Applied Computation Courses
Faculty of the School of Engineering and Applied Sciences Offering Instruction in Applied Computation
Ryan Prescott Adams, Assistant Professor of Computer Science
Katia Bertoldi, Assistant Professor of Applied Mechanics
William H. Bossert, David B. Arnold, Jr. Professor of Science
Michael P. Brenner, Glover Professor of Applied Mathematics and Applied Physics, Harvard College Professor, Area Dean for Applied Mathematics
David M. Brooks, Gordon McKay Professor of Computer Science
Christopher R. Cecka, Lecturer on Computational Science
Yiling Chen, Associate Professor of Computer Science
Stephen N. Chong, Assistant Professor of Computer Science
Marie D. Dahleh, Senior Lecturer on Engineering Sciences
Krzysztof Z. Gajos, Assistant Professor of Computer Science
Steven J. Gortler, Robert I. Goldman Professor of Computer Science
Efthimios Kaxiras, John Hasbrouck Van Vleck Professor of Pure and Applied Physics, Affiliate of the Department of Chemistry and Chemical Biology
David J. Knezevic, Lecturer on Computational Science
Edward W. Kohler, Associate Professor of Computer Science
Zhiming Kuang, Gordon McKay Professor of Atmospheric and Environmental Science
H. T. Kung, William H. Gates Professor of Computer Science and Electrical Engineering
Harry R. Lewis, Gordon McKay Professor of Computer Science (on leave 2012-13)
L. Mahadevan, Lola England de Valpine Professor of Applied Mathematics, of Organismic and Evolutionary Biology, and of Physics
Michael D. Mitzenmacher, Gordon McKay Professor of Computer Science, Area Dean for Computer Science
John G. Morrisett, Allen B. Cutting Professor of Computer Science
Cherry Murray, John A. and Elizabeth S. Armstrong Professor of Engineering and Applied Sciences and Professor of Physics, Dean of the School of Engineering and Applied Sciences
Radhika Nagpal, Fred Kavli Professor of Computer Science
David C. Parkes, George F. Colony Professor of Computer Science, Harvard College Professor (on leave fall term)
Hanspeter Pfister, Gordon McKay Professor of Computer Science
Pavlos Protopapas, Lecturer on Computational Science
Michael O. Rabin, Thomas J. Watson, Sr. Professor of Computer Science, Thomas J. Watson, Sr. Professor of Computer Science, Emeritus (on leave fall term)
Margo I. Seltzer, Herchel Smith Professor of Computer Science
Stuart M. Shieber, James O. Welch, Jr. and Virginia B. Welch Professor of Computer Science
Michael D. Smith, John H. Finley, Jr. Professor of Engineering and Applied Sciences, Dean of the Faculty of Arts and Sciences
Vahid Tarokh, Perkins Professor of Applied Mathematics and Vinton Hayes Senior Research Fellow of Electrical Engineering
Eli Tziperman, Pamela and Vasco McCoy, Jr.Professor of Oceanography and Applied Physics
Salil P. Vadhan, Vicky Joseph Professor of Computer Science and Applied Mathematics
Leslie G. Valiant, T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics (on leave 2012-13)
James H. Waldo, Gordon McKay Professor of the Practice of Computer Science
Gu-yeon Wei, Gordon McKay Professor of Electrical Engineering and Computer Science
Woodward Yang, Gordon McKay Professor of Electrical Engineering and Computer Science (on leave 2012-13)
Primarily for Graduates
Applied Computation 263. Data and Computation on the Internet - (New Course)
Catalog Number: 83688 Ian Stokes-Rees
Half course (fall term). M., W., 4–5:30.
.This course explores the Internet as a central component of modern scientific data processing and computation. We will examine the architecture of the Internet and the models of computation and data with which it is compatible. Through readings and exercises, students will explore the trade-offs of these various models and gain an appreciation for successful Internet-oriented system design for modern, federated, data- and compute-intensive scientific research. Students will complete a team
Prerequisite: A course in object-oriented programming (e.g. Computer Science 51) and familiarity with the Unix operating system or variants.
[Applied Computation 272 (formerly Applied Mathematics 272r). Kinetic Methods for Fluids: Theory and Applications]
Catalog Number: 27235
Instructor to be determined
Half course (spring term). W., 3–5, M., 7–9 p.m.
Systematic introduction to kinetic methods for studying fluids, based on the lattice Boltzmann equation. Emphasizes theory, including discrete dynamics and symmetry, as well as hands-on programming of basic algorithms for fluid flow simulations, paying attention to understanding of the theoretical basis and connection to real fluid physics. The course lays the foundation for further research on the method extensions, particularly in complex fluids and micro/nano-fluidics and presents specific applications in various science and engineering problems.
Prerequisite: Knowledge of basic classical physics, fluid dynamics, and numerical methods are desirable.
Applied Computation 274 (formerly Applied Mathematics 274). Computational Fluid Dynamics
Catalog Number: 70261
David J. Knezevic
Half course (spring term). Tu., Th., 10–11:30.
A theoretical and practical introduction to the key tools in computational fluid dynamics. The course will examine a range of numerical algorithms relevant to fluids modeling, analyzing the stability, convergence and accuracy of each. Students will implement an extensive range of CFD algorithms. Topics include the hyperbolic partial differential equations and conservation laws, with a focus on numerical discretization via discontinuous Galerkin finite element methods, followed by simulation of viscous incompressible fluids via the continuous Galerkin finite element method.
Prerequisite: A first course in scientific computing, e.g. Applied Mathematics 111 or 205, and knowledge of computer programming.
Catalog Number: 18739Instructor to be determined
Half course (fall term). M., W., 2:30–4.
This course will provide the background and an extensive set of examples showing how computational methods are applied to modern design of materials with desired functionality. The methods will span multiple length and time scales, including molecular dynamics simulations, first-principles approaches, stochastic methods for optimization and sampling, and continuum elasticity theory. Examples will include problems in electronic and photonic devices, materials for energy conversion, storage, and environmental protection, and those related to mechanical strength of materials.Note:
Expected to be given in 2013–14.
Prerequisite: Undergraduate coursework in quantum mechanics, solid state physics, thermodynamics and statistical mechanics is recommended. Knowledge of physical chemistry and solid mechanics is required.
Applied Computation 298r. Interdisciplinary Seminar in Computational Science & Engineering - (New Course)
Catalog Number: 46142
Efthimios Kaxiras and Daniel Weinstock
Half course (spring term). F., 12–3. EXAM GROUP: 5, 6, 7
This course, centered on the Institute for Applied Computation Science (IACS) seminar series, will provide broad exposure to cutting-edge topics, applications, and unifying concepts in Computational Science & Engineering. Students will read, present and discuss journal articles related to IACS talks, attend the seminars and meet with visiting speakers. Possible topics to be covered include scientific visualization, computational approaches to disease, mathematical neuroscience, computational archeology, and computational finance.