Resume

Education

• Ph.D. in Electrical and Computer Engineering (Honored), University of Miami May 2014

  • Curriculum specialized: Programming Languages and Algorithms; Databases and Distributed Systems; Signals and Systems; Analytical Techniques

• M.Sc. in Soil Microbiology(Major) and Statistics (Minor), University of Florida May 2009

  • Curriculum specialized: Fundamental of Probability and Statistical Theory; Computer Programming in Statistics; Statistical Methods in Research

• B.Sc. in Biological Technology, Nankai University Jun. 2006

  • • Curriculum specialized: Computer System and Programming Languages; Software Development; Quantitative Genetics; Molecular and Computational Biology

Research Experience

• • Bioinformatics, Machine Learning and Statistical Signal Processing Lab, University of Miami Aug. 2009- May 2014

• 1. Design computation methods for accurate sparse model seletion and estimation.

  2. Funded U.S. Natinal Science Fundation, National Institute of Health.

  3. Work along with Dr. Xiaodong Cai, Dr. Shizhong Xu.

  4. Design fast empirical Bayesian variable shrinkage algorithms, with implementation in human genetic mappings.

• • Signal Processing in Networking and Communication Lab, Univ. of Minnesota Jan.-Sep. 2011

• 1. Visiting student in the Digital Technology Center, Department of Electrical and Computer Engineering, University of Minnesota

  2. Worked along with SPiNCOM group (PI: Prof. Georgios Giannakis) in developing network inference methods

     1. Research contribution acknowledged in Journal Paper (X. Cai, J. A. Bazerque, and G. B. Giannakis, PLoS Comput. Biol. 2013, 9(5): e1003068)

• • Microbial Community Ecology Lab, University of Florida Aug. 2006-Jul. 2009

• 1. Completed the missing link in arsenic transfer from soil to plant by arsenic hyperaccumulator project.

  2. UF-IFAS Research Innovation Fund

  3. Worked alongside Professors Lena Ma, Max Teplitski, and Bala Rathinasabapathi .

• Fermentation Engineering Lab, Nankai University Apr.2005-Jun.2006

  • 1. Managed the bioleaching of heavy metal in sewage sludge by Thiobacilus ferrooxidans project.

• 1. Implemented BIOLOG System in bacteria identification

  2. Designed a bioleaching system for sewage sludge remediation.

Machine Learning Algorithms and Software Developments

• EBLASSO (Implemented in Matlab, Rpackage and C/C++)

1. Empirical Bayes LASSO for ultra-dimensional data

2. Sparse feature selection and model inference

3. Features Gaussian and Binomial model for linear regression and classification

4. More robust and faster than state-of-the-art algorithms (RVM, LASSO, BhGLM, HyperLasso, EB, etc.)

5. More accurate prediction

6. R-package freely available upon request

• EBEN (Implemented in Rpackage and C/C++)

1. Empirical Bayes elastic net for ultra-dimensional data

2. Sparse feature selection and model inference encouraging a grouping effect

3. Features Gaussian and Binomial model for linear regression and classification

4. Efficient C/C++ implemented with LAPACK/BLAS

• SML-SEM (Implemented in Matlab, R and C/C++)

1. Sparse-aware Maximum Likelihood for network inference by Structural Equation Model

2. State-of-the-art network topology inference algorithm

3. Capable of inferring topology of large scale of network with thousands of nodes

4. Implemented with high performance computing methods including OPENMPI, LAPACK/BLAS

Programming skills

• • C/C++(since 2003); SAS(since 2007); Matlab(since 2009); R(since 2009); SQL(since 2010)

• High performance computation: LAPACK; SAS-IML; Matlab-MEX; R-ext

Teaching Experience

• Guest Lecturer EEN118 Programming Language I(Spring 2012)

