Teaching

Quantum engineering education at FIU

Courses emphasize intuition, rigorous modeling, Python/Jupyter workflows, Qiskit, simulations, recorded modules, and no-cost materials through FIU's quantum-computing curriculum.

Courses and Mentoring

Undergraduate, graduate, special-topics, senior design, and dissertation research activities in quantum engineering and computational electromagnetics, including FIU's first undergraduate/graduate quantum-computing sequence.

EEE 4423: Introduction to Quantum Computers

Undergraduate introduction to quantum information concepts, circuits, gates, algorithms, and hands-on Qiskit workflows.

EEE 6429: Advanced Quantum Computers

Graduate-level quantum computing with deeper treatment of algorithms, noise, hardware constraints, and simulation.

EEL 6020: Numerical Analysis of Electrical Devices

Numerical methods and computational modeling for electrical devices, fields, resonators, and engineering systems.

EEL 6931: Quantum Technologies and Materials / Special Topics

Special topics in quantum technologies, materials, photonics, sensing, and emerging electromagnetic platforms.

Quantum Nanophotonics Special Topics

Advanced topics in light–matter interaction, nanophotonic resonators, metasurfaces, polaritons, and quantum optical systems.

Senior Design and Dissertation Research

Mentored projects in simulation, measurement, documentation, quantum devices, metamaterials, and technical writing.

Teaching Tools

Courses use Qiskit, Python, Jupyter notebooks, simulations, recorded modules, and no-cost materials to make quantum engineering practical, reproducible, and accessible.

Research Practice Taught in the Lab

QTM Lab training emphasizes the daily habits that turn coursework and early projects into reproducible research.

Use the Research Loop

Define the question, explain why it matters, reproduce a known baseline, choose the smallest testable step, analyze carefully, and write while the result is fresh.

Document Everything

Record raw data, parameters, software versions, code commits, assumptions, units, boundary conditions, calibration notes, and figure-generation scripts.

Build Professional Outputs

Progress is measured through evidence: validated simulations, calibrated measurements, clean figures, shared notes, draft sections, abstracts, code, datasets, and manuscripts.

Write Early

Start with the motivation, outline, related work, methods, and figure plan. A strong paper grows from a clear sequence of figures and controls.

Prepare for Meetings

Each research meeting should answer four questions: what was done, what was found, what blocks progress, and what will happen next.

Featured YouTube Lectures

Selected public lectures and teaching videos connected to QTM Lab research and quantum engineering education.

Introduction to Python for Physics

Python, Jupyter notebooks, plotting, arrays, and computational habits for physics and engineering workflows.

Dipole and Yagi-Uda Antennas Using ANSYS HFSS

Hands-on antenna simulation tutorial for electromagnetic modeling and RF design practice.

Electromagnetic Radiation and Antennas

Lecture coverage of radiation concepts, antenna behavior, and practical electromagnetic interpretation.

Six Postulates of Quantum Mechanics

Quantum-mechanics foundations for students entering quantum computing and quantum engineering.

Quantum Circuits, Two-Qubit Operations, and Entanglement

Quantum-circuit elements, multi-qubit operations, and the role of entanglement in quantum information.

Quantum Teleportation Algorithm

Algorithmic structure and circuit-level interpretation of quantum teleportation.

Quantum Nonreciprocity with Nonlinearity and Weyl Semimetals

Invited lecture recorded for Polytechnique Montréal, connecting nonlinear platforms, Weyl semimetals, and quantum-compatible nonreciprocal response.

Scattering Anomalies: Recent Breakthroughs and Quantum Applications

FIU KFSCIS seminar on scattering anomalies, embedded eigenstates, and quantum-relevant applications in resonant wave systems.