printer friendly pageME 326: Collaborative Robotics (CS 339R)
This course focuses on how robots can be effective teammates with other robots and human partners. Concepts and tools will be reviewed for characterizing task objectives, robot perception and control, teammate behavioral modeling, inter-agent communication, and team consensus. We will consider the application of these tools to robot collaborators, wearable robotics, and the latest applications in the relevant literature. This will be a project-based graduate course, with the implementation of algorithms in either python or C++.
Terms: Win
| Units: 3
ME 331A: Advanced Dynamics & Computation
Newton, Euler, D'Alembert (road-map) methods and computational tools for 3D kinematic, force, and motion analysis of multibody systems. Power, work, and energy. Computational solutions of nonlinear algebraic and differential equations governing the static and dynamic behavior of multibody systems.
Terms: Win
| Units: 3
Instructors:
Balachandran, A. (PI)
;
Mitiguy, P. (PI)
;
Algazi, D. (TA)
...
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Instructors:
Balachandran, A. (PI)
;
Mitiguy, P. (PI)
;
Algazi, D. (TA)
;
Jurasius, B. (TA)
;
Skov, S. (TA)
ME 335A: Finite Element Analysis
Fundamental concepts and techniques of primal finite element methods. Method of weighted residuals, Galerkin's method and variational equations. Linear eliptic boundary value problems in one, two and three space dimensions; applications in structural, solid and fluid mechanics and heat transfer. Properties of standard element families and numerically integrated elements. Implementation of the finite element method using Matlab, assembly of equations, and element routines. Lagrange multiplier and penalty methods for treatment of constraints. The mathematical theory of finite elements.
Terms: Win
| Units: 3
Instructors:
Lew, A. (PI)
;
Majumdar, A. (TA)
ME 343: Machine Learning for Computational Engineering. (CME 216)
Linear and kernel support vector machines, deep learning, deep neural networks, generative adversarial networks, physics-based machine learning, forward and reverse mode automatic differentiation, optimization algorithms for machine learning, TensorFlow, PyTorch.
Terms: Win
| Units: 3
Instructors:
Patel, D. (PI)
;
Woringer, P. (TA)
ME 350: Plasma Science and Technology Seminar (AA 296)
Guest speakers present research related to plasma science and engineering, ranging from fundamental plasma physics to industrial applications of plasma.
Terms: Aut, Win, Spr
| Units: 1
| Repeatable
for credit
(up to 99 units total)
Instructors:
Edwards, M. (PI)
;
Hara, K. (PI)
ME 351B: Fluid Mechanics
Laminar viscous fluid flow. Governing equations, boundary conditions, and constitutive laws. Exact solutions for parallel flows. Creeping flow limit, lubrication theory, and boundary layer theory including free-shear layers and approximate methods of solution; boundary layer separation. Introduction to stability theory and transition to turbulence, and turbulent boundary layers. Prerequisite: 351A.
Terms: Win
| Units: 3
Instructors:
Santiago, J. (PI)
;
Jiang, Q. (TA)
ME 364: Optical Diagnostics and Spectroscopy
The spectroscopy of gases and laser-based diagnostic techniques for measurements of species concentrations, temperature, density, and other flow field properties. Topics: electronic, vibrational, and rotational transitions; spectral lineshapes and broadening mechanisms; absorption, fluorescence, Rayleigh and Raman scattering methods; collisional quenching. Prerequisite: 362A or equivalent.
Terms: Win
| Units: 3
Instructors:
Hanson, R. (PI)
;
Clees, S. (TA)
ME 366: Light and Plasma (PHOTON 366)
An introduction to the science and applications of laser-plasma interactions. The first part of the course will discuss the fundamental concepts and analytic, computational, and experimental tools for understanding the linear and nonlinear propagation of light in plasma, including dispersion relations, ionization and absorption mechanisms, stimulated scattering and light-driven waves, and relativistic optics. The second part of the course will use these tools to understand a variety of existing and under-development applications of laser-plasma interactions and high-power beams, including EUV lithography, laser diagnostics, directed energy, laser-wakefield accelerators, laboratory astrophysics, and inertial confinement fusion.Previous coursework in plasma physics, optics, or electromagnetism, or discussion with the instructor, is recommended.
Terms: Win
| Units: 3
Instructors:
Edwards, M. (PI)
;
Ou, K. (TA)
ME 368A: Biodesign Innovation: Needs Finding and Concept Creation (BIOE 374A, MED 272A)
In this two-quarter course series (
BIOE 374A/B,
MED 272A/B,
ME 368A/B,
OIT 384/5), multidisciplinary student teams identify real-world unmet healthcare needs, invent new health technologies to address them, and plan for their implementation into patient care. During the first quarter (winter), students select and characterize an important unmet healthcare problem, validate it through primary interviews and secondary research, and then brainstorm and screen initial technology-based solutions. In the second quarter (spring), teams select a lead solution and move it toward the market through prototyping, technical re-risking, strategies to address healthcare-specific requirements (regulation, reimbursement), and business planning. Final presentations in winter and spring are made to a panel of prominent health technology experts and/or investors. Class sessions include faculty-led instruction and case studies, coaching sessions by industry specialists, expert guest lecturers, and int
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In this two-quarter course series (
BIOE 374A/B,
MED 272A/B,
ME 368A/B,
OIT 384/5), multidisciplinary student teams identify real-world unmet healthcare needs, invent new health technologies to address them, and plan for their implementation into patient care. During the first quarter (winter), students select and characterize an important unmet healthcare problem, validate it through primary interviews and secondary research, and then brainstorm and screen initial technology-based solutions. In the second quarter (spring), teams select a lead solution and move it toward the market through prototyping, technical re-risking, strategies to address healthcare-specific requirements (regulation, reimbursement), and business planning. Final presentations in winter and spring are made to a panel of prominent health technology experts and/or investors. Class sessions include faculty-led instruction and case studies, coaching sessions by industry specialists, expert guest lecturers, and interactive team meetings. Enrollment is by application only, and students are required to participate in both quarters of the course. Visit
http://biodesign.stanford.edu/programs/stanford-courses/biodesign-innovation.html to access the application, examples of past projects, and student testimonials. More information about Stanford Biodesign, which has led to the creation of 50 venture-backed healthcare companies and has helped hundreds of student launch health technology careers, can be found at
http://biodesign.stanford.edu/.
Terms: Win
| Units: 4
Instructors:
Denend, L. (PI)
;
Edmonds, Z. (SI)
;
Makower, J. (SI)
...
more instructors for ME 368A »
Instructors:
Denend, L. (PI)
;
Edmonds, Z. (SI)
;
Makower, J. (SI)
;
Venook, R. (SI)
;
Sunier, S. (TA)
ME 370B: Energy Systems II: Modeling and Advanced Concepts
Development of quantitative device models for complex energy systems, including fuel cells, reformers, combustion engines, and electrolyzers, using thermodynamic and transport analysis. Student groups work on energy systems to develop conceptual understanding, and high-level, quantitative and refined models. Advanced topics in thermodynamics and special topics associated with devices under study. Prerequisite: 370A.
Terms: Win
| Units: 4
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