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Yijun
Sun, Ph.D.
Interdisciplinary
Department of Electrical and Computer
Engineering University
of Florida
Email: sun {at}
dsp.ufl.edu |
I received M. Sc and
Ph.D. degrees in electrical engineering from the University of Florida,
Postdoc Association Position
Research Interests
o Bioinformatics: metagenomics,
sequence analysis, microbial community analysis, molecular classification,
genetic network modeling for cancer diagnosis and prognosis.
o Machine Learning/Data Mining: large margin classification/regression, ensemble learning, feature selection/extraction, computational learning theory, graphical model and Bayesian network.
Postdocs and Students
o Dr. Yunpeng Cai
(Postdoc)
o Yubo Cheng (Ph.D.
Student)
o Bing Han (Ph.D.
Student, Committee member)
o Jun Xu (Ph.D. Student,
Committee member)
Publications
o
Y.
Cai, Y. Sun, Y. Cheng, J. Li, and S. Goodison,
Molecular Profiling
for Predicting Disease Outcomes of ER- Breast Cancer Patients,
Technical Report,
2009.
o
Y.
Sun,
and Y. Cai,
Analyzing Microbe-microbe
Interactions Using Large Collections of 16S rRNA Pyrosequences,
Technical Report,
2009.
o
Y.
Sun,
Local Learning Based Feature Selection for
High Dimensional Data Analysis, [Website]
IEEE Trans. on Pattern Analysis and Machine
Intelligence (TPAMI),
accepted. (impact factor: 6.0, the overall top-ranked IEEE and CS transactions
journal)
o Y. Cai, Y. Sun, Y. Cheng, J. Li, and S. Goodison,
Fast Implementation of ℓ1 Regularized Learning Algorithms Using Gradient Descent Methods, [Website]
SIAM International Conference on Data Mining (SDM), submitted.
o Y. Sun, Y. Cai, W. Farmerie, F. Yu, and S. Goodison,
Comparative Community Analysis of Human Gut Flora Reveals Obesity-associated Microbial Signatures,
Technical Report, 2009.
o M. L. Farrell, L. Liu,
Y. Sun, V. T. Ryan, K. L. Brown, W. G. Norrie, W. G. Farmerie, R. A.
Winegar, W. McKendree,
Mesopotamian
Air Genome Reveals Unprecedented Bacterial Diversity,
Applied and Environmental Microbiology, submitted, 2009.
o
F.
Yu*, Y. Sun*, L. Liu, and W. Farmerie, (*equal contribution)
GSTaxClassifier: A Genomic Signature Based Taxonomic Classifier for Metagenomics Data Analysis, [Website]
Bioinformation, accepted, 2009.
o N. Bandyopadhyay, T.
Kahveci, S. Ranka, Y. Sun and S. Goodison,
Pathway based Feature
Selection Algorithm for Cancer Microarray Data
Advances in
Bioinformatics,
accepted, 2009.
o
Y.
Sun*,
Y. Cai*, L. Liu, F. Yu, M. L. Farrell, W. McKendree, and W. Farmerie, (*equal
contribution)
ESPRIT: Estimating Species Richness Using Large Collections of 16S rRNA Pyrosequences, [Website]
Nucleic Acids Research, vol. 37, no. 10 e76,
May 2009. (impact factor: 7.0)
This paper is
among the 50 most-frequently read articles in Nucleic Acids Research:
June 2006 (42nd).
o
L.
Yin, L. Liu, Y. Sun, R. R. Gray, A. C. Lowe, W. Hou, J. W.
Sleasman, and M. M. Goodenow,
Ultra-deep
Pyrosequencing Captured Low Frequency CXCR4 Virus Populations Co-archived with
CCR5 Virus in Peripheral Blood Lymphocytes from HIV-infected Therapy-naive
Children,
The
17th Conference on Retroviruses and Opportunistic Infections (CROI 2010), San Francisco, CA,
February 2010.
o Y. Duan, L. Zhou, D.
Hall, W. Li, H. Doddapaneni, H. Lin, L. Liu, C. Vahling, D. Gabriel, K.
Williams, A. Dickerman, Y. Sun, and T. Gottwald,
Complete
Genome Sequence of Citrus Huanglongbing Bacterium, Candidatus Liberibacter
Asiaticus Obtained through Metagenomics,
Molecular
Plant-Microbe Interactions, vol. 22, no. 8, 2009, pp. 1011-1020, 2009. (impact
factor: 4.3)
o Y. Sun, V. Urquidi, and S.
Goodison,
Breast
Cancer Research and Treatment, DOI: 10.1007/s10549-009-0365-6, 2009.
