Welcome to Dr. Shibiao WAN's homepage

I have moved to Princeton University! Please refer to my new website here for my up-to-date information!

My name is Shibiao WAN (traditional Chinese: 萬時彪,simplified Chinese: 万时彪), currently a Postdoctoral Research Associate in Department of Electrical Engineering at Princeton University. I got my PhD from The Hong Kong Polytechnic University in 2014 and B.Eng. from Wuhan University in 2010.  Before joining Princeton University, I worked as a Postdoctoral Fellow in Department of Electronic and Information Engineering at The Hong Kong Polytechnic University, Hong Kong SAR from 2014 to 2016. I was a visiting scholar to The Johns Hopkins School of Medicine and Virginia Tech in 2013.

EDUCATION

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ACADEMIC EXPERIENCE
  • Postdoctoral Research Associate, Bioinformatics and Machine Learning, Department of Electrical EngineeringPrinceton University, 2016 - present. Supervisor: Prof. Sun-Yuan Kung.
  • Postdoctoral Fellow, Bioinformatics, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, 2014 - 2016. Supervisor: Dr. Man-Wai Mak.
  • Research Associate, Bioinformatics,  Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, 2014. Supervisor: Dr. Man-Wai Mak.
  • Visiting scholar, Bioinformatics, The Johns Hopkins School of Medicine, MD, USA and CBIL lab of Virginia Tech, VA, USA , 2013. Supervisor: Prof. Yue Wang.       
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RESEARCH INTERESTS
         
      I am mainly interested in bioinformatics, computational biology and machine learning, both algorithmically and biologically.
  • Bioinformatics/Computational Biology: Protein Subcellular Localization Prediction, Membrane Protein Type Prediction, Sequence Analysis, Gene Ontology, Computational Proteomics, Proteomics Data Analysis.
  • Machine Learning: Multi-label Classification, Semi-Supervised Learning, Transductive Learning, Data and Text Mining, Classification/Prediction,  Optimization, Dimension Reduction.

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PUBLICATIONS

Book

  1. S. Wan and M. W. Mak, " Machine Learning for Protein Subcellular Localization Prediction", De Gruyter, ISBN 978-1-5015-0150-0, 2015, Germany. [link

