Graduate Courses
- Analog Integrated Circuits: Nonswitching aspects of analog integrated circuits using bipolar or CMOS technologies. Biasing, DC behavior, small signal behavior. Emphasis on use of physical reasoning, identification of circuit functions, and use of suitable approximations to facilitate understanding and analysis.
- Advanced Microelectronics Processing: Introduction to unit step processes in semiconductor manufacturing. Introduction to various semiconductor processes, with emphasis on process and device integration issues for major integrated circuit processes. Basic circuit and design techniques including subsystem design and device scaling. Fundamentals of chip layout and integrated circuit design methodology for solid state circuits.Theory of diffusion, oxidation, deposition and processing, etc. and process integration.
- Design Oriented Analysis of Electronic Circuits: Emphasis on obtaining analytical approximations for maximum insight into circuit behavior. Extra element theorem, feedback theorem, low-entropy design equations, frequency-domain measurement of loop gains, impedances.
- Solid State Devices: Basic semiconductor physics and materials, PN junctions, metal semiconductor junctions/contacts. BJTs and MOSFETs, device operation, terminal behavior and frequency response, device models.
- Digital System VLSI Design: Standard cell layout, gate and switch level simulation, level mode sequential circuits. VLSI testing, CAD tools, laboratory projects.
- Advanced Logic Synthesis and Verification Algorithms: Mathematical foundations of Boolean Algebras, elementary finite automata theory, exact algorithms and heuristic procedures for synthesis and minimization of two and multi-level logic, mathematical models of sequential systems and algorithm for synthesis and verification of finite state machines, and algorithms for technology mapping.
- Random Processes for Engineering Applications: Probability, random variables, stochastic processes, correlation functions and spectra with applications to communications, control, and computers.
- Electronic Packaging Principles: Introduction to problems encountered at all levels
of
packaging: thermal, mechanical, electrical, reliability, materials and
system integration. Future trends in packaging.
- Computer-Aided Logic Design: Tabular
minimization of single and multiple output Boolean functions, NMOS and
CMOS realizations, synthesis of sequential circuits, RTL description,
laboratory exercises.
- Electromagnetic Field
Theory: Time-harmonic fields; fundamental theorems and
concepts;
rectangular and circular waveguides and resonators; apertures in ground
planes, cylinders, and wedges; scattering by cylinders and wedges.
- Quantum Mechanics for Optical
Physics: Elements of quantum mechanics used in
laser, semiconductor and quantum optics. Mathematical formalism and
basic postulates of quantum mechanics. Particle in a box, periodic
potentials, harmonic oscillator, angular momentum, atomic structure,
perturbation theory, identical particles.
- Advanced Topics in Microelectronics and
Solid-State Devices: Specialized topics, SiGe HBTs, bandgap
engineering, low injection profiles, effects of temperature, percentage
Ge, and thickness of SiGe layer.
- Linear Algebra: Vector spaces, linear
transformations and matrices, eigenvalues, bilinear forms, orthogonal and
unitary transformations. Graduate-level requirements include more
extensive problem sets or advanced projects.
- Topics in Applied Math:
Inverse Problems in Geoscience and Engineering: Least Squares,
Singular Value Decomposition, Adjoints, Gauss/Markov Estimation, Recursive
improvement, Kriging, Kalman filter, and other methods.
- Principles and Methods of Applied
Mathematics: Boundary value problems; Green's functions,
distributions, Fourier transforms, the classical partial differential
equations (Laplace, heat, wave) of mathematical physics.
- Numerical Analysis: Error analysis,
solution of linear systems and nonlinear equations, eigenvalue
interpolation and approximation, numerical integration, initial and
boundary value problems for ordinary differential equations, optimization.