Teaching Assistant Experiences
CMSC 634: Empirical Research Methods for Computer Science
Instructor: Prof. Michelle Mazurek
A graduate-level introductory course on empirical research methods for computer scientists. Introduction to constructs and methods of measurements, qualitative and quantitative design, experimental, quasi-experimental and non-experimental design, and statistical analysis.
ENTS622: Introduction to Digital Communications
Instructor: Prof. Alejandra Mercado
A graduate-level course on principles of analog and digital communication systems design. This includes analysis of the performance and relative merits of different modulation schemes such as PSK, QAM, and GMSK, spectral analysis, signal processing techniques, filtering, frequency selective fading channels and coherence bandwidth, time varying channels and Doppler spread, and optimum receivers. Also provides hands-on labs where students learn to work with the Ettus B210 software-defined radio, using GnuRadio; for example, students will generate digital signals, and perform pulse-shaping, synchronization, and equalization for different digital modulation schemes.
ENEE322: Signal and System Theory
Instructor: Prof. Carol Espy-Wilson
Concept of linear systems, state space equations for continuous systems, time and frequency domain analysis of signals and linear systems. Fourier, Laplace and Z transforms. Application of theory to problems in electrical engineering.
ENEE380: Electromagnetic Theory
Instructor: Prof. Leonard Taylor
Introduction to electromagnetic fields. Coulomb’s law, Gauss’s law, electrical potential, dielectric materials capacitance, boundary value problems, Biot-Savart law, Ampere’s law, Lorentz force equation, magnetic materials, magnetic circuits, inductance, time varying fields and Maxwell’s equations.
- TA Training and Development Fellow, ECE, UMD, 2016-2017