(impact factor: 5.7)
o Y. Sun* and S. Goodison*
(equal contribution)
Optimizing Molecular
Signatures for Predicting Prostate Cancer Recurrence,
The
Prostate,
vol. 69, no. 10, pp. 1119-27, 2009. (impact factor: 3.7)
This
paper is featured in Medical News Today.
o Y. Cai, Y. Sun, J. Li, and S. Goodison,
Online
Feature Selection Algorithm with Bayesian L-1 Regularization,
in Proc. 13th Pacific-Asia Conference on
Knowledge Discovery and Data Mining (PAKDD09), Bangkok, Thailand, April
2009. (oral presentation: 39/338 = 12%)
o M. L. Farrell, W.
Norrie, V. Ryan, K. Brown, R. Winegar, Y.
Sun, L. Liu, W. Farmerie, and W. McKendree,
Metagenomic
Analysis of Air,
The 2009 Gordon Research Conferences on
Chemical and Biological Terrorism Defense, Galveston, TX, January 2009.
o C. Rosser, L. Liu, Y. Sun, P. Villicana, M. McCullers, S.
Porvasnik, and S. Goodison
Bladder Cancer
Associated Gene Expression Signatures Identified by Profiling of Exfoliated
Urothelia,
Cancer Epidemiology,
Biomarkers and Prevention, vol. 18, no. 2, pp. 444-453, 2009. (impact factor: 4.8)
o Y. Sun, and D. Wu
Feature Extraction
through Local Learning,
Statistical Analysis and Data Mining, vol. 2, no.
1, pp. 34-47, 2009.
o Y. Cheng, Y. Cai, Y. Sun, and J. Li
Semi-supervised
Feature Selection under the Logistic I-RELIEF Framework,
in
Proc. 19th International Conference on
Pattern Recognition (ICPR08), Tampa, FL, December 2008.
(oral
presentation: 18%)
o Y. Sun, Y. Cai, and S. Goodison
Combining nomogram and microarray data for
predicting prostate cancer recurrence
in
Proc. 8th IEEE International Conference
on Bioinformatics and Bioengineering (BIBE08), pp. 1-7, Athens, Greece,
October 2008.
o Y. Sun and D. Wu
A RELIEF Based Feature Extraction
Algorithm [Matlab code]
in
Proc. 8th
(oral
presentation: 40/282 = 13%)
o Y. Sun, S. Todorovic, and S. Goodison
A
Feature Selection Algorithm Capable of Handling Extremely Large Data
Dimensionality [Matlab code]
in Proc. 8th SIAM International Conference on
Data Mining (SDM08), pp. 530-540, April 2008.
(acceptance rate:
72/282 = 25%)
o Y. Sun
Iterative RELIEF for Feature Weighting: Algorithms, Theories, and Applications [Matlab code]
IEEE Trans. on Pattern Analysis and Machine
Intelligence (TPAMI),
vol. 29, no. 6, pp. 1035-1051, June 2007. (impact factor: 6.0)
o Y. Sun, S. Goodison, J. Li, L. Liu, and W. Farmerie
Improved Breast Cancer Prognosis
through the Combination of Clinical and Genetic Markers
Bioinformatics, vol. 23, no. 1, pp. 30-37, January 2007. (impact factor: 5.0)
This paper
was among the 50 most-frequently read articles in Bioinformatics. Dec. 2006
(29th), Jan. 2007 (5th), Feb. 2007 (44th). It is featured in MATLAB
Digest--Biotech and Pharmaceutical Edition (vol. 1, no. 2, June
2007).
o Y. Sun, S. Todorovic, and J. Li
Unifying
Multi-Class AdaBoost Algorithms with Binary Base Learners under the Margin
Framework
Pattern Recognition Letters (PRL), vol. 28, no. 5, pp.
631-643, April 2007.
o Y. Sun
Feature
Weighting through Local Learning
Computational Methods of Feature Selection, H. Liu and H. Motoda
(eds.), Chapman and Hall/CRC Press, October 2007.
o Y. Sun and J. Li
Iterative RELIEF for
Feature Weighting
in Proc.
International Conference on Machine
Learning (ICML06), vol. 29, pp. 1035-1051, June 2006.
(acceptance rate
140/700 = 20%)
o Y. Sun, S. Todorovic, J. Li,
and D. O. Wu
Unifying Error-Correcting
and Output-Code AdaBoost within the Margin Framework,
in Proc. International Conference on Machine Learning
(ICML05), vol. 119, pp. 872-879, August 2005.
(acceptance rate
134/491 = 27%) [Matlab code]
o Y. Sun, Z. Liu, S. Todorovic and J. Li
Adaptive Boosting for Synthetic
Aperture Radar Automatic Target Recognition,
IEEE Trans. on Aerospace and Electronic Systems (TAES), vol. 43, no. 1, pp.
112-125, January 2007.
o Y. Sun and
Predicting
Breast Cancer Metastasis by Integrating Both Clinical and Genetic Markers,
in Proc. International Conference on
Bioinformatics and Computational Biology (BIOCOMP07), vol. 1, pp. 229-235,
June 2007.
