Sheng Liu

PERSONAL

*** **** ****

INFORMATION

Department of Computer and Information Science

The University of Mississippi

University, MS 38677

Email: acd0kb@r.postjobfree.com

Tel: 662-***-****

HIGHLIGHTS Extensive experience applying machine learning and computational methods for

data analysis including prediction, interpretation, and feature selection. Diverse

experience in biology and computer science.

Ph. D, Engineering Science on Computer Science. U niversity of Mississippi,

EDUCATION

U.S.A. 2011.8-2014.5.

Master of Science, Engineering Science on Computer Science. University of

Mississippi, U.S.A. 2009.8-2011.8

Bachelor of Science, Biochemistry, Wuhan University, China. 1993.9-1997.7

EXPERIENCE Research Assistant 2009 - present

University of Mississippi, U.S.A.

Discussed in group meetings on data provenance project (computational

biology) which contributed a PARC data provenance system; Designed

machine learning algorithms aimed for various kinds of data, especially rule

based learning on chemical compound data, gene expression data, biosensor

data, and other biological data. Other projects: Glycoprotein classification

(MATLAB). Human body pose detection(C/C++, MATLAB). Visualization

with marching tetrahedral(C/C Business plan competition. Database

searcher (in Perl, MySQL). Network programming under Xinu (C), Android

app shaker, document classification, handwritten digit recognition, CUDA, etc.

Collaboration with other departments, universities, and company.

Technical Executive 2008 - 2009

Radarsimu Technology, Singapore.

Improved implementation of robust clustering algorithm. Managed account.

Products purchasing.

Research Scholar 2001 - 2007

School of EEE, Nanyang Technological University, Singapore.

Researched on clustering algorithms for biological sequence data. Projects

actively participated: classification of disease candidate genes; Robust

clustering algorithms for biological data; Rando m forest clustering of bio-

sequence data. Wrote a package based on proposed algorithm ( MATLAB).

Research Assistant 1997-2001

Analytical Biotechnology Lab (1999.09-2001.12), Plant Virus Lab (1997.07 -

1999.09), Wuhan Institute of Virology, Chi nese Academy of Sciences (CAS),

China.

Researched plant virus involving molecular biology experiments. Organized

lab facilities. With experience on grant application.

Matlab, C/C++, R, Perl, Java, HTML/Javascript/CSS, android app

SKILLS

development, SQL, C#, .NET, SAS, PHP, Python, Bioinformatics tools,

large sequence data like RNA-seq, parallel computing, big data and

techniques like Hadoop, MapReduce, Windows/Linux/Mac, etc.

Data mining and various machine learning algorithms for prediction:

clustering, k-means, deterministic annealing, EM, GMM, nonparametric,

classification, regression, SVM, random forests, feature selection, rule

based learning, optimization and tools like CPLEX, Clp, GLPK., graphical

models, randomized algorithm, robust learning, deep learning, sparse

learning, etc.

Hypothesis testing, p value, t-test, exploratory data analysis, regression,

ANOVA, logistic regression, design of experiment, etc.

Biochemistry, molecular biology and experiments, plant virus.

Dissertation fellowship, Spring 2014

HONORS AND

Upsilon Pi Epsilon Member since 2011

ACTIVITIES

Student Travel Award, the IEEE International Conference on Bioinformatics

and Biomedicine 2011

Student scholarship since Fall 2009

Reviewer for journals: Bioinformatics, Pattern Recognition, etc.

Member of Institute of Electrical and Electronics Engineers, Association for

Computing Machinery, International Society for Computational Biology

President of Ole Miss Badminton Club 2012

Advancement to Round 1 of Google Code Jam 2014

Participating Kaggle Competition (Sentiment Analysis on Movie

Reviews, Walmart store sales forecasting), DREAM8.5 chanllenge

Oral presentation

PRESENTATIONS

IEEE International Conference on Bioinformatics and Biomedicine

(BIBM), 2013

Annual Midsouth Computational Biology and Bioinformatics Society

(MCBIOS) conference, 2013

IEEE International Conference on Bioinformatics and Biomedicine

(BIBM), 2011

7th Annual Biotechnology and Bioinformatics Symposium (BIOT),

2010

Poster presentations

Annual MCBIOS conferences 2014, 2012, 2011, 2010.

Annual EPSCOR meeting 2014, 2013, 2012, 2011, 2010

Departmental seminars

Fall 2011, Spring 2013, Fall 2013

TEACHING Teaching assistant for java 08/2009 - 05/2010

Teaching assistant for lab 08/2009 - 05/2010

Taught programming language - Smalltalk 10/2009

S. Liu, S. Dissanayake, S. Patel, X. Dang, T. Mlsna, Y. Chen, D. Wilkins.

PUBLICATIONS

Extended work of paper presented in BIBM 2013 is invited to be in BMC

System Biology.

S. Liu, S. Dissanayake, S. Patel, X. Dang, T. Mlsna, Y. Chen, D. Wilkins,

Rule Based Regression and Feature Selection for Biological Data, Proc. Of

the IEEE International Conference on Bioinformatics and Biomedicine,

December 2013. (With Matlab package)

Z. Zhao, G. Fu, S. Liu, K. M Elokely, R. J Doerksen, Y. Chen, D. E Wilkins,

Drug activity prediction using multiple -instance learning via joint instance

and feature selection, BMC Bioinformatics 2013, 14(Suppl 14):S16.

