EE 235: Molecular and Cellular Engineering Lab (BIOE 301A)
The first half of the course teaches practical applications of biotechnology and molecular bioengineering including recombinant DNA techniques, molecular cloning, microbial cell growth and manipulation, and library screening. The second half of the course covers advanced methods including high-throughput sequencing, proteomics, cytometry and other advanced techniques. Emphasis is on experimental design and data analysis.
Terms: Win
| Units: 3
EE 235A: Analytical Methods in Biotechnology I
This course provides fundamental principles underlying important analytical techniques used in modern biotechnology. The course comprises of lectures and hands-on laboratory experiments. Students will learn the core principles for designing, implementing and analyzing central experimental methods including polymerase chain reaction (PCR), electrophoresis, immunoassays, and high-throughput sequencing. The overall goal of the course is to enable engineering students with little or no background in molecular biology to transition into research in the field of biomedicine.
Last offered: Winter 2024
| Units: 3
EE 236A: Modern Optics
Geometrical optics; lens analysis and design, aberrations, optical instruments, radiometry. ray matrices. Wave nature of light; polarization, plane waves at interfaces and in media with varying refractive index, diffraction, Fourier Optics, Gaussian beams. Interference; single-beam interferometers (Fabry-Perot), multiple-beam interferometers (Michelson, Mach-Zehnder).
Terms: Aut
| Units: 3
Instructors:
Congreve, D. (PI)
;
Gallegos, A. (TA)
EE 236B: Guided Waves
Maxwell's equations, constitutive relations. Kramers-Kronig relations. Modes in waveguides: slab, rectangular, circular. Photonic crystals, surface plasmon modes. General properties of waveguide modes: orthogonality, phase and group indices, group velocity dispersion. Chirped pulse propagation in dispersive media and its connection to Gaussian beam propagation. Time lens. Waveguide technologies: glass, silicon, III-V semiconductor, metallic. Waveguide devices: fibers, lasers, modulators, arrayed waveguide gratings. Scattering matrix description of passive optical devices, and constraints from energy conservation, time-reversal symmetry and reciprocity. Mode coupling, directional couplers, distributed-feedback structures. Resonators from scattering matrix and input-output perspective. Micro-ring resonators. Prerequisites:
EE 236A and
EE 242 or familiarity with differential form of Maxwell's equations.
Terms: Win
| Units: 3
Instructors:
Fan, S. (PI)
;
Abrashuly, A. (TA)
EE 236C: Lasers
Atomic systems, spontaneous emission, stimulated emission, amplification. Three- and four-level systems, rate equations, pumping schemes. Laser principles, conditions for steady-state oscillation. Transverse and longitudinal mode control and tuning. Exemplary laser systems: gas (HeNe), solid state (Nd:YAG, Ti:sapphire) and semiconductors. Elements of laser dynamics and noise. Formerly
EE231. Prerequisites:
EE 236B and familiarity with modern physics and semiconductor physics. Recommended:
EE 216 and
EE 223 (either may be taken concurrently).
Terms: Spr
| Units: 3
Instructors:
Heinz, T. (PI)
;
Mathew, A. (TA)
EE 237: Solar Energy Conversion
This course will be an introduction to solar photovoltaics. No prior photovoltaics knowledge is required. Class lectures will be supplemented by guest lectures from distinguished engineers, entrepreneurs and venture capitalists actively engaged in solar industry. Past guest speakers include Richard Swanson (CEO, SunPower), Benjamin Cook (Managing Partner at NextPower Capital) and Shahin Farshchi (Partner, Lux Capital). Topics Include: Economics of solar energy. Solar energy policy. Solar cell device physics: electrical and optical. Different generations of photovoltaic technology: crystalline silicon, thin film, multi-junction solar cells. Perovskite and silicon tandem cells. Advanced energy conversion concepts like photon up-conversion, quantum dot solar cells. Solar system issues including module assembly, inverters, micro-inverters and microgrid. No prior photovoltaics knowledge is required.
Terms: Spr
| Units: 3
EE 237L: Solar Energy Conversion Laboratory
EE 237L is fabrication extension to
EE 237: Solar Energy Conversion. Students will fabricate and test photovoltaic devices according to modern practice. They will utilize Stanford Nanofabrication Facilities to construct a solar cell and measure its performance under ideal and real-world conditions. Students will gain experience in semiconductor fab, solar cell measurements, and presenting photovoltaic data.
Terms: Spr
| Units: 2
Instructors:
Congreve, D. (PI)
;
Casey, E. (TA)
EE 238: Introduction to Fourier Optics
Fourier analysis applied to optical imaging. Theoretical topics include Fourier transform and angular spectrum to describe diffraction, Fourier transforming properties of lenses, image formation with coherent and incoherent light and aberrations. Application topics will cover image deconvolution/reconstruction, amplitude and phase pupil engineering, computational adaptive optics, and others motivated by student interest. Prerequisites: familiarity with Fourier transform and analysis,
EE 102 and
EE 142 or equivalent.
Last offered: Spring 2022
| Units: 3
EE 242: Electromagnetic Waves
This course will provide an advanced treatment of electromagnetic waves in free space and media. The first part of the course will cover reflection, refraction, resonators, photonic crystals, and waveguides. The second part will cover finite-difference time-domain (FDTD) computation and introduce students to commercial FDTD software. The third part will focus on an analysis of EM waves in matter. The fourth part will cover potentials, Green's functions, far-field radiation, near-field radiation, antennas, and phased arrays. In lieu of a final exam, students will perform a group project demonstrating theoretical and application proficiency in a topic of their choosing. Homeworks and the final project will tie into real world applications of electromagnetics and utilize scientific computing (Matlab, Mathematica, or Python).
Terms: Win
| Units: 3
Instructors:
Choi, J. (PI)
;
Azzouz, M. (TA)
EE 244: Hardware Accelerators for Machine Learning (CS 217)
This course explores the design, programming, and performance of modern AI accelerators. It covers architectural techniques, dataflow, tensor processing, memory hierarchies, compilation for accelerators, and emerging trends in AI computing. This course will cover modern AI/ML algorithms such as convolutional neural nets, and Transformer-based models / LLMs. We will consider both training and inference for these models and discuss the impact of parameters such as batch size, precision, sparsity and compression on the accuracy of these models. Students will become familiar with hardware implementation techniques for using parallelism, locality, and low precision to implement the core computational kernels used in ML. Students will develop intuitions to make system-level trade-offs to design energy-efficient accelerators. Students will read recent research papers and complete a final design project.
Terms: Spr
| Units: 3-4