Teaching

ML / Robotics / Computer Vision Teaching Materials

• Module 1: Linear Algebra Foundations, Fast Nearest Neighbors
• Module 2: Numerical Linear Algebra Direct Methods, Conjugate Gradients, Least Squares
• Module 3: SVMs and Optimization Kernel Trick, Gauss-Newton Optimization, Convex Opt.
• Module 4: State Estimation Bayes Filter, Lie Groups & Rigid Body Kinematics
• Module 5: Geometry and Camera Calibration Stereo, Epipolar Geometry, Visual Odometry, ICP
• Module 6: Convolutional Neural Networks Conv Layer Backprop, GANs, Pytorch Tutorial, JAX Tutorial
• Module 7: Reinforcement Learning Policy Gradients

Courses Taught at Georgia Tech (2018-2021)

• CS 6476 Computer Vision, Spring 2021, Teaching Assistant to Professor James Hays, Georgia Institute of Technology.

  Assignments:

  • Project 1: Convolution & Hybrid Images (Pytorch) [.zip] [PDF]
  • Project 2: SIFT Local Features (Pytorch) [.zip] [PDF]
  • Project 3: Camera Calibration [.zip] [PDF]
  • Project 4a: Stereo w/ Deep Learning (Pytorch) [.zip] [PDF]
  • Project 4b: Stereo w/ Deep Learning (Pytorch) [.zip] [PDF]
  • Project 5: Recognition w/ Deep Learning (Pytorch) [.zip] [PDF]
  • Project 6: Semantic Segmentation w/ Deep Learning (Pytorch) [.zip] [PDF] [colab]
    

• CS 4476 Computer Vision, Fall 2019, Teaching Assistant to Professor Frank Dellaert, Georgia Institute of Technology.

  Assignments:

  • Project 1: Image Filtering and Hybrid Images [html] [.zip]
  • Project 2: Local Feature Matching (Harris & SIFT as Deep Nets) [html] [.zip]
  • Project 3: Camera Projection Matrix & Fundamental Matrix Estimation w/ RANSAC [html] [.zip]
  • Project 4: Depth Estimation using Stereo [html] [.zip]
  • Project 4a: Depth Estimation using Stereo [html] [.zip]
  • Project 4b: Depth Estimation using Stereo [html]
  • Project 5: Scene Recognition w/ Bag of Words [html] [.zip]
  • Project 6: Scene Recognition w/ Deep Learning [html] [.zip]

• CS 6476 Computer Vision, Fall 2018, Teaching Assistant to Professor James Hays, Georgia Institute of Technology.