Jennifer Smith, Ph.D.

Education

• PhD Electrical Engineering, University of Idaho
• PhD Economics, State University of New York at Albany
• MS Electrical Engineering, University of Connecticut
• BS Computer and Systems Engineering, Rensselaer Polytechnic Institute

Publications

BOOK CHAPTERS:

Smith, “Covariance-Model-Based RNA Gene Finding: Using Dynamic Programming versus Evolutionary Computing,” Chapter 7 in Computational Intelligence in Bioinformatics, A. Kelemen, A. Abraham, Y. Chen, and Y. Liang, eds., Springer-Verlag, 2007.

REFEREED JOURNAL PUBLICATIONS:

1. Smith, “RNA Search with Decision Trees and Partial Covariance Models,” IEEE Trans. Computational Biology & Bioinformatics, Volume 6, No. 3, 2009.
2. Smith “Efficient Non-coding RNA Gene Searches through Classical and Evolutionary Methods,” Int. J. Computational Intelligence in Bioinformatics and Systems Biology, Volume 1, No. 1, pp. 42-58, 2009.
3. Smith & Wiese, “Integrating Thermodynamic and Observed-Frequency Data for Non-coding RNA Gene Search,” Trans. Computational Systems Biology X, pp. 124-142, Corrado Priami ed., Springer, 2008.
4. Smith, “Homology Search with Binary and Trinary Scoring Matrices,” International Journal of Bioinformatics Research and Applications, Volume 2, No. 2, pp. 119-131, April 2006.
5. Smith and Frenzel, “Bioinformatics Searches Using a Single-Chip Shared-Memory Multiprocessor,” Future Generation Computer Systems, Volume 22, No. 1-2, pp. 80-87, January 2006.

REFEREED CONFERENCE PUBLICATIONS:

1. Smith, “RNA Gene Finding with Biased Mutation Operators,” 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB ’07), pp. 268-274, in 2007 IEEE Symposium Series on Computational Intelligence (SSCI ’07).
2. Smith, “A Fast Approximate Covariance-Model-Based Database Search Method for Non-coding RNA,” 2007 International Symposium on Bioinformatics Research and Applications (ISBRA ’07), LNBI 4463, Springer-Verlag, pp. 270-281.
3. Smith and Wiese, “Improved Covariance Model Parameter Estimation Using RNA Thermodynamic Properties,” Bionetics 2007 (IEEE/ACM sponsored).
4. Smith, “Covariance Searches for ncRNA Gene Finding,” 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB ’06), pp. 320-326.
5. Smith, “A Genetic Algorithms Approach to Non-coding RNA Gene Searches,” 2006 IEEE Systems, Man, and Cybernetics Workshop on Adaptive and Learning Systems (SMCALS ’06), pp. 48-53.
6. Smith, “Accelerated Non-coding RNA Searches with Covariance Model Approximations,” 2006 IEEE Congress on Evolutionary Computation (CEC ’06), pp. 9278-9283.
7. Smith, “Truncated Profile Hidden Markov Models,” 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB ’05), pp. 257-261.
8. Smith, “Searching for Protein Classification Features,” 2005 IEEE Congress on Evolutionary Computation (CEC ’05), Volume 1, pp. 648-653.
9. Smith, “Protein Family Classification Using Structural and Sequence Information,” 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB ’04), pp. 168-174.
10. Smith, “Performance of a GALS Single-Chip Multiprocessor,” 2004 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA ’04), Volume 1, pp. 449-454.
11. Smith, “An Asynchronous GALS Interface with Applications,” 2004 IEEE Workshop on Microelectronics and Electron Devices (WMED ’04), pp. 41-44.
12. Smith and Frenzel, “Bioinformatics Application of a Scalable Supercomputer-on-chip Architecture,” 2003 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA ‘03), Volume 1, pp. 385-391.
13. Smith and Frenzel, “Low-latency Multiple Clock Domain Interfacing Without Alteration of Local Clocks,” IEEE 15th Biennial University / Government / Industry Microelectronics Symposium (UGIM ‘03), pp. 342-343.

Research

Dr. Smith does research in the area of Music Information Retrieval, mostly in the sub-area of Automatic Music Transcription (AMT). The goal of this research is the conversion of music audio into sheet music or MIDI files. Song segmentation, instrument separation, and musical key determination are some of the sub-tasks of AMT.

Areas of Interest

• Music Information Retrieval
• Computer Architecture
• Audio Engineering
• Digital Signal Processing