Journals

  1. S. Wan, M. W. Mak, and S. Y. Kung, "Gram-LocEN: Interpretable Prediction of Subcellular Multi-Localization of Gram-Positive and Gram-Negative Bacterial Proteins", Chemometrics and Intelligent Laboratory Systems, 2017, vol. 162, pp. 1-9. [link] (Impact Factor: 2.217)
  2. S. Wan, M. W. Mak, and S. Y. Kung, "FUEL-mLoc: Feature-Unified Prediction and Explanation of Multi-Localization of Cellular Proteins in Multiple Organisms", Bioinformatics, 2017, vol. 33, pp. 749-750. [link] (Impact Factor: 5.766)
  3. S. Wan, M. W. Mak, and S. Y. Kung, "Ensemble Linear Neighborhood Propagation for Predicting Subchloroplast Localization of Multi-Location Proteins", Journal of Proteome Research, 2016, vol. 15, pp. 4755-4762. [link] (Impact Factor: 4.173)
  4. S. Wan, M. W. Mak, and S. Y. Kung, "Benchmark Data for Identifying Multi-Functional Types of Membrane Proteins", Data in Brief, 2016, vol. 8, pp. 105-107. [link]
  5. S. Wan, M. W. Mak, and S. Y. Kung, "Mem-ADSVM: A Two-Layer Multi-Label Predictor for Identifying Multi-Functional Types of Membrane Proteins", Journal of Theoretical Biology, 2016, vol. 398, pp. 32-42. [link] (Impact Factor: 2.351)
  6. S. Wan, M. W. Mak, and S. Y. Kung, "Transductive Learning for Multi-Label Protein Subchloroplast Localization Prediction", IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017, vol. 14, pp. 212-224. [link] (Impact Factor: 1.438)
  7. S. Wan, M. W. Mak, and S. Y. Kung, "Sparse Regressions for Predicting and Interpreting Subcellular Localization of Multi-Label Proteins", BMC Bioinformatics, 2016, 17:97. [link] (Impact Factor: 3.02)
  8. S. Wan, M. W. Mak, and S. Y. Kung, "Mem-mEN: Predicting Multi-Functional Types of Membrane Proteins by Interpretable Elastic Nets", IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2016, vol. 13, pp. 706-718. [link] (Impact Factor: 1.438)
  9. S. Wan and M. W. Mak, "Predicting Subcellular Localization of Multi-Location Proteins by Improving Support Vector Machines with an Adaptive-Decision Scheme", International Journal of Machine Learning and Cybernetics, 2015. [link] (Impact Factor: 1.11)
  10. S. Wan, M. W. Mak, and S. Y. Kung, "mLASSO-Hum: A LASSO-Based Interpretable Human-Protein Subcellular Localization Predictor", Journal of Theoretical Biology, 2015, vol. 382, pp. 223-234. [link] (Impact Factor: 2.351)
  11. S. Wan, M. W. Mak, and S. Y. Kung, " mPLR-Loc: An Adaptive-decision Multi-label Classifier Based on Penalized Logistic Regression for Protein Subcellular Localization Prediction"Analytical Biochemistry, 2015, vol. 473, pp. 14-27. [link]  (Impact Factor: 2.305)
  12. S. Wan, M. W. Mak, and S. Y. Kung, "R3P-Loc: A Compact Multi-label Predictor Using Ridge Regression and Random Projection for Protein Subcellular Localization", Journal of Theoretical Biology, 2014, vol.360, pp. 34-45[link] (Impact Factor: 2.351)
  13. S. Wan, M. W. Mak, and S. Y. Kung, "HybridGO-Loc: Mining Hybrid Features on Gene Ontology for Predicting Subcellular Localization of Multi-Location Proteins", PLoS ONE, 2014,  9(3): e89545. [link]  (Impact Factor: 3.730)
  14. S. Wan, M. W. Mak, and S. Y. Kung, " Semantic Similarity over Gene Ontology for Multi-label Protein Subcellular Localization ", Engineering, 2013, vol. 5, pp. 68-72. [pdf] [link] (also presented in 2013 International Conference on Bioinformatics and Biomedical Engineering (iCBBE'2013), Beijing, China, Sep. 2013)
  15. S. Wan, M. W. Mak, and S. Y. Kung, "GOASVM: A Subcellular Location Predictor by Incorporating Term-Frequency Gene Ontology into the General Form of Chou’s Pseudo-Amino Acid Composition", Journal of Theoretical Biology, 2013, vol. 323, pp. 40–48. [link(Impact Factor: 2.351)
  16. S. Wan, M. W. Mak, and S. Y. Kung, "mGOASVM: Multi-label Protein Subcellular Localization Based on Gene Ontology and Support Vector Machines", BMC Bioinformatics, 2012, 13:290. [link(Impact Factor: 3.02) 

Conference Papers

  1. S. Wan, M. W. Mak, and S. Y. Kung, "Protecting Genomic Privacy by a Sequence-Similarity Based Obfuscation Method", 2017, arXiv preprint arXiv: 1708.02629. [link]
  2. M. AI, S. Wan and S. Y. Kung, "Ratio Utility and Cost Analysis for Privacy Preserving Subspace Projection", 2017, arXiv preprint arXiv:1702.07976. [link] 
  3. S. Wan, M. W. Mak, B. Zhang, Y. Wang and S. Y. Kung, "Ensemble Random Projection for Multi-label Classification with Application to Protein Subcellular Localization", 2014 IEEE International Conference on Acoustic Speech and Signal Processing (ICASSP'14)Florence, Italy, May 2014, pp. 5999-6003. [pdf[link]
  4. S. Wan, M. W. Mak, B. Zhang, Y. Wang and S. Y. Kung, "An Ensemble Classifier with Random Projection for Predicting Multi-label Protein Subcellular Localization", The 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM'2013), Shanghai, China, Dec. 2013, pp. 35-42[link]
  5. S. Wan, M. W. Mak, and S. Y. Kung, "Adaptive Thresholding for Multi-Label SVM Classification with Application to Protein Subcellular Localization Prediction", 2013 IEEE International Conference on Acoustic Speech and Signal Processing (ICASSP'13), Vancouver, CanadaMay 2013, pp. 3547-3551. [pdf] [link]
  6. S. Wan, M. W. Mak, and S. Y. Kung, "GOASVM: Protein Subcellular Localization Prediction Based on Gene Ontology Annotation and SVM", 2012 IEEE International Conference on Acoustic Speech and Signal Processing (ICASSP'12), Kyoto, Japan, Mar. 2012, pp. 2229-2232. [link]
  7. S. Wan, M. W. Mak, and S. Y. Kung, "Protein Subcellular Localization Prediction Based on Profile Alignment and Gene Ontology", 2011 IEEE International Workshop on Machine Learning for Signal Processing (MLSP'11), Beijing, China, Sep. 2011, pp. 1-6. [link]
  8. S. Wan, C. Yao, Y. Hu, G. Zhang ,“A Method of Continuous Data Flow Embedded within Speech Signals”, The 2-nd International Conference on Signal Acquisition and Processing (ICSAP’10), Bangalore, India, Feb. 2010, pp. 362-365. [link]