(acceptance rate =
27%)
o Y. Sun, F. Yu, L. Liu, and W. Farmerie
Estimating Microbial
Population Densities Based on Genomic Signatures,
in
Proc. International Conference on
Bioinformatics and Computational Biology (BIOCOMP07), vol. 1, pp. 163-168,
June 2007.
(acceptance
rate = 27%)
o Y. Sun, L. Liu, M.
Popp, and
Estimation of
Cross-hybridization Signals Using Support Vector Regression,
in
Proc. IEEE Symposium of Computations in Bioinformatics and Bioscience
(SCBB06), vol. 1, pp. 17- 21, June 2006.
o Y. Sun, S. Todorovic, and J. Li
Reducing the Overfitting of AdaBoost by Controlling its Data Distribution Skewness,
International Journal of Pattern Recognition and
Artificial Intelligence (IJPRA), vol. 20, no. 7, pp. 1093-1116, November 2006.
o Y. Sun, S. Todorovic, and J. Li, Increasing the
Robustness of Boosting Algorithms within the Linear-Programming Framework, Journal
of VLSI Signal Processing Systems, vol. 48, no. 1-2, pp. 5-20, August 2007.
o Y. Sun and J. Li
Adaptive Learning Approach to Landmine Detection,
IEEE Trans. on Aerospace and
Electronic Systems (TAES), vol. 41, no. 3, pp. 973-985,
July 2005.
o
Y. Wang, X. Li, Y. Sun, J. Li and P. Stoica
Adaptive Imaging for Forward-looking Ground Penetrating Radar,
IEEE Trans. on Aerospace and Electronic Systems (TAES), vol. 41, no. 3, pp. 922-936, July 2005.
o
Y.
Sun, X. Li and J. Li
Practical Landmine Detector Using Forward-Looking Ground Penetrating
Radar,
IEE Electronics Letters, vol. 41, pp.97-98,
January 2005.
o
Y.
Sun, S. Todorovic, J. Li, and D. O. Wu
A Robust Linear-programming Based Boosting Algorithm,
in Proc.
IEEE International
Workshop on Machine Learning for Signal Processing (MLSP05), Mystic, CT, September 2005.
o
Y.
Sun, J. Li, and W. Hager
Two New Regularized AdaBoost Algorithms,
in Proc. International
Conference on Machine Learning and Applications (ICMLA04), pp. 41- 48,
Louisville, KY, December 2004.
o Y. Sun and J. Li,
IEE Proc.-Radar, Sonar and Navigation, special issue on Time-Frequency
Analysis and Feature Extraction, vol. 150, pp.
253-261, August 2003.
o
Y.
Sun, M. Xue, J. Li, and S. R. Stanfill,
Improving ATR Performance through Distance Metric Learning,
in Proc. of SPIE on Technologies and Systems
for Defense and Security (SPIE07),
o
Y.
Sun and J. Li,
Landmine Detection Using Forward-looking Ground Penetrating Radar,
in Proc. of SPIE on Technologies and Systems
for Defense and Security (SPIE05), vol. 5794, pp. 1089-1097, Orlando, FL,
April 2005.
o
Q. Liu, Y. Sun, and J. Li,
Automatic Target Recognition with Bayesian Networks for Wide-area
Airborne Minefield Detection,
in Proc. of SPIE on Technologies and Systems
for Defense and Security (SPIE05), vol. 5794, pp. 1060-1070, Orlando, FL,
April 2005.
o
Y.
Sun, Z. Liu, S. Todorovic, and J. Li,
SAR Automatic Target Recognition Using AdaBoost,
in Proc. of SPIE on Technologies and Systems
for Defense and Security (SPIE05), vol. 5808, pp. 282-293, Orlando, FL,
April 2005.
o
Y.
Sun and J. Li,
Boosting a Wavelet
Packet Transform Based Landmine Detector,
in Proc. of
SPIE on Technologies and Systems for Defense and Security (SPIE04), vol.
5415, pp. 1300-1309,
o
Y.
Sun and J. Li,
Detect Buried Plastic Mines Using Time-frequency
Analysis,
in Proc. of SPIE on Detection and Remediation Technologies for Mine
and Minelike Targets (SPIE03), vol. 5089, pp. 851-862,
US Patents
o
Y. Sun, and J. Li, Land Mine Detector, Patent No.
o
Y. Sun,
o
Y. Sun, and
Some Links:
o
IEEE
Trans. on Pattern Analysis and Machine Intelligence
o
Journal of Machine Learning Research
o International Conference on Machine
Learning (ICML09)
o SIAM
International Conference on Data Mining (SDM09)
Some Pictures of Beautiful China:
o
Taken by
Dr. Dimitri Bertsekas
If
we knew what it was we were doing, it would not be called research, would it?
----- Albert Einstein
A Stroke of
Genius: Striving for Greatness in All You Do.----- Richard Hamming