Ali Cafer Gurbuz, PhD

Teaching

I have been regularly teaching in the emphasis area of Signal Processing and Machine Learning — from core undergraduate courses to graduate electives I designed and introduced.

At NC State University (2025– )

Complex plane, eigenvalue equation, and differential equation illustration

ECE 220 — Analytical Foundations for ECE

Course Offered: Spring 2025, Spring 2026

This course builds the core mathematical foundations for electrical and computer engineering: complex numbers and the complex exponential, linear algebra, and differential equations — the analytical language behind circuits, signals, systems, and machine learning.

Signals and systems illustration

ECE 301 — Linear Systems

Course Offered: Fall 2025

Representation and analysis of signals and linear time-invariant systems in continuous and discrete time: convolution, Fourier series and transforms, sampling, and transform-domain analysis — the foundation of modern signal processing.

At Mississippi State University (2018–2024)

11 courses with 400+ students total, plus 12 directed individual studies.

Mathematical foundations of machine learning

ECE 4990/6990 — Mathematical Foundations of Machine Learning

Course Offered: Spring 2020, Spring 2021 (designed and offered first time at MSU)

Provides senior, masters, and first-year Ph.D. students in engineering and computing with a solid mathematical background of modern data science in linear algebra, signal processing, and applied probability. Covers the mathematical foundations of both supervised and unsupervised machine learning — so students can understand, extend, and develop learning techniques rather than only applying black-box tools.

Statistical signal processing

ECE 8433 — Statistical Signal Processing

Course Offered: Spring 2019

Introduces graduate students to the mathematical ideas forming the basis of modern statistically-based analysis of signals and systems. Students learn fundamental tasks such as detection, classification, and estimation with the underlying statistical and mathematical properties — foundations of many current machine learning and deep learning approaches.

Signals and systems

ECE 3443 — Signals and Systems

Course Offered: Spring 2019, Fall 2020, Spring 2022, Fall 2022, Fall 2023

Basic concepts of signals, system modeling, and system classification; time-domain and frequency-domain approaches to the analysis of continuous and discrete systems; tools and techniques to analyze systems and data, with modern simulation software.

Principles of modern radar book cover

ECE 4433/6433 — Introduction to Radar

Course Offered: Fall 2021

Basic principles of radar and key radar sub-systems; radar range equation; radar cross section; clutter; radar measurements of range and velocity; basic waveforms, matched filtering, pulse compression, and stretch processing; ambiguity functions and coded waveforms; Doppler processing and MTI filtering; principles of radar target detection.

Electromagnetics illustration

ECE 3313 — Electromagnetics I

Course Offered: Fall 2018

Fundamental laws and concepts governing electromagnetics: static and dynamic EM fields, energy, and power; EM fields and waves within and at the boundaries of media; EM radiation and propagation in space and within transmission lines.

Additional Classes

  • Smart Farming: Data-Enabled Agriculture (FYE 1001) — created this freshman-year experience class with two collaborating instructors in agriculture departments, introducing data science to freshmen in the context of agriculture applications.
  • Directed Individual Studies (ECE 7000) — 12 taught; specialized graduate-level classes for one student.

Capstone Project Advising

  • "L.O.T.U.S. — Land Ordnance Termination Unmanned System" (2022)
  • "Beatwave: Design of a Low-Cost EEG Device" (2022)
  • "OvenMax" (2021)
  • "Flying Livestock Inventory Registrar" (2019) · "PlantBot" (2019) · "LYRA — Proactive Forklift Safety System" (2019)
  • "Cornhole" (2018)

Prior to MSU — TOBB University, Turkey (2009–2016)

Undergraduate Classes

  • ELE 201 Circuit Analysis I (and Lab)
  • ELE 202 Circuit Analysis II
  • ELE 371 Signals and Systems
  • ELE 474 Digital Signal Processing
  • ELE 480 Introduction to Estimation
  • ELE 495 Undergraduate Project

Graduate Classes

  • ELE 465/565 Fundamentals of Radar Signal Processing
  • ELE 571 Detection and Estimation (established and offered first time at the university)
  • ELE 670 Radar Signal Processing (established and offered first time at the university)
  • ELE 675 Array Signal Processing (established and offered first time at the university)
  • ELE 576 Special Problems

Graduate Advising

4+ Ph.D. and 14+ M.S. (thesis) students graduated as (co-)major professor; 2 postdoctoral researchers mentored; 40+ graduate committees served. See Theses & Dissertations for the full list.

Current Students

Student Honors

  • NASA FINESST Awardee (2023)
  • IEEE IGARSS Best Student Paper Finalist (2022)
  • DoD SMART Scholarship · NSF Scholarship for Service
  • MSU Graduate Research Symposium 1st Place — Engineering, Ph.D. category (2022); MSU ECE Research Symposium Best Presentation (2022)
  • MSU Bagley College of Engineering Undergraduate Research Award (2020) · MSU ECE Best TA Award (2020)