BIOINFORMATICS WEB-SERVERS
  • PolyU-Loc: A Package of Web-Servers for Protein Subcellular Localization Prediction.
  • GOASVM: Single-location Protein Subcellular Localization Prediction (for Eukaryote and Human).
  • mGOASVM: Multi-location Protein Subcellular Localization Prediction (for Virus and Plant).
  • HybridGO-Loc: Mining Hybrid GO Features for Multi-label Protein Subcellular Localization (for Virus and Plant).
  • R3P-LocCompact Predictor for Multi-Label Protein Subcellular Localization (for Eukaryote and Plant).
  • mPLR-Loc: Probabilistic Predictor for Multi-label Protein Subcellular Localization (for Virus and Plant).
  • mLASSO-HumInterpretable Predictor for Single- and Multi-label Protein Subcellular Localization (for Human).
  • Mem-mENInterpretable Predictor for Multi-Functional Types of Membrane Proteins.
  • SpaPredictor: An Interface of Two Predictors for Interpretable Protein Subcellular Localization.
  • Mem-ADSVM: A Two-Layer Predictor for Multi-Label Membrane Protein Type Prediction.
  • EnTrans-Chlo: Ensemble Transductive Learning for Protein Subchloroplast Localization Prediction.
  • LNP-ChloLinear Neighborhood Propagation for Protein Subchloroplast Localization Prediction.
  • FUEL-mLocFeature-Unified Prediction and Explanation of Protein multi-Localization of Cellular Prediction.
  • Gram-LocENInterpretable Prediction of Subcellular Multi-Localization of Gram-Positive and Gram-Negative Bacterial Proteins.

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PROFESSIONAL ACTIVITIES
  • Editorial Board Member for Gene & Translational Bioinformatics (GTB)
  • TPC Member for IEEE ICTAI 2017
  • TPC Member for IEEE ICTAI 2016
  • TPC Member for 2018 International Conferenceon Computer Intelligent Systems & Networking (ICCISN 2018)
  • Reviewer for IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS) (1 time)
  • Reviewer for Journal of Proteome Research (1 time)
  • Reviewer for BMC Bioinformatics (1 time)
  • Reviewer for Biochimie (1 time)
  • Reviewer for IEEE Transactions on NanoBioscience (IEEE T-NB) (1 time)
  • Reviewer for Journal of Theoretical Biology (JTB) (1 time)
  • Reviewer for Analytical Biochemistry (AB) (5 times)
  • Reviewer for Molecules (1 time)
  • Reviewer for International Journal of Molecular Sciences (IJMS) (1 time)
  • Reviewer for International Journal of Machine Learning and Cybernetics (JMLC) (3 times)
  • Reviewer for Applied Mathematics and Computation (AMC) (1 time)
  • Reviewer for Journal of Applied Mathematics (JAM) (1 time)
  • Reviewer for Advances in Artificial Neural Systems (AANS) (2 times)
  • Reviewer for Computer Methods and Programs in Biomedicine (CMPB) (1 time)
  • Reviewer for International Journal of Biomedical Imaging (IJBI) (1 time)
  • Reviewer for 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE ICASSP 2017)
  • Reviewer for 2016 IEEE International Conference on Tools with Artificial Intelligence (IEEE ICTAI)
  • Reviewer for 2015 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2015)

AWARDS & HONORS
  • “Best Poster Award” in the 6-th Beijing-Hong Kong International Doctoral Forum 2011, Hong Kong SAR, Aug., 2011; 
  • Postgraduate Scholarship, The Hong Kong Polytechnic University, Hong Kong SAR, 2010-2014;
  • National Assistantship, Wuhan, China, 2008-2009;
  • National Inspirational Scholarship, Wuhan, China, 2007-2008;
  • Excellent Scholarship (the 3-rd prize), Wuhan, China, 2007-2008;
  • The Freshmen Scholarship, Wuhan, China, 2006-2007.

