systems
   Teaching
2020:
NeuroAI Seminar (EE 598 & AMATH 500C)
Intro To Differential Equations And Applications (AMATH 351)
2019:
Discrete Time Linear Signals and Systems (EE 341)
Practical Introduction to Neural Networks (ECE 596)
Data-driven Neural Networks Seminar (EE 598 & AMATH 500C)
2018:
Scientific Computing Undergraduate (UW AMATH 481 A)
Scientific Computing Graduate (UW AMATH 581 A,C,D)
Scientific Computing EDGE (Online) (UW AMATH 581 B)
Data-driven Neural Networks Seminar (EE 598 & AMATH 500C )
Engineering Entrepreneurial Capstone II (EE 498)
Engineering Entrepreneurial Capstone I (EE 497)
2017:
Data-driven Neural Networks Seminar (EE 598 & AMATH 500C)
Engineering Entrepreneurial Capstone II (EE 498)
Engineering Entrepreneurial Capstone I (EE 497)
2016:
Engineering Entrepreneurial Capstone II (EE 498)
Engineering Entrepreneurial Capstone I (EE 497)
2015:
Scientific Computing Undergraduate (UW AMATH 481 A)
Scientific Computing Graduate (UW AMATH 581 A,C,D)
Scientific Computing EDGE (Online) (UW AMATH 581 B)
2014-2015:
Scientific Computing Undergraduate (UW AMATH 481 A)
Scientific Computing Graduate (UW AMATH 581 A,C,D)
Scientific Computing EDGE (Online) (UW AMATH 581 B)
2013-2014:
Scientific Computing Undergraduate (UW AMATH 481 A)
Scientific Computing Graduate (UW AMATH 581 A,C,D)
Scientific Computing EDGE (Online) (UW AMATH 581 B)
2012-2013:
Scientific Computing Undergraduate (UW AMATH 481 A)
Scientific Computing Graduate (UW AMATH 581 A,C,D)
Scientific Computing EDGE (Online) (UW AMATH 581 B)
2011-2012:
Applied Partial Differential Equations (UW - AMATH 353)
Introduction to Scientific Computing (UW - AMATH 301 A,B)
2010-2011:
Introduction to Scientific Computing (UW - AMATH 301 A,B,C)
2009-2010:
Introduction to Scientific Computing (UW - AMATH 301 A,B)
2008-2009:
Dynamical Systems and Modeling (WIS)
2007:
Students Course (WIS)
Graduate Course: Practical Introduction to Neural Networks.

New Graduate Course: Practical Introduction to Neural Networks aimed to provide practical and fundamental skills to perform research with neural networks.

Data-driven Neural Networks Seminar

Data-driven Neural Networks Graduate Seminar (ECE 598N and AMATH 500C; Fall, Winter, Spring).

Ordinary Office Hour in Scientific Computing Course. Fun is always guaranteed.

Office Hours turn into hackathons in the Scientific Computing course :)

Neuromorphic circuits

Students design neuromorphic circuits in Engineering Entrepreneurial Capstone course :)

Assortment of Videos Prepared
by Students in the Scientific Computing Course