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Computation for Design and Optimization (CDO)

Research and Teaching Output of the MIT Community

Computation for Design and Optimization (CDO)


Intensive Computation for Design and Optimization (CDO) has become an essential activity in such diverse areas as telecommunications, imaging, guidance/control, the Internet, aerospace design, micromachined devices, distribution networks, traffic management, air transport, web-based retailing, the electric power grid, and manufacturing scheduling. Effective computation produces shorter design cycle times, higher-quality products, and improved functionality.

The MIT CDO program offers a unified treatment of the computational aspects of complex engineered systems. Through hands-on projects and a master's thesis, students develop and apply advanced computational methods to a diverse range of applications, from aerospace to nanotechnology, from Internet protocols to telecommunications system design. Career opportunities for CDO graduates include companies and research centers where systems modeling, numerical simulation, design and optimization play a critical role.

The MIT CDO program educates students in the formulation, analysis, implementation, and application of computational approaches to designing and operating engineered systems, emphasizing:

  • Breadth through introductory courses in numerical analysis and simulation, optimization, and applied probability
  • Depth in optimization methods and numerical methods for partial differential equations
  • Multidisciplinary aspects of computation
  • Hands-on experience through projects, assignments, and a master's thesis
For more information, please visit the CDO web site,

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Recent Submissions

  • Mahmood, Zohaib (Massachusetts Institute of Technology, 2015)
    In this thesis we study the design of robust decoupling matrices for coupled transmit radio frequency arrays used in magnetic resonance imaging (MRI). In a coupled parallel transmit array, because of the coupling itself, ...
  • Feng, Chi, S.M. Massachusetts Institute of Technology (Massachusetts Institute of Technology, 2015)
    The optimal selection of experimental conditions is essential to maximizing the value of data for inference and prediction. We propose an information theoretic framework and algorithms for robust optimal experimental design ...
  • Sakamoto, Tomoaki (Massachusetts Institute of Technology, 2015)
    This dissertation examines retweeting activities as the information spreading function of Twitter. First, we investigated what kind of features of a tweet help to get retweets. We construct a model that describes peoples' ...
  • Narayanan Subramani, Deepak (Massachusetts Institute of Technology, 2014)
    The growing use of autonomous underwater vehicles and underwater gliders for a variety of applications gives rise to new requirements in the operation of these vehicles. One such important requirement is optimization of ...
  • Kudo, Jun, S.M. Massachusetts Institute of Technology (Massachusetts Institute of Technology, 2014)
    The ability to achieve accurate predictions of turbulent flow over arbitrarily complex geometries proves critical in the advancement of aerospace design. However, quantitatively accurate results from modern Computational ...