CTI research projects currently available for undergraduate students
The table below contains a listing of current research projects at CTI that have undergraduate students involvement. Questions about a particular project may be directed to the Faculty Advisor.
| Project Title/Description | Project Area | Project Requirements | Posting Date | Faculty Advisor |
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Grid Computing and Bioinformatics: Grid computing is a new field that utilizes geographically separated commodity computers as a virtual supercomputer. Students will have access to thousands of computers at the advanced computational facilities at Argonne National Laboratory and the Illinois Bio-Grid. Bioinformatics is a relatively new field of biological research involving computation. Areas include human genome research, simulations of biological and biochemical processes (such as cell membranes), and proteomics (e.g., protein folding simulations). |
Grid Computing and Bioinformatics | 02/15/2005 |
David Angulo
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Secure Personalization:
Publicly-accessible adaptive systems such as recommender systems present a
security problem. Attackers who cannot be readily distinguished from
ordinary users may introduce biased data in an attempt to force the system
to "adapt" in a manner advantageous to them, push a particular product by
having it recommender to more people, for example. Secure personalization is
the study of how such public systems can be made more robust in the face of
such attacks. |
Secure Personalization |
Java programming (at least CSC 383 - Data structures) and IT 223, SE 350 ideal. CSC 380 and/or CSC 334 also helpful |
12/07/2004 |
Robin Burke, Bamshad Mobasher
|
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American Sign Language: Combining computer technology and linguistics research to bridge the communication gap between the deaf and hearing worlds, this team of deaf and hearing researchers is working towards the realization of a digital English-to-ASL translator. |
Computer Graphics, Linguistics, Speech Recognition, Artificial Intelligence, Life Drawing, Knowledge of American Sign Language |
Knowledge of one or more of the topics
mentioned in project area |
11/12/2004 |
Jacek Brzezinski, Roymeico Carter (University of North Carolina, Charlotte), Jacob Furst, Edna Johnston (Columbia College, Chicago) Glenn Lancaster, John McDonald, Nedjla Ougouag and Rosalee Wolfe |
|
Visualization Techniques for Medical Data: The students working on this project will experience, develop, and assess different visualization tools (http://www.cc.nih.gov/cip/visualization/vis_packages.html), including VTK (a popular freely available object-oriented visualization toolkit, http://public.kitware.com/VTK), for exploring Computed Tomography data of the chest and abdomen. http://facweb.cs.depaul.edu/research/vc/ http://facweb.cs.depaul.edu/research/vc/medix/2006/index.htm |
Image Processing, Image Analysis, Data Mining | CSC381, CSC367, Matlab, C++ | 05/02/2006 | Daniela Raicu |
|
Volumetric Segmentation: Students working on this project will investigate which Haralick texture descriptors are best for conducting the segmentation of soft tissues (liver, spleen, kidneys, etc) in Computed Tomography of the chest and abdomen). http://facweb.cs.depaul.edu/research/vc/ http://facweb.cs.depaul.edu/research/vc/medix/2006/index.htm |
Image Processing, Image Analysis, Data Mining | CSC381,CSC382, CSC367, Matlab, C++ | 05/02/2006 | Jacob Furst |
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Content-based Image Retrieval: Content-based Image Retrieval (CBIR) systems can be the tool that will allow researchers and medical practioners to automatically access images directly by their content and complement the textual retrieval approach currently in use. In particular, students working on this project will develop and evaluate a CBIR system for the Lung Image Database Consortium (LIDC, http://radiology.rsnajnls.org/cgi/content/full/232/3/739).
http://facweb.cs.depaul.edu/research/vc/ http://facweb.cs.depaul.edu/research/vc/medix/2006/index.htm |
Image Processing, Image Analysis, Data Mining | CSC381,CSC382, CSC367, Matlab, C++ | 05/02/2006 | Daniela Raicu |
|
Automatic detection of intensity spots in micro-array images. This project will examine the task of reading micro-array images that contain significant noise and imaging artifacts, and generating a reliable and robust way of identifying the relative intensity of the spots with respect to the image background. Applications of microarray technologies include forensics, medical diagnosis, gene mapping, and disease tracking. http://facweb.cs.depaul.edu/research/vc/ http://facweb.cs.depaul.edu/research/vc/medix/2006/index.htm |
Image Processing, Image Analysis | CSC381,CSC382, Matlab, C++ | 05/02/2006 | Jacob Furst |
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Evaluation of segmentation algorithms. Last summer a methodology for evaluating unsupervised segmentation algorithm was developed and a metric based on a statistical analysis of the overlap between machine segmented and referenced ground truth images was introduced. Students working on this project will test the effectiveness of such metric in evaluating and optimize intra-algorithm parameters, and compare inter-algorithm performance for unsupervised segmentation algorithms. http://facweb.cs.depaul.edu/research/vc/ http://facweb.cs.depaul.edu/research/vc/medix/2006/index.htm |
Image Processing, Image Analysis | CSC381,CSC382, Matlab, C++ | 05/02/2006 | Lucia Dettori |