Teaching

Lecturer/Instructor

• Coursera: Introduction to Machine Learning (Summer 2018 - present)
  • Designed the materials (IPython notebook tutorials) and recorded videos for Duke’s deep learning Coursera.
• +Data Science (Summer 2018 - Spring 2020)
  • Instructor for EGR190: Introduction to Machine Learning Methods and Practice and numerous In-Person Learning Experiences: Introduction to TensorFlow, Introduction to PyTorch, PyTorch for Computer Vision, Deep Convolutional Object Detection, Implementing Generative Adversarial Networks in TensorFlow.
• Duke Natural Language Processing School (Winter 2020)
  • Taught hands-on software sessions on natural language processing in PyTorch.
• Duke Machine Learning School (Summer 2018, Winter 2019)
  • Taught hands-on TensorFlow sessions to a class of 150, including logistic regression, convolutional neural networks, generative adversarial networks, reinforcement learning, and natural language processing.
• Infinia ML Machine Learning Bootcamp (Summer 2018)
  • Taught hands-on TensorFlow sessions to a class of 100 software developers
• Duke-Tsinghua Machine Learning Summer School (Summer 2017)
  • Taught evening sessions to a class of 150 introducing TensorFlow, multilayer perceptrons, convolutional neural networks, and variational autoencoders.

Teaching Assistantships

• ECE 590-16: Introduction to Deep Learning (Fall 2018)

• ECE 581: Random Signals and Noise (Fall 2017)

• ECE 381: Fundamentals of Digital Signal Processing (Fall 2016)

• ECE 110: Fundamentals of Electrical and Computer Engineering (Fall 2014, Spring 2015)

• Math 216: Linear Algebra and Differential Equations (Fall 2012, Spring 2013)

Project Management

• Data+: Finding Space Junk with the World’s Biggest Telescopes (Summer 2020)