Teaching
At NYU
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CS-GY 6953 / ECE-GY 7123: Deep Learning
Fall 2020, Spring 2021, Fall 2021
Theory and software tools for deep neural network learning.
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CS-GY 9223 / ECE-GY 9133: Foundations of Deep Learning
Spring 2022
A mathematical treatment of deep learning.
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ECE-GY 6143: Introduction to Machine Learning
Spring 2020, Summer 2020
Theory and software tools for machine learning.
At Iowa State
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CprE 310: Theoretical Foundations of Computer Engineering
Fall 2016, Fall 2017, Spring 2018, Fall 2018, Spring 2019
Overview of several topics in discrete mathematics pertinent to computer science and engineering.
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EE 525X: Data Analytics in Electrical and Computer Engineering
Spring 2016, Spring 2017, Spring 2018
Introduction to a variety of data analysis techniques -- particularly those relevant for electrical and computer engineers -- from a foundational perspective. Topics include techniques for classification, visualization, and parameter estimation, with applications to signals, images, matrices, and graphs.
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EE 324: Signals and Systems II
Fall 2015
Techniques for signal analysis (including Laplace transforms and z-transforms) and applications to filter design and feedback systems.
At MIT
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6.006: Introduction to Algorithms
Spring 2015 (along with Piotr Indyk and Yuan Zhou)
Introduction to mathematical modeling of computational problems. Topics include common algorithmic paradigms, data structures, and hands-on problem solving.
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6.042: Mathematics for Computer Science
Spring 2014 (along with Albert Meyer)
Topics in discrete mathematics, directed towards computer science and engineering majors, that are typically not covered in a normal calculus or algebra curriculum.