Description:
We are looking for hiring two hourly student research assistants for the summer quarter for two different projects.
1) Text/speech similarity and anomaly/novelty analysis: Developing a measure of text similarity is useful for a variety of applications, including detection of related text that may provide redundant, new or contradictory information for purposes of summarization. Extending the problem to speech, we can also consider detecting doubt and sarcasm. This project will involve research aimed at developing improved measures of text similarity and methods for automatically classifying differences in similar texts or spoken utterances.
2) Automatic detection and classification of marine mammals: Detection of marine mammals is important for avoiding sonar operations when they are present and for tracking populations. The problem is challenging because of the highly variable noise conditions in the oceans. We have developed some prototype algorithms in Matlab and are looking for someone to work on porting these algorithms to C/C++ and factoring the implementation to leverage parallel processing and allow experimentation with large amounts of data. Once the software is in place, the goal is to explore semi-supervised learning algorithms.
Both projects will require computer implementation of algorithms for data processing and analysis.
1) Text/speech similarity and anomaly/novelty analysis: Developing a measure of text similarity is useful for a variety of applications, including detection of related text that may provide redundant, new or contradictory information for purposes of summarization. Extending the problem to speech, we can also consider detecting doubt and sarcasm. This project will involve research aimed at developing improved measures of text similarity and methods for automatically classifying differences in similar texts or spoken utterances.
2) Automatic detection and classification of marine mammals: Detection of marine mammals is important for avoiding sonar operations when they are present and for tracking populations. The problem is challenging because of the highly variable noise conditions in the oceans. We have developed some prototype algorithms in Matlab and are looking for someone to work on porting these algorithms to C/C++ and factoring the implementation to leverage parallel processing and allow experimentation with large amounts of data. Once the software is in place, the goal is to explore semi-supervised learning algorithms.
Both projects will require computer implementation of algorithms for data processing and analysis.
Qualification/expertise:
Computer
programming skills and experience, including: experience with unix,
programming languages such as C, C++ or Java and scripting languages
such as Perl and Python. Students should have completed and done well in
both CS142 and 143 (at least). Knowledge of probability is very useful
for anticipated work on machine learning. For project 2, experience with
Matlab is desirable.
Hours & Salary:
The position will involve 15-40 hrs/week in
the summer, flexible hours, depending on student availability, and may
continue at a lower level of effort in the fall. The salary is
$12-14/hr, depending on experience.
Application Documents:
CV,
(unofficial) transcript, and the contact information of one or two
references, including either the instructor for one of your programming
courses or a supervisor for whom you've done programming.
Contact:
Interested candidates may send their application material to Dr. Hanna Hajishirzi at hannaneh@uw.edu and cc Prof. Mari Ostendorf at ostendor@u.washington.edu and Nicole Nichols (nmn3@u.washington.edu) for the second position.