• Teaching Assistant for the following courses in UM, 2011-2013

  1. EEN204: Eletircal Circuit (Instructor: Prof. Reuven Lask)

  2. EEN218: Programming Language II(Instructor: Dr. Nigel John)

  3. EEN310: Introduction to Engineering Probability (Instructor: Dr. Xiaodong Cai)

  4. EEN653: Pattern Recognition (Instructor: Dr. Mohamed Abdel-Mottaleb)

Honors

• Outstanding Ph.D. Research Award, College of E Engineering, University of Miami, 2014

For excellence in Ph.D. dissertation research, Outstanding Ph.D. Research Award is given to the best graduate researcher in the College of Engineering each year

• Eliahu I and Joyce Jury Award for scholarship in Electrical and Computer Engineering, University of Miami, 2013

Established by Dr. Eliahu I. Jury, the pioneer and world-famous scientist known for his contribution to the advancement on Z-transform, the Eliahu I. and Joyce Jury Award is given to the best graduate researcher in the Electrical and Computer Engineering department each year.

• Grinter Fellowship, University of Florida, 2006

• Fundamental Scholarship, Nankai University, 2002

Collaborative Research Projects

• Image Object Identification and Measurement

1. Implemented CellProfiler, ScreenMill and imaging processing software for biological image processing

2. Built up pipelines for imaging denoising, object filtering and identification

• Genetic and physical interaction network construction

1. BioGrid, Pombase, STRING and other database retrieval for genetic and physical interactions

2. Network construction and visualization via Cytoscape and STRING API and GUI

3. Gene Ontology (GO) enrichment analysis for network clusters

4. Ortholog gene group identification and association with interaction networks

• Next Generation Sequencing (NGS) analysis

1. NGS analysis with DNA multiplexing sequences

2. Built up pipelines for sequence analysis capable of handling terabytes of NGS DNA short reads

3. Quantified gene expression level via gene barcode

• Saccharomyces Genome Resequencing Project (SGRP) analysis

1. DNA variants identification from NGS sequencing results obtained from Sanger Genome Institute

2. Probe sequence alignment via Bowtie2 for genotype identification of single nucleotide polymorphisms (SNPs)

3. Genome-wide SNP profiling for a variety of Saccharomyces strains

• Transcriptome analysis for TCGA (The Cancer Genome Atlas) dataset

1. Quantitative analysis of gene expression level in tumor and normal match samples

2. Differentiated expression levels for isoforms of genes

   1. Comparative analysis of alternative splicing pattern among cancers and normal tissues

• Human genome missing genotype imputation

1. Utilized PLINK, IMPUTE, IMPUTE2 and other imputing software

2. Performed genotype impute for sporadic missing genotypes and untyped genomic markers

   • Whole-genome QTL mapping and genome-wide association studies

[P1] Soybean QTL mapping

Collaborative research with Dr. Shizhong Xu (Department of Botany and Plant Sciences, University of California, Riverside)

Contributions to journal paper (Z. Hu, Y. Li, X. Song, Y. Han, X. Cai, S. Xu and W. Li, BMC Genetics 2011, 12:14)

[P2] Barley QTL mapping

Collaborative research with Dr. Shizhong Xu (Department of Botany and Plant Sciences, University of California, Riverside)

Reported in journal paper (Huang, A., Xu, S., Cai, X. Heredity. Revised)

[P3] Rice hybrids QTL mapping

Collaborative research with Dr. Shizhong Xu (Department of Botany and Plant Sciences, University of California, Riverside)

Reported in journal paper (Huang A., Xu S., Cai X., PLoS ONE, 2014 9(1):e87330)

[P4] Drosophila QTL mapping

Collaborative research with Dr. Trudy Mackay (Department of Genetics, University of North Carolina)

[P5] Pathway-based GWAS of human Parkinson disease

Collaborative research with Dr. Eden Martin (Department of Public Health Sciences, University of Miami)

Reported in Journal Paper (Huang, A., Martin, E., Vance, J., Cai, X. Genet. Epidemiol. 2014. 10.1002/gepi.21803)