Computer Engineering

Joseph Cavallaro
Student needs: 2
Suggested Elec 599 projects:

• Topics in Architecture Analysis of Processors and Accelerators for Wireless Systems.

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Alan Cox
Student needs: 1
Suggested Elec 599 projects:

• rethinking virtual-to-physical address translation for data intensive applications

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Farinaz Koushanfar
Student needs: 2
Suggested Elec 599 projects:

• Topics in security, trust, and data integrity of reconfigurable and cognitive radios

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Kartik Mohanram
Student needs: 3 students
Suggested Elec 599 projects:

• Topics in circuit design and computer engineering

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Peter Varman
Student needs: 1 to 2 students
Suggested Elec 599 projects:

• Resource Management Issues in Data Centers

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Lin Zhong
Student needs: 3
Suggested Elec 599 project:

• Efficiency-driven wireless system design
  
• Energy management in trace-gas sensor networks for event detection
  
• Efficiency and equilibriums of information exchange in socially inspired networks
  
  

Multimedia Communications

Wireless Networks

Edward Knightly
Student needs: approximately 2
Suggested Elec 599 projects:

• Topics in multihop wireless networking spanning theory to experimental research.
  Example projects include medium access protocol design and analysis, network analysis and control, mobility, security, and new applications.

Signal and Image Processing

Richard Baraniuk
Student needs:
Suggested Elec 599 projects:

• Topics in Compressive Sensing

Erzsébet Merényi
Student needs: 1
Suggested Elec 599 projects:

• Neural manifold learning in high-dimensional spaces

  Topics range from theories of self-organized learning to applications. Self-organized learning is one of the biologically most plausible machine learning paradigms, mimicking information processing in the cerebral cortex. SOMs and variants are powerful for identification of structure in "complicated" data.

  Theories for project topics include "recent advances in self-organizing maps (SOMs)"; magnification control in adaptive map formation; graph representation of SOM knowledge and optimum segmentation; metric learning for (classification of) inhomogeneous fused data. Applications include structure identification (unsupervised segmentation or clustering) for discoveries from multi- and hyperspectral images (of Earth, Mars, other planets, Moon), or from clinical data; comparative studies in supervised "precision" classification; studies in selection of relevant features / compression for hyperspectral images; classification of fused disparate image data of planetary surfaces. The 599 project will be a well-defined subset of the chosen topic, and will build on tools developed in previous work.

Michael Orchard
Student needs: 1
Suggested Elec 599 projects:

• Multiple-frame super-resolution
  As you stand at the edge of the Grand Canyon, taking in the stunning scene before you, you regret not having invested the extra money for the 16-megapixel SLR camera you had decided was too much a luxury. You decide to shoot the scene with your 10-megapixel camera N (e.g. N=16) different times. This project addresses the challenge of how to process the N different low-resolution (LR) images to produce a higher-resolution (HR) image that might approach the quality of the desired 16-megapixel image. Since the N LR images will not be exactly aligned, you will need to estimate local, sub-pixel alignment offsets between LR images (i.e. the "image registration" problem). Given the alignments, the problem of estimating the HR image is complicated by the fact that ALL digital images suffer from substantial aliasing, particularly in their highest frequency components. Due to aliasing, every high-frequency component of each LR image is composed of a sum of two or more unknown frequency components of the original continuous scene. However, since your N different LR images provide information about different sums of the unknown spectral components, it should be possible to resolve the unknown spectral components, thereby estimating a higher-resolution, de-aliased image. Since aliasing in the LR images also effects image registration, the image registration and de-aliasing problems will need to be addressed jointly.

Photonics and Nanoengineering

Daniel Mittleman
Student needs: 1 or 2
Suggested Elec 599 projects:

• The science and technology associated with terahertz radiation is a rapidly growing area of research and development. New techniques for generating, detecting, manipulating, and controlling terahertz electromagnetic radiation are leading to many exciting possible applications in sensing, imaging, and spectroscopy. Recently, we have discovered several new waveguiding techniques which hold great promise. One of these involves the propagation of terahertz pulses between two smooth parallel metal plates. Calculations of the intrinsic attenuation suggest that this method could provide orders of magnitude improvement, as compared to all previous waveguiding methods. This 599 project involves an experimental validation of these computational results. A successful completion of this project will involve several steps:
  1. Become familiar with the basic science and technology of terahertz radiation, and why it is important.
  2. Become familiar with the theory of parallel plate metal waveguides as applied to the THz domain, as well as other common waveguide techniques.
  3. Become trained in the operation of the THz time-domain spectrometer in the laboratory.
  4. Design and fabricate parallel plate metal waveguides for testing. These will need to be long enough so that a very small attenuation-per-unit-length can still produce a measureable effect.
  5. Test and compare to theoretical predictions.

Bioengineering

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Last modified: November 21, 2008