Teaching
EECE5644: Introduction to Machine Learning and Pattern Recognition.
Course covering foundational models and algorithms as well as applications for machine learning, designed for both undergraduate and graduate students. Taught Summer 2023.
EECE7323: Numerical Optimization Methods.
Course presenting the fundamental theory and algorithms for nonlinear and convex optimization for graduate students. Taught Fall 2016, Spring 2020, 2021, 2022.
EECE7366: Analysis and Design of Data Networks.
Course focusing on analysis and system design of communication networks for graduate students. Taught Fall 2012, Fall 2015, Spring 2019.
EECE7337: Information Theory.
Course which presents information theory as the intellectual foundation for digital communication and networking. Taught Fall 2011, Fall 2013.
EECE3468: Noise and Stochastic Processes.
Course on probability and stochastic processes for Electrical and Computer Engineering undergraduates. Taught Spring 2012, 2013, 2014, 2015 and 2016.
EENG 444/ENAS 944: Digital Communication Systems.
Course which presents the fundamentals of digital communication foradvanced undergraduate and graduate students. Taught Spring 2002, Fall 2002, Fall 2003, Fall 2006, Fall 2008, Fall 2009 and Fall 2010.
ENAS 964: Communication Networks.
Course focusing on analysis and system design of communication networks for advanced undergraduate and graduate students. Taught Spring 2004 and Spring 2010.
EENG 454/STAT 364/AMTH 364: Information Theory.
Course which presents information theory as the intellectual foundation for digital communication and networking. Taught Spring 2003 and 2005.
ENAS 530: Nonlinear and Convex Optimization.
Course presenting the fundamental theory and algorithms for nonlinear and convex optimization for graduate students. Taught Fall 2005.
EENG 201: Semiconductors, Computers, and Communications.
Course which introduces the core areas in Electrical Engineering to beginning undergraduates. Co-taught with Yiorgos Makris and Jung Han, Fall 2003.
ENAS 496: Probability and Stochastic Processes.
Course focusing on stochastic processes for engineering applications geared toward advanced undergraduate and graduate students. Taught Spring 2006, Spring 2007, Spring 2009, Spring 2011.
Advanced Topics in Signal Processing: Analysis and Design of Data Networks.
Master of Science in Communications Engineering (MSCE) Program. Course focusing on analysis and system design of communication networks for graduate students. Taught as Guest Professor, Summer 2013.
6.451: Principles of Communications II.
Served as assistant to Professor G. David Forney for advanced course on digital communication and coding for graduate students. Taught Spring 2001.