Nha Nguyen’s Site







Welcome to my world:


          Doctoral, August 2010

University of Texas at Arlington

Electrical Engineering, University of Texas at Arlington, USA.

·       Concentrations: Bioinformatics, Machine Learning and Signal Processing

·       Dissertation:  Wavelet based array comparative genomic hybridization and mass spectrometry data analysis

Master, Sep 2000

HCM City University of Technology

Electrical Engineering, HCM City University of Technology, Vietnam.

·       Concentrations: Electronics and Telecommunications.

·       Dissertation: Neural network to cancel echo signal in telephone system.

Bachelor, May 1996

HCM City University of Technology

Electrical Engineering, HCM City University of Technology, Vietnam.

·       Concentrations: Telecommunications.

·       Dissertation: Designing integrated circuit which can interface to computer to test phone line system.



·       Statistics Signal Processing: I am interested in math, special in statistics signal processing.  What I have been done will be mentioned first. Noise model in array CGH is complicated. No de-noising method works well with this noise one. Luckily, I have explored and developed advanced theories in wavelet transform to smooth array CGH signal well. Besides noise modeling, wavelet footprint has been developed to detect biology marker in mass spectrometry. Structure of protein has been recognized by using novel method in wavelet transform. Detecting DNA copy number in array CGH has been done by using my new theory, Wavelet scalogram, in wavelet transform. Furthermore, I and my collaborator have proposed new theory in complex wavelet transform. This new theory has been used in many other publications. When moving to Penn, I introduced stationary wavelet entropy in first time and applied to predict gene expression. I continue developing wavelet footprint’s theory and applying to detect enriched regions and exploring epigenomic landscapes.

Application of wavelet transform is new in epigenomics and next generation sequencing. New advanced theory in wavelet should be explored more and would be my future work.

·       Machine learning: I am working on deep learning and random forest in promoter and enhancer interaction. Besides two these clustering methods, I also want to do research on other supervised and unsupervised machine learning methods

·       Computational biology and bioinformatics: Mass spectrometry (MS) has been my first research. I have developed a method to detect ions corresponding to peaks in MS. Array CGH is my second data to research about cancer. I have developed many methods to smooth array CGH data and find DNA copy number. When moving to Penn, I had good chances to do research with next sequencing such as epigenetics, ChIP-Seq, GROseq, histone modification, RNA-Seq. Single cell also is my current research. By using these data, diabetes has been explored in my papers. Besides human, mouse and fly are also studied. Many publications have been done by using these data.



Current Work:


           Research Scientist, Department of Genetics, School of Medicine, University of Pennsylvania, 2011-Now