S. Liu, R. Y. Patel, P. R. Daga, H. Liu, G. Fu, R. Doerksen, Y. Chen, and D.

Wilkins, Combined Rule Extraction and Feature Elimination in Supervised

Classification, IEEE Transactions on Nanobioscience, vol. 11, no. 3, pp. 228 -

236, 2012. (with Matlab package)

X. Nan, G. Fu, Z. Zhao, S. Liu, R. Y. Patel, H. Liu, P. R. Daga, R. J.

Doerksen, X. Dang, Y. Chen, and D. Wilkins, Leveraging Domain

Information to Restructure Biological Prediction, BMC Bioinformatics, vol.

12, Suppl 8, 2011.

S. Liu, Y. Chen, D. Wilkins, Large Margin Classifiers and Random Forests

for Integrated Biological Prediction on Mixed Type Data, International

Journal of Bioinformatics Research and Applications, vol., no., pp., 2011.

S. Liu, R.Y. Patel, P.R. Daga, H. Liu, G. Fu, R. Doerksen, Y. Chen, and D.

Wilkins, Multi-Class Joint Rule Extraction and Feature Selection for

Biological Data, Proc. Of the IEEE International Conference on

Bioinformatics and Biomedicine, pp.476-481, Atlanta, GA, USA, November

2011.

S. Liu, Y. Chen, D. Wilkins. Large Margin Classifiers and Random Forests

for Integrated Biological Prediction on Mixed Type Data. Proc. of the 7th

Annual Biotechnology and Bioinformatics Symposium (BIOT). Pp.11-18,

Lafayette, Louisiana, October2010.

S. Liu, Y. Chen, and D. Wilkins, Diffusion Kernel Large Margin Random

Forest Classification for Integrated Biological Prediction, The Seventh Annual

Conference of the MidSouth Computational Biology and Bioinformatics

Society, pp. 92, Jonesboro, AR, February 2010

Y. Wu, Q. Song, S. Liu: A Normalized Adaptive Training of Recurrent

Neural Networks with Augmented Error Gradient. IEEE Transactions on

Neural Networks (TNN) 19(2):351-356 (2008)

S. Liu, Q. Song. Random Forests Proximity Clustering of Sequences, PRIB

2007

S. Liu, Q. Song et al. Robust clustering of DNA binding sites, IEEE 2006

International Conference of the Engineering in Medicine and Biology Society

(EMBC 2006).

Y. Wu, Q. Song and S. Liu, Incremental Gain Analysis of Chaotic Recurrent

Neural Network and Applications in Pattern Association, IEEE International

Joint Conference on Neural Networks (IJCNN 2006).

T. Du, Y. Wang, Q Hu, J. Chen, S. Liu, W Huang, M Lin, Transgenic

Paulownia Expressing shiva 1 Gene Has Increased Resistance to Paulownia

Witches' Broom Disease, Journal of integrative plant biology. 47(12):1500-

1506. 2005.

X. Yang, Q. Song, S. Liu, Pre-selection of working set for SVM

decomposition algorithm, IEEE International Joint Conference on Neural

Networks (IJCNN 2005), 31 Jul – 4 Aug, Montreal, Canada, 2005

X. Yang, Q. Song, S. Liu, "A robust deterministic annealing algorithm for

data clustering", IEEE International Joint Conference on Neural Networks

(IJCNN2005), 31 Jul – 4 Aug, Montreal, Canada, 2005

X. Yang, Q. Song, A. Cao, S. Liu, C. Guo, Robust c-shells based

deterministic annealing clustering algorithm, Fuzzy Systems, 2004.

Proceedings. 2004 IEEE International Conference on, Volume 3, Pages:

1413 - 1417, 25-29 July 2004

S. Liu, Q. Song, W. Hu, A. Cao, Disease Classification Using Support Vector

Machine (SVM), Proceedings of the 9th International Conference on Neural

Information Processing (ICONIP'02), pp760-763, November 18-22, 2002.

Y. Wang, S. Liu et al, Transformation of Agrobacteria tumefaciens on healthy

and infectious Paulownia. Acta Botanica Boreali-Occidentalia Sinica. 2001,21(3)

Z. Deng, Q. Hu, S. Liu et al, A homologous comparison between mycoplasma

and phytoplasma using 16S rDNA PCR amplification and RFLP analysis,Chinese Biodiversity. 2000,8(1):103-105

Y. Wang, M. Lin, X. Shen, S. Liu, Xylophyta Genetic Transformation by

Agrobacterium.Biotechnology Information. 1999, 15(6):23-27.

Dr. Yixin Chen, acd0kb@r.postjobfree.com Department of Computer and

REFERENCE

Information Science, University of Mississippi

Dr. Dawn Wilkins, acd0kb@r.postjobfree.com Department of Computer and

Information Science, University of Mississippi

Dr. Robert Doerksen, acd0kb@r.postjobfree.com Department of Medicinal Chemistry,

University of Mississippi

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