Courses Developed / Instructed

EEEE 547/647 Artificial Intelligence Explorations

  • Taught in Fall 2021

  • Latest Textbook: S. Russel, P. Norvig, "Artificial Intelligence: A modern approach," 4th edition, Pearson, 2021.

  • Description: The course explores a variety of artificial intelligence techniques, and their applications and limitations. Some of the AI topics to be covered in this course are agents, search, heuristics, logic, Bayesian networks, and machine learning.

  • Course website

EEEE 595/695 Optimization Methods for Engineers

  • Description: Formulating and solving optimization problems; Feasibility sets and convexity; Optimization methods: optimality criteria, closed-form solution, iterative solvers; Stochastic optimization; Applications in Machine Learning, Signal Processing, Communications, and other areas of engineering.

  • Course website

EEEE 484 Communication Systems

  • Taught in Fall 2019, Spring 2020, Fall 2020, Spring 2021

  • Latest Textbook: J. Proakis, M. Salehi, "Fundamentals of Communication Systems" 2nd edition, Pearson, 2014.

  • Description: This course introduces the fundamental principles of communication systems. Topics include: Noise through linear systems, analog amplitude modulation/demodulation, analog angle modulation/demodulation, binary detection, optimum receiver design, matched filters, ASK, PSK, and FSK modulation for digital communication.

  • Course website

EEEE 594/694 Sensor Array Processing

  • Taught in Spring 2018, Spring 2019, Spring 2020

  • Originally developed and introduced by P. Markopoulos

  • Latest Textbook: S. Haykin, "Adaptive Filtering Theory," 5th edition, Pearson, 2014; H. Van Trees, "Optimum Array Processing," Wiley, 2002.

  • Description: Principles of sensor-array processing, with a focus on wireless communications. Topics covered: uniform linear antenna arrays (inter-element spacing and Nyquist sampling in space); beamforming, array beam patterns, array gain, and spatial diversity; interference suppression in the absence of noise (null-steering); optimal beamforming in AWGN; optimal beamforming in the presence of colored interference; estimation of filters from finite measurements and adaptive beamforming; demodulation with antenna arrays (multiple users and AWGN); demodulation in CDMA (multiple users and AWGN); ML and subspace methods for direction-of-arrival estimation; demodulation with antenna arrays in CDMA systems (space-time processing); introduction to mmWave beamforming and massive arrays.

  • Course website

EEEE 593/693 Digital Data Communications

  • Taught in Fall 2015, Fall 2016, Spring 2019

  • Lectures and assignments designed by P. Markopoulos

  • Latest Textbook: John G. Proakis and Masoud Salehi, "Communication Systems Engineering," 2nd edition, Prentice-Hall, 2005.

  • Description: Principles and practices of modern digital data communication systems. Topics include pulse code transmission and error probabilities, M-ary signaling and performance, AWGN channels, band-limited and distorting channels, filter design, equalizers, optimal detection for channels with memory, synchronization methods, non-linear modulation, and introduction to multipath fading channels, spread spectrum, and OFDM.

  • Course website

EEEE 592/692 Communication Networks

  • Taught in Spring 2016, Spring 2017, Fall 2017, and Fall 2018

  • Lectures and assignments designed by P. Markopoulos

  • Latest Textbook: James F. Kurose and Keith W. Ross, "Computer Networking: A Top-Down Approach," 7th edition, Pearson, 2017.

  • Description: This course covers communication networks in general and the internet in particular. Topics include layer service models, circuit and packet switching, queuing, pipelining, routing, packet loss and more. A five-layer model is assumed and the top four levels are covered in a top-down approach: starting with the application layer, going down through the transport layer to the network layer, and finally the data link layer.

  • Course website

EEEE 105 Freshman Practicum Laboratory

  • Taught in Fall 2017

  • Description: Introduction to the practice of electrical engineering including understanding laboratory practice, identifying electronic components, operating generic electronic instruments, building an electronic circuit (Wein Bridge oscillator), measuring and capturing an electronic waveform, schematic entry, modeling, and simulation of an electronic circuit (SPICE or equivalent), analyzing a waveform using a commercial software package (MATLAB), and building and studying an amplitude modulation radio receiver. This studio-style lab course emphasizes a learn-by-doing approach to introduce the student to electrical engineering design practices and tools used throughout the undergraduate program and professional career. Each student will prototype and build a functioning electronic circuit.

  • Course website

EEEE 499 Cooperative Education

  • Student advisor for Co-Op education since Fall 2017.

  • Description: One semester of work experience in electrical engineering.

Teaching Awards

  • Exemplary Performance in Teaching, KGCOE, RIT, 2018.

  • Nominated and shortlisted for Richard and Virginia Eisenhart Provost's Award for Excellence in Teaching, RIT, 2018.