Previous RESEARCH PROJECTS

• • Postdoctoral research in University of Pennsylvania, PA, USA, Sep. 2017 - Aug. 2019,

    • Project: Large-Scale Single-Cell Data Analysis.

      1. Develop unsupervised learning approaches for large-scale single-cell RNA-seq clustering.

      2. Integrate single-cell RNA-seq and single-cell ATAC-seq for comprehensive profiling of transcriptomic and epigenetic landscapes.

      3. Investigate machine learning based algorithms for single-cell downstream analysis, including pseudo-time analysis, gene-regulatory network reconstruction, batch effect removal, cell-cell interaction, etc.

    • Project: Probing the Cardiac PGC-1 Regulatory Cascade.

      1. Investigate the estrogen-related receptor (ERR) signaling in the cardiac development from fetal to adult.

      2. Integrate bulk RNA-seq, bulk ChIP-seq with single-nucleus RNA-seq for cell type-specific gene-regulatory landscapes in heart biology.

      3. Do extensive bioinformatics analysis for the roles of ERR gamma in human pluripotent stem cells (hPSC) in heart development.

    • Project: Molecular Control of Muscle Fuel Metabolism.

      1. Investigate the biological and physiological functions of MondoA signaling in skeletal muscle.

      2. Do extensive next-generation sequencing data analysis, including RNA-seq, ATAC-seq, ChIP-seq, etc.

      3. Integrate multiple bioinformatics analysis, including differential gene expression analysis, pathway analysis, motif analysis, chromatin accessibility analysis, etc, for the roles of MondoA in muscle metabolism.

  • Postdoctoral research in Princeton University, NJ, USA, Jun. 2016 - Aug. 2017,

    • Project: Machine Learning for Compressive Privacy.

      1. Develop machine learning approaches for compressive privacy.

      2. Investigating machine learning algorithms in genomic privacy, especially DNA sequence obfuscation.

      3. Design utility-privacy tradeoff architecture for big-data privacy.

    • Project: Explainable Machine Learning for Protein Attribute Prediction.

      1. Develop explainable machine learning algorithms for protein subcellular localization.

      2. Investigate Explainable AI (XAI) algorithms for membrane protein function prediction.

      3. Apply sparse regression methods for interpretable proteomics data analysis.

  • Postdoctoral research in The Hong Kong Polytechnic University, HK, China, Aug. 2014 - Jun. 2016,

    • Project: A Unified Machine Learning Framework for Classifier Design with Applications to Cancer Diagnosis.

• 1. 1. 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. 1. 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.

• Project: Discriminative Models for Biological Sequence Labeling and Segmentation.

• 1. 1. 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. 1. 1. Research on communication of underwater acoustic sensor networks.

        2. Design protocols for low-noise variable-rate underwater communication.

• • • Project: Continuous Data Flow Transmission within Speech Signals.

• 1. 1. 1. Develop digital watermarking technology for hidden communication.

        2. Research on speech signal processing for lossless information transmission.