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TEACHING & TUTORING EXPERIENCE
  • 2016
    • Kernel-Based Machine Learning (ELE477), Princeton University
  • 2015
    • Object-Oriented Design and Programming (EIE320/EIE3375), The Hong Kong Polytechnic University
  • 2014
    • Information Technology (ENG2003), The Hong Kong Polytechnic University
    • Database Systems (EIE3114), The Hong Kong Polytechnic University
  • 2013
    • Information Technology (ENG2003), The Hong Kong Polytechnic University
    • Object-Oriented Design and Programming (EIE320/EIE3375), The Hong Kong Polytechnic University
    • Database Systems (EIE3114), The Hong Kong Polytechnic University
    • Distributed Systems and Network Programming (EIE424/EIE4108), The Hong Kong Polytechnic University
  • 2012
    • Object-Oriented Design and Programming (EIE320/EIE3375), The Hong Kong Polytechnic University
    • Distributed Systems and Network Programming (EIE424/EIE4108), The Hong Kong Polytechnic University
    • Communication Fundamentals (EIE331), The Hong Kong Polytechnic University
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RESEARCH PROJECTS
  • Postdoctoral research in The Hong Kong Polytechnic University, HK, China, Aug. 2014 - present,
    Project: A Unified Machine Learning Framework for Classifier Design with Applications to Cancer Diagnosis.
    1. Develop biologically-interpretable approaches for protein subcellular localization prediction.
    2. Detect protein complexes in protein-protein interaction datasets.
    3. Integrate sequence-based and network-based approaches into interactomes to unravel the mechanisms of biological systems.
  • Exchange program in The Johns Hopkins School of Medicine, MD, USA and CBIL lab of Virginia Tech, VA, USA , Spring 2013 - Summer 2013,
    Project: Clinical Proteomic Tumor Analysis Consortium (CPTAC).
    1. Construct customized sample-specific protein sequence databases.
    2. Research on proteogenomic integration using customized protein sequence databases derived from TCGA genomic data.
    3. Apply protein subcellular localization prediction methods in ovarian cancer sample post-translational modification (PTM) study.
  • Doctoral research in The Hong Kong Polytechnic University, HK, China, Aug. 2010 - present,
    Project: Fusion of Functional Site Detection and Kernel Discriminant Analysis for Biological Sequence Classification.
    1. Research on biological feature extraction and dimension-reduction approaches.
    2. Discover Gene-Ontology based semantic similarity and hierarchical-structure information and apply them into protein subcellular localization prediction.
    3. Improve multi-label classifiers to adapt to our multi-location protein subcellular localization problems.
  • Doctoral research in The Hong Kong Polytechnic University, HK, China, Aug. 2010 - present,
    Project: Discriminative Models for Biological Sequence Labeling and Segmentation.
    1. Predict protein subcellular localization.
    2. Extract Gene Ontology information and its application in sequence analysis and function prediction.
    3. Design classifiers for computational biology.
  • Undergraduate research in Wuhan University, China, Jan. 2010 – Jun. 2010,
    Project: Design and Simulation of Variable-Rate CDMA-based MAC Protocol.
    1. Research on communication of underwater acoustic sensor networks.
    2. Design protocols for low-noise variable-rate underwater communication.
  • Undergraduate research in Wuhan University, China, Mar. 2009 – Jan. 2010,
    Project: Continuous Data Flow Transmission within Speech Signals.
    1. Develop digital watermarking technology for hidden communication.
    2. Research on speech signal processing for lossless information transmission.

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PUBLICATION ANALYSIS

TECHNICAL SKILLS
  • Algorithm Implementation and Modeling: MATLAB, Perl, R, Python;
  • Programming Languages: C/C++, HTML, Java, Javascript;
  • Editing: Latex, MS Office Word/PowerPoint/Excel/Publisher;
  • Operating Systems: Windows WIN7/Vista/XP